Local coupon transaction method and device

Abstract

The invention provides a local coupon transaction method and device, and relates to the technical field of local coupon transaction, and the key points of the technical scheme are that the method comprises the steps: obtaining land parcel information and river channel construction partition information; dividing the land parcels in the land parcel information into a plurality of value units according to the river channel construction partition information; obtaining time sequence information of river channel construction; endowing each value unit with a time sequence weight coefficient; generating value flow coupons according to the value units and the time sequence weight coefficients, wherein the value flow coupons comprise time sequence information and space information; obtaining project progress information and greenbelt node position information; calculating the current value of each value unit by adopting a value flow model according to the project progress information and the greenbelt node position information; and establishing a value flow coupon transaction rule according to the current value, and executing the transaction matching of the value flow coupon. The local coupon transaction method and device provided by the invention have the advantages that the transaction strategy is dynamically adjusted in the project proceeding process, and the optimal configuration of the overall benefit is realized.

Description

Technical Field

[0001] The present application relates to the technical field of land securities trading, and in particular, to a land securities trading method and device. Background Art

[0002] Various complex situations often arise in newly developed suburban plots. For example, multiple equity owners each own a portion of the construction land. The area is planned as an ecological residential area, requiring the construction of an ecological landscape river that runs through the entire area to meet the regional drainage and landscape needs. The construction of the river requires some owners to transfer their land, and the future value of the plots along the river will be significantly improved. The river construction must be carried out in the order of upstream and downstream, and cannot be started at the same time. The plots in the hands of some owners span different sections of the river, which will result in value differences due to different timings of river construction. Several public green space nodes are also planned along the river. The location of these nodes directly affects the value of the surrounding plots, but the final location of the nodes needs to be determined based on the actual terrain conditions during the river construction process.

[0003] In this process, due to the construction cycle, there are many uncertainties in its planning. For example, the planned river construction and green space node construction may be shelved or undergo other changes due to various reasons. Such changes often have a huge impact on the surrounding land prices.

[0004] Existing land transaction methods are difficult to cope with such complex situations. Traditional land transactions are usually based on fixed land boundaries and static value assessments, and cannot flexibly deal with factors such as land spatial segmentation, construction schedule, and future value uncertainty. In addition, existing methods also lack a mechanism to dynamically adjust transaction strategies during the project, making it difficult to optimize overall interests, which will hinder land transactions and affect the progress of the project.

[0005] There is an urgent need for improvement in response to the above issues. Summary of the invention

[0006] The purpose of this application is to provide a land transaction method and device, which has the advantages of being able to adapt to the dynamic spatial segmentation needs of land plots, effectively deal with the impact of construction schedule on land value, consider future value uncertainty, dynamically adjust transaction strategies during the project, and achieve optimal configuration of overall benefits.

[0007] In the first aspect, the present application provides a method for land securities trading, and the technical solution is as follows: Obtain land parcel information and river construction zoning information; Dividing the land parcels in the land parcel information into a plurality of value units according to the river channel construction zoning information; Obtain timing information of river construction; Assigning a time sequence weight coefficient to each value unit according to the time sequence information of the river channel construction; Generate a value flow voucher according to the value unit and the time sequence weight coefficient, wherein the value flow voucher includes the time sequence information and the space information; Obtain project progress information and green space node location information; According to the project progress information and the green space node location information, a value flow model is used to calculate the current value of each value unit; The value flow voucher trading rules are established according to the current value, and the transaction matching of the value flow voucher is performed.

[0008] Furthermore, in the present application, the step of assigning a time sequence weight coefficient to each value unit according to the time sequence information of the river channel construction includes: Obtaining location information of each of the value units; Determine the construction sequence of each value unit according to the timing information of the river channel construction; Establishing a time sequence weight coefficient calculation model, wherein the time sequence weight coefficient calculation model includes a construction sequence parameter and a location parameter; Inputting the construction sequence and the location information into the timing weight coefficient calculation model; A corresponding time sequence weight coefficient is assigned to each value unit according to the calculation result of the time sequence weight coefficient calculation model.

[0009] Furthermore, in the present application, the step of establishing a timing weight coefficient calculation model includes: Obtain historical data on river construction; Extracting the correlation coefficient of the impact of construction sequence on the value of the land plot based on the historical data; Obtain terrain condition data at various locations along the river; Calculating a location influence factor according to the terrain condition data; Establishing a mathematical model with the correlation coefficient and the position influence factor; The timing weight coefficient calculation model is generated according to the mathematical model.

[0010] Furthermore, in the present application, the step of calculating the location influence factor according to the terrain condition data includes: Obtain elevation data, slope data and soil data at various locations along the river; Establishing a terrain scoring model, wherein the terrain scoring model includes elevation parameters, slope parameters and soil quality parameters; Inputting the elevation data, slope data and soil quality data into the terrain scoring model; Obtaining a terrain score for each location according to a calculation result of the terrain scoring model; Establishing a position influence factor calculation formula, wherein the position influence factor calculation formula maps the terrain score to a position influence factor; Inputting the terrain score into the location influence factor calculation formula; The position influence factor of each position is obtained according to the calculation result of the position influence factor calculation formula.

[0011] Furthermore, in the present application, the step of calculating the current value of each value unit using a value flow model according to the project progress information and the green space node location information includes: Obtain the completion rate data of the project progress and the coordinate data of the green space nodes; Establish a value calculation function that includes progress parameters and position parameters; Generate a value flow model according to the value calculation function; Inputting the engineering progress completion rate data and the green space node coordinate data into the value flow model; The current value of each value unit is obtained according to the calculation result of the value flow model.

[0012] Furthermore, in the present application, the step of establishing the value flow voucher trading rules according to the current value and executing the transaction matching of the value flow voucher includes: Obtaining the current value and transaction request data of each of the value units; Establish trading rules including trading price ranges and trading volume limits; classifying and sorting the transaction request data according to the transaction rules; Execute transaction matching based on the principle of price priority and time priority; Generate transaction result data and update value flow voucher holding information.

[0013] Furthermore, in the present application, the method further comprises: Based on the value unit and the timing weight coefficient, a standardized transaction contract template is established, and the transaction contract template includes a value unit identification code, a timing weight coefficient, a transaction quantity, a transaction price and a transaction validity period.

[0014] Furthermore, in this application, the step of establishing a standardized transaction contract template includes: Obtaining a value unit identification code and the timing weight coefficient; Entering the value unit identification code and the timing weight coefficient into a preset contract template database; Generate an electronic contract including a value unit identification code, a timing weight coefficient, a transaction quantity, a transaction price, and a transaction validity period based on the contract template database; The electronic contract is digitally signed and encrypted for storage.

[0015] Furthermore, in this application, the value flow model includes: V(t,s) = ∑[αi × Pi(t) × Wi(s)] Among them, V(t,s) represents the value of segment s at time t, αi represents the weight of the i-th influencing factor, Pi(t) represents the time-related progress function, and Wi(s) represents the space-related position function; The value flow model also includes a nonlinear feedback mechanism: V'(t,s) = V(t,s) + β × ΔV(t-1,s) × F(N) Among them, V'(t,s) represents the value after adding nonlinear feedback, β represents the value adjustment coefficient, ∆V represents the value change rate, F(N) represents the proximity effect function, t-1 represents the previous moment, and N represents the number of adjacent value units.

[0016] In a second aspect, the present application proposes a land bond trading device, which includes: The first acquisition module is used to acquire the land plot information and river construction zoning information; A division module, used for dividing the land parcels in the land parcel information into a plurality of value units according to the river channel construction zoning information; The second acquisition module is used to obtain the timing information of the river construction; A first processing module, configured to assign a time sequence weight coefficient to each value unit according to the time sequence information of the river channel construction; A second processing module, configured to generate a value flow voucher according to the value unit and the time sequence weight coefficient, wherein the value flow voucher includes the time sequence information and the space information; The third acquisition module is used to obtain project progress information and green space node location information A fourth processing module, configured to calculate the current value of each of the value units using a value flow model according to the project progress information and the green space node location information; The fifth processing module is used to establish the value flow voucher transaction rules according to the current value and execute the transaction matching of the value flow voucher.

[0017] From the above, it can be seen that the land voucher trading method and device provided by the present application divides the land into value units and assigns time weight coefficients to generate value flow vouchers containing time and space information, adopts a value flow model to dynamically calculate the value, and establishes trading rules to execute matching. It solves the problems that traditional methods are unable to adapt to dynamic spatial segmentation, handle the impact of construction timing, consider future uncertainties, and dynamically adjust strategies. It has the advantages of being able to adapt to the dynamic spatial segmentation needs of land plots, effectively handle the impact of construction timing on land value, consider future value uncertainties, dynamically adjust trading strategies during the project, and achieve the optimal configuration of overall interests. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flow chart of a land security transaction method provided for this application.

[0019] Figure 2 A schematic diagram of the structure of a land securities trading device provided in this application.

[0020] In the figure: 210, a first acquisition module; 220, a division module; 230, a second acquisition module; 240, a first processing module; 250, a second processing module; 260, a third acquisition module; 270, a fourth processing module; 280, a fifth processing module. DETAILED DESCRIPTION

[0021] The technical solutions in the present application will be clearly and completely described below in conjunction with the drawings in the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the present application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0022] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0023] In the newly developed suburban plots, multiple equity owners each own a portion of the construction land. The area is planned as an ecological residential area, which requires the construction of an ecological landscape river that runs through the entire area to solve the regional drainage and landscape needs. The construction of the river requires some owners to transfer their land, but the future value of the plots along the river will be significantly improved. The river construction must be carried out in the order of upstream and downstream, and cannot be started at the same time. The plots in the hands of some owners span different sections of the river, which will result in value differences due to the different timing of the river construction. Several public green space nodes are also planned along the river. The location of these nodes directly affects the value of the surrounding plots, but the final location of the nodes needs to be determined based on the actual terrain conditions during the river construction process.

[0024] Existing land transaction methods are difficult to cope with such complex situations. Traditional land transactions are usually based on fixed land boundaries and static value assessments, and cannot flexibly deal with factors such as land spatial segmentation, construction schedule, and future value uncertainty. In addition, existing methods also lack a mechanism to dynamically adjust transaction strategies during the project, making it difficult to optimize overall benefits. Therefore, a new land transaction method is needed to solve these problems.

[0025] In a specific technical application scenario, a river channel construction is underway in an ecological residential area, and the construction must be carried out in an upstream and downstream order, which results in different sections of land having different development values ​​in different time periods. Suppose that the land owned by a certain owner spans multiple sections of the river channel, and the construction progress of these sections is inconsistent. Due to the sequential nature of the construction, the value of these sections will change at different time points, but the traditional land transaction method cannot dynamically reflect this value change. Specifically, the location of the public green space nodes along the river channel has not yet been finalized, which increases the uncertainty of the future value of the land. Owners cannot reasonably evaluate and trade the value of their land through the existing transaction mechanism, which directly affects the optimal allocation of land resources in the region.

[0026] If the above problems are not solved, it may cause inefficient and unfair land transactions, and fail to reflect the real value changes of the land. Specifically, the owner may not be able to transfer or acquire land at a reasonable price at the right time, resulting in a mismatch of resources. In addition, the lack of a mechanism to dynamically adjust transaction strategies may lead to delays and increased costs of the overall development project. It can be seen that solving this problem is very necessary to achieve efficient use of land resources and smooth progress of the project.

[0027] When faced with complex land transaction situations, this application first considers how to divide the land into smaller units for easier management and trading. This proposes the concept of dividing the land into multiple value units. This division method can more finely reflect the value differences of the land, especially in the context of river construction zoning.

[0028] Next, this application considers how to reflect the impact of the timing of river construction on the value of the plot. To this end, the concept of timing weight coefficient is introduced. By assigning a timing weight coefficient to each value unit, the change in the value of the plot in different time periods can be quantified.

[0029] However, only the value unit and the time-series weight coefficient are not enough to achieve flexible transactions. Therefore, this application proposes the concept of value flow vouchers to convert the value of land into tradable objects. The value flow voucher contains time-series information and spatial information, so that both parties to the transaction can have a more comprehensive understanding of the value composition of the land.

[0030] In order to dynamically reflect the changes in the value of the land, this application introduces a value flow model. This model takes into account the project progress information and the location information of the green space nodes, and can calculate the current value of each value unit in real time. This solves the problem that traditional static evaluation methods cannot reflect the dynamic changes in value.

[0031] Finally, in order to achieve orderly transactions, this application proposes a method to establish value flow trading rules based on current value and execute transaction matching. This method can ensure the fairness and efficiency of transactions, while also being able to adapt to the dynamic characteristics of value changes.

[0032] Therefore, refer to Figure 1 The present application proposes a land bond trading method, the steps of which include: S110, obtaining land plot information and river construction zoning information; S120, dividing the land parcel in the land parcel information into a plurality of value units according to the river channel construction zoning information; S130, obtaining timing information of river channel construction; S140, assigning a time sequence weight coefficient to each value unit according to the time sequence information of the river construction; S150, generating a value flow voucher according to the value unit and the time sequence weight coefficient, wherein the value flow voucher includes time sequence information and space information; S160, obtaining project progress information and green space node location information; S170, using the value flow model to calculate the current value of each value unit according to the project progress information and the green space node location information; S180. Establish value flow voucher trading rules based on the current value, and execute transaction matching of value flow vouchers.

[0033] Among them, plot information refers to the basic data such as the location, area, ownership, etc. of each plot in the area to be developed. Specifically, a geographic information system (GIS) can be used to obtain and manage this information.

[0034] Among them, river construction zoning information refers to the regional division plan during the river project construction process. Specifically, the project planning drawings and construction schedules can be used to determine the scope and construction sequence of each zone.

[0035] Among them, value unit refers to the smaller value assessment units into which the land parcel is divided. Specifically, a grid division method can be adopted to divide the land parcel into several regular or irregular small areas according to the river construction zoning information. In some specific implementation methods, its size can be adjusted as needed. The purpose of setting the value unit is to divide the land parcel spanning multiple river construction zones into different units, so as to calculate their respective values ​​later.

[0036] Among them, the timing weight coefficient refers to the coefficient that reflects the degree of influence of the timing of river construction on the value of the plot. It can be calculated using a specified mathematical model, and factors such as the construction sequence and the distance from the river can be considered.

[0037] Among them, value flow vouchers refer to the conversion of value units into tradable electronic certificates, which can be achieved by using blockchain technology to ensure the security and transparency of transactions.

[0038] Among them, the value flow model refers to a mathematical model used to dynamically calculate the current value of a value unit. It can be constructed using multiple regression analysis or machine learning algorithms, taking into account multiple influencing factors such as project progress and green space node location.

[0039] The core innovation of this application is to introduce the concepts of value unit, time series weight coefficient and value flow voucher, and realize the dynamic evaluation of land value through the value flow model. This method incorporates time and space factors into the value evaluation and transaction process, realizes the dynamic adjustment and refined management of land value, and solves the complex situations that traditional land transaction methods are difficult to deal with.

[0040] The working principle of this application can be described in detail as follows: First, the land parcel information, including the precise coordinates, area and ownership information of each land parcel, was obtained through the geographic information system. At the same time, the river construction zoning information, including the boundaries and construction sequence of each construction section, was obtained from the engineering planning department.

[0041] Then, according to the river construction zoning information, the land parcel is divided into multiple value units. This step can use the spatial analysis function of GIS software to cut the land parcel according to the boundaries of the river construction zoning to form smaller value units corresponding to the construction zoning.

[0042] Next, the timing information of the river construction is obtained, including the start time and expected completion time of each construction section. Based on this information, a timing weight coefficient is assigned to each value unit. The timing weight coefficient can be calculated using a mathematical model that considers the construction sequence and distance factors, for example: W = α * (1 / T) + β * (1 / D) Among them, W is the time series weight coefficient, T is the construction start time (the number of days from the current time), D is the shortest distance from the value unit to the river, and α and β are adjustment parameters.

[0043] According to the value unit and the time sequence weight coefficient, a value flow voucher is generated. Each value flow voucher corresponds to a value unit, containing the spatial information (such as coordinates) and time sequence information (such as construction time) of the unit. The value flow voucher can be realized through blockchain technology, and each voucher has a unique identifier and a related smart contract.

[0044] During the river channel construction process, the project progress information and green space node location information are continuously obtained. The project progress information can be collected in real time through IoT devices, and the green space node location information is determined according to the actual terrain conditions and planning requirements.

[0045] The value flow model is used to calculate the current value of each value unit. The model can be expressed as: V = f(P, G, W) Among them, V is the current value, P is the project progress, G is the distance to the nearest green space node, and W is the time series weight coefficient. Function f can be trained by machine learning algorithms, considering the impact of these factors on the value of the plot in historical data.

[0046] Finally, the trading rules of the value flow voucher are established based on the calculated current value. Specifically, in some embodiments, the trading rules of the value flow voucher established based on the current value refer to the establishment of trading rules for the current value flow voucher. For example, the upper and lower price limits can be set based on the calculated current value, and the single transaction volume can be limited. Transaction matching can be automatically executed through smart contracts to ensure the fairness and efficiency of transactions.

[0047] This working principle fully takes into account the dynamic changes in the value of land plots. By introducing time-series weights and value flow models, it achieves accurate assessment and flexible trading of land plot values ​​in complex situations.

[0048] As a specific implementation method, this application can be applied in a river construction project in a certain ecological residential area. The specific implementation steps are as follows: First, high-precision GPS equipment and drone aerial photography technology were used to obtain the plot information of the ecological residential area. The obtained data was processed by GIS software to generate a digital map containing the precise coordinates, area and ownership information of each plot.

[0049] Then, according to the river engineering planning drawings, the entire river is divided into 10 construction sections. The length of each section is about 500 meters, and the width depends on the terrain, generally between 30-50 meters. The information of these construction sections is superimposed on the digital map.

[0050] Next, the spatial analysis function of GIS software is used to divide the original plot according to the boundaries of the construction section. For example, a plot of 10,000 square meters may be divided into three value units, each located in a different construction section.

[0051] Obtain the timing information of river construction. Assuming that the entire project is planned to be completed within 2 years, the construction time of each section is 2 months. According to the construction sequence, assign a timing weight coefficient to each value unit. Use the formula mentioned above to calculate, where α=0.7, β=0.3, T is in months, and D is in meters.

[0052] For example, for a value unit located in the third construction section and 50 meters away from the center line of the river, its time series weight coefficient is calculated as follows: W = 0.7 * (1 / 4) + 0.3 * (1 / 50) = 0.181 Based on the calculated value unit and timing weight coefficient, a value flow voucher is generated. Each value flow voucher contains a unique 64-bit identifier, the coordinate information of the value unit, the construction section number to which it belongs, the timing weight coefficient, and other information. This information is encoded into the smart contract on the blockchain.

[0053] During the construction process, the project progress information is collected in real time. The progress data is updated every day and the completion percentage of each construction section is recorded. At the same time, the specific locations of the five green space nodes are determined according to the actual terrain conditions, and their coordinate information is entered into the system.

[0054] The trained machine learning model is used as the value flow model to calculate the current value of each value unit every day based on the latest project progress and green space node location information. The model input includes the project progress percentage, the distance to the nearest green space node, and the time series weight coefficient, and the output is the estimated result of the current value.

[0055] Finally, establish trading rules for value flow vouchers. For example, set a single transaction volume of no more than 5% of the total generated, and price fluctuations of no more than 10% of the previous day's closing price. Transaction matching is automatically executed through smart contracts, and trading is open from 9:00 am to 3:00 pm every weekday.

[0056] In this way, the technical solution of the present application can effectively handle complex land transaction situations and realize dynamic evaluation and flexible transaction of land value.

[0057] In some of the above-mentioned embodiments, during the implementation of the present application, there is still the problem of how to assign a reasonable timing weight coefficient to each value unit according to the timing information of the river construction.

[0058] In this regard, the present application further proposes the steps of assigning a timing weight coefficient to each value unit according to the timing information of the river channel construction, including: obtaining the location information of each value unit; determining the construction sequence of each value unit according to the timing information of the river channel construction; establishing a timing weight coefficient calculation model, the timing weight coefficient calculation model including construction sequence parameters and location parameters; inputting the construction sequence and location information into the timing weight coefficient calculation model; assigning a corresponding timing weight coefficient to each value unit according to the calculation result of the timing weight coefficient calculation model.

[0059] This application converts the timing information of river channel construction into quantifiable timing weight coefficients through systematic steps. It takes into account the location characteristics and construction sequence of the value unit, and establishes a calculation model that includes time and space factors, so that each value unit can be assigned a reasonable timing weight coefficient. This method not only considers the impact of the construction sequence on the value of the plot, but also takes the location factor into consideration, making the allocation of weight coefficients more accurate and reasonable.

[0060] The core invention of this solution is to establish a time-series weight coefficient calculation model that comprehensively considers construction sequence and location factors. This model can objectively reflect the impact of river construction on value units at different locations, effectively solving the problem that traditional methods are difficult to accurately quantify time-series impacts. It converts complex spatiotemporal factors into calculable parameters, and realizes automated weight allocation through the model, greatly improving the accuracy and efficiency of value assessment in land transactions.

[0061] The technical solution proposed in this application includes multiple key steps, each of which has its specific implementation method and function. First, obtaining the location information of each value unit can be achieved in a variety of ways, such as using a GPS positioning system, a geographic information system (GIS), or through manual measurement. This location information may include longitude and latitude coordinates, distance relative to the river, elevation, and other data.

[0062] Secondly, determine the construction sequence of each value unit based on the timing information of river construction. This step can be achieved based on the project planning documents, construction schedule or expert evaluation. The construction sequence can be linear (such as from upstream to downstream) or segmented and parallel, depending on the actual situation of the project.

[0063] Establishing a time-series weight coefficient calculation model is the core step of this solution. This model can take many forms, such as a linear regression model, a neural network model, or a rule-based expert system. The construction sequence parameter in the model can be a numerical value indicating the order of construction, such as an integer from 1 to 10, where a smaller value indicates an earlier construction. The location parameter can be the distance from the centerline of the river channel, the elevation difference, etc.

[0064] The process of inputting construction sequence and location information into the model can be done automatically through the software interface or manually. The format and units of the input data need to match the requirements of the model.

[0065] Finally, the time series weight coefficient is assigned according to the model calculation results. In this step, a value range of the weight coefficient can be set, such as between 0 and 1, and the output of the model is mapped into this range through normalization.

[0066] The location information and construction sequence jointly determine the temporal and spatial position of a value unit in the entire project, which directly affects the potential for its value change. The computational model integrates this information and quantifies the impact of timing and location on value through mathematical methods. The final weight coefficient assignment process converts the theoretical results of the model into practical parameters.

[0067] The technical solution of this application adopts a systematic and quantitative approach to solve the problem of how to assign a reasonable time sequence weight coefficient to each value unit based on the time sequence information of river channel construction. First, by obtaining the location information of the value unit, a spatial data foundation is established. This step ensures the accuracy of subsequent calculations, because value units at different locations will be affected to varying degrees by river channel construction.

[0068] Next, the construction order of each value unit is determined based on the timing information of the river construction. This step takes into account the time dimension of the river construction and reflects the impact of construction at different times on the value. For example, the area that is constructed first may benefit from the value increase brought by the river improvement earlier, while the area that is constructed later may be disturbed by the construction in the short term.

[0069] The core innovation of this solution is to establish a time sequence weight coefficient calculation model. This model comprehensively considers the two key factors of construction sequence and location, and integrates time sequence and spatial information into a unified calculation framework. This method overcomes the limitation of traditional evaluation methods that often only consider a single factor, and provides a more comprehensive and scientific calculation basis.

[0070] The process of inputting construction sequence and location information into the model enables personalized calculation of each specific value unit, which means that each value unit can obtain a unique weight coefficient that reflects its specific time and space conditions, rather than using a rough, uniform weight.

[0071] Finally, the corresponding time-series weight coefficient is assigned to each value unit based on the model calculation results, ensuring the objectivity and accuracy of the weight distribution. This model-based assignment method avoids the bias that may be caused by human subjective judgment and improves the fairness and credibility of the entire evaluation process.

[0072] Through this method, this application not only considers the impact of construction sequence on the value of the land, but also takes location factors into consideration, making the allocation of weight coefficients more accurate and reasonable. This method of comprehensively considering time and space factors can more accurately reflect the actual impact of river construction on different value units, thereby providing a more reliable value assessment basis for subsequent land transactions.

[0073] As a preferred implementation, the present application can be implemented through the following specific steps: First, a high-precision GPS device is used to obtain the coordinates of the center point of each value unit, accurate to the meter level. At the same time, a laser rangefinder is used to measure the vertical distance from each value unit to the center line of the river.

[0074] Secondly, according to the project planning documents, the entire river construction process is divided into 10 stages, and each stage is assigned an integer value from 1 to 10 to indicate the construction order. For example, the first area to be constructed is assigned a value of 1, and the last area to be constructed is assigned a value of 10.

[0075] Then, a time series weight coefficient calculation model based on multivariate linear regression is established. The mathematical expression of the model can be: W = a * S + b * D + c Among them, W is the timing weight coefficient, S is the construction sequence parameter (an integer from 1 to 10), D is the distance to the center line of the river (unit: meter), and a, b, and c are coefficients.

[0076] Next, the construction sequence parameters and distance data for each value unit are input into the model. For example, for a value unit with a construction sequence of 3 and a distance of 50 meters from the centerline of the river, the input data is (3, 50).

[0077] Finally, the model is used to calculate the time series weight coefficient of each value unit. Assuming that the range of the model calculation result is 0-100, it can be normalized to the range of 0-1 by dividing it by 100 as the final time series weight coefficient.

[0078] Through this method, the application can assign a weight coefficient to each value unit that reflects its spatiotemporal characteristics, thereby more accurately evaluating its value changes during the river channel construction process. This data- and model-based method has higher accuracy and objectivity than traditional empirical estimates. It can capture subtle spatial differences and temporal effects, providing a more reliable value basis for land securities transactions.

[0079] Compared with the prior art, the method of the present application has significant advantages. Traditional land valuation methods usually only consider static location factors, or only roughly consider the impact of construction sequence. The method proposed in this application realizes a dynamic evaluation of value changes by establishing a comprehensive model that organically combines time and space factors. This method not only improves the accuracy of the evaluation, but also enhances the fairness and transparency of the entire transaction process. In addition, the method of the present application has good scalability and adaptability, and the model parameters can be adjusted according to the needs of specific projects, making it suitable for river construction projects of different sizes and types.

[0080] In some of the above-mentioned embodiments, during the implementation of the present application, there is still the problem of how to establish a temporal weight coefficient calculation model that accurately reflects the impact of construction sequence and terrain conditions on the value of the land.

[0081] In this regard, the present application further proposes the steps of establishing a time series weight coefficient calculation model, including: obtaining historical data on river construction; extracting the correlation coefficient of the impact of construction sequence on the value of the land based on the historical data; obtaining terrain condition data at various locations along the river; calculating the position influence factor based on the terrain condition data; establishing a mathematical model for the correlation coefficient and the position influence factor; and generating a time series weight coefficient calculation model based on the mathematical model.

[0082] This application obtains historical data and terrain condition data, extracts key influencing factors, and establishes a mathematical model to generate a time series weight coefficient calculation model. Specifically: First, historical data on river channel construction is obtained to provide basic data support for the model. This historical data may include information such as the construction sequence of similar projects in the past and changes in the value of land plots.

[0083] Secondly, the correlation coefficient of the impact of construction sequence on land value is extracted from historical data to quantify the impact of construction sequence. This step may involve data analysis and statistical modeling, such as using regression analysis or time series analysis.

[0084] Then, obtain the terrain condition data of each location along the river and consider the impact of terrain factors on the value of the land. The terrain condition data can include information such as elevation, slope, and soil quality.

[0085] Next, the location impact factor is calculated based on the terrain condition data to transform the terrain factors into quantifiable indicators. This may involve establishing a terrain scoring model to convert various terrain features into a unified scoring standard.

[0086] After that, the correlation coefficient and the location influencing factor are combined to establish a mathematical model that comprehensively considers the influence of construction sequence and terrain conditions. This mathematical model can be a multivariate function, in which the construction sequence and terrain conditions are used as independent variables and the land value is used as the dependent variable.

[0087] Finally, a time sequence weight coefficient calculation model is generated based on the established mathematical model. This model will be able to calculate the corresponding time sequence weight coefficient according to the given construction sequence and terrain conditions.

[0088] In practical applications, the technical solution of the present application can be implemented by the following steps: First, database or data warehouse technology can be used to store and manage historical data on river construction. This data can come from multiple completed river construction projects, including information such as the construction sequence of each project and changes in the value of land plots at each stage.

[0089] Secondly, data mining and machine learning techniques are used to extract the correlation coefficient of the impact of construction sequence on the value of the plot from historical data. For example, time series analysis methods such as the autoregressive integrated moving average model (ARIMA) can be used to analyze the relationship between the construction sequence and the change in plot value to obtain the correlation coefficient.

[0090] Then, the geographic information system (GIS) technology is used to obtain and process the terrain condition data of various locations along the river, which can be achieved through digital elevation model (DEM), remote sensing image analysis and other technologies.

[0091] Next, a terrain scoring model is established to calculate the location impact factor. This model can be a weighted sum model, in which various terrain features (such as elevation, slope, soil quality, etc.) have corresponding weights. For example: Location factor = w1 * elevation score + w2 * slope score + w3 * soil score Among them, w1, w2, and w3 are corresponding weight coefficients, which can be determined through expert evaluation or data analysis.

[0092] Afterwards, multiple regression analysis or machine learning methods (such as artificial neural networks) are used to establish a mathematical model that comprehensively considers the correlation coefficient and position influencing factors. The general form of this model can be as follows: Time series weight coefficient = f(correlation coefficient, position influence factor) Where f is a nonlinear function, and its specific form can be determined by training data.

[0093] Finally, this mathematical model is encapsulated into a callable function or module to form the final time series weight coefficient calculation model. This model can be integrated into the entire land securities trading system to dynamically calculate the time series weight coefficient of each value unit.

[0094] Through this method, the application can more accurately reflect the impact of construction sequence and terrain conditions on the value of the land, thereby providing a more reliable basis for the generation and trading of value flow vouchers. The advantages of this method are: The two key factors of construction sequence and terrain conditions were comprehensively considered to improve the accuracy and applicability of the model.

[0095] By using historical data, the model is supported by actual data, which enhances the reliability and persuasiveness of the model.

[0096] The location influence factor is introduced to consider the impact of terrain conditions on the value of the land, making the model closer to the actual situation.

[0097] The mathematical modeling method is used to make the calculation of the timing weight coefficient scientific and repeatable.

[0098] Through a data-driven approach, the model can be continuously optimized as new data accumulates, improving long-term applicability.

[0099] Compared with the prior art, the method of the present application has obvious advantages in the following aspects: Data-driven: Existing technologies may rely mainly on expert experience or simple linear models, while the method of this application is based on a large amount of historical data and can capture more complex nonlinear relationships.

[0100] Dynamic adjustment: The model of this application can be continuously updated based on new historical data, while existing technologies may use fixed evaluation methods that are difficult to adapt to market changes.

[0101] Integration of multiple factors: This application takes into account both construction sequence and terrain conditions, while existing technologies may only focus on a single factor and fail to fully reflect the factors affecting the value of the plot.

[0102] Explainability: By using a clear mathematical model, the method of this application has good explainability, which helps to increase the trust of all parties involved in the transaction.

[0103] Accurate quantification: This application accurately quantifies the impact of various factors through mathematical models, while existing technologies may only provide a rough qualitative assessment.

[0104] Through this approach, this application not only solves the problem of how to accurately reflect the impact of construction sequence and terrain conditions on the value of land, but also provides a more scientific and reliable foundation for the entire land trading system, which helps to achieve fairer and more efficient transactions.

[0105] In some of the above embodiments, during the implementation of the present application, there is still a problem of how to calculate the position influence factor according to the terrain condition data.

[0106] In this regard, the present application further proposes to obtain elevation data, slope data and soil data of each location along the river channel; establish a terrain scoring model, which includes elevation parameters, slope parameters and soil parameters; input the elevation data, slope data and soil data into the terrain scoring model; obtain the terrain score of each location based on the calculation results of the terrain scoring model; establish a position influence factor calculation formula, which maps the terrain score to the position influence factor; input the terrain score into the position influence factor calculation formula; and obtain the position influence factor of each location based on the calculation results of the position influence factor calculation formula.

[0107] First, obtain the elevation data, slope data and soil data of each location along the river. These data are the basic inputs for calculating the location impact factor and reflect the key characteristics of the terrain. Secondly, establish a terrain scoring model, which integrates the three parameters of elevation, slope and soil quality for comprehensive evaluation of terrain conditions. Then, input the data into the terrain scoring model and calculate the terrain score. This step converts the original terrain data into a comparable score for subsequent processing. Next, establish a location impact factor calculation formula, which further converts the terrain score into a location impact factor, reflecting the degree of influence of terrain conditions on the value of the plot. Finally, calculate the location impact factor of each location, and the final location impact factor can be used for subsequent calculation of the time series weight coefficient, thereby affecting the generation and transaction of value flow vouchers.

[0108] By gradually processing and transforming the terrain data, we can finally obtain the location influence factor that can quantify the impact of terrain on the value of the plot. This method takes into account a variety of terrain factors, and through the design of models and formulas, realizes the scientific conversion from original terrain data to location influence factors. Through this method, we can objectively calculate the degree of influence of terrain conditions at various locations along the river on the value of the plot. This provides an important basis for the subsequent calculation of the time series weight coefficient, which helps to more accurately evaluate and predict the value changes of the plot. At the same time, this method also provides a more reasonable basis for the generation and trading of value flow coupons, which is conducive to achieving the fairness and scientificity of the entire land voucher trading system.

[0109] In the technical solution proposed in this application, obtaining elevation data, slope data and soil quality data at various locations along the river can be achieved in a variety of ways. For example, elevation data can be obtained through satellite mapping, laser radar scanning or field measurement; slope data can be calculated from elevation data or directly measured using an inclinometer; soil quality data can be obtained through geological drilling and soil sampling and analysis methods.

[0110] Establishing a terrain scoring model is a key step in this scheme. The terrain scoring model can be in many forms, such as a linear weighted model, a fuzzy comprehensive evaluation model, or an artificial neural network model. Taking the linear weighted model as an example, it can be expressed as: S = w1H + w2G + w3T Among them, S is the terrain score, H, G, and T are the normalized elevation, slope, and soil quality scores, respectively, and w1, w2, and w3 are the corresponding weight coefficients.

[0111] In the process of inputting elevation data, slope data and soil data into the terrain scoring model, the original data needs to be preprocessed and standardized. For example, elevation data can be converted into relative elevation, slope data can be converted into percentage, and soil data can be converted into suitability score. Standardization can be done by using the maximum and minimum method or the Z-score method.

[0112] After obtaining the terrain score of each location based on the calculation results of the terrain scoring model, it is necessary to establish a calculation formula for the location influence factor. This formula can be a simple linear mapping or a more complex nonlinear function. For example, an S-type function can be used: F = 1 / (1 + e^(-k(S-S0))) Among them, F is the location influence factor, S is the terrain score, k is the curve slope parameter, and S0 is the intermediate threshold.

[0113] The terrain score is input into the position influence factor calculation formula, and the position influence factor of each position is obtained according to the calculation result. This process can be automatically completed by a computer program. In order to improve the calculation efficiency, parallel computing or distributed computing technology can be used.

[0114] The technical solution of this application establishes a comprehensive terrain assessment system by comprehensively considering multiple terrain factors such as elevation, slope and soil quality. Compared with the traditional method that only considers a single factor, this method can more accurately reflect the impact of terrain conditions on the value of the plot. For example, in the traditional method, only the elevation factor may be considered, while the impact of slope and soil quality is ignored, resulting in an incomplete assessment result.

[0115] The method of this application achieves a scientific conversion from raw terrain data to location influence factors by establishing a terrain scoring model and a location influence factor calculation formula. This conversion process takes into account the interaction and combined impact of different terrain factors, avoiding the errors that may be caused by simple superposition. For example, in some cases, a plot with a higher elevation but a gentler slope may be more valuable than a plot with a lower elevation but a steeper slope. This method can accurately capture this complex relationship.

[0116] In addition, the method of the present application has good adaptability and scalability. By adjusting the parameters of the terrain scoring model and the calculation formula of the location influence factor, it can adapt to the needs of different regions and different types of projects. For example, in mountainous projects, it may be necessary to increase geological stability parameters, and in coastal projects, it may be necessary to consider flood control factors. This method can meet these needs by expanding the model.

[0117] As a preferred implementation, the present application can be implemented according to the following steps: First, the elevation data along the river channel was obtained through drone aerial survey. At the same time, high-precision GPS equipment was used to measure ground control points to correct the aerial survey data. Slope data was calculated by numerical differentiation of elevation data. Soil quality data was obtained by taking soil samples every 100 meters.

[0118] Secondly, a terrain scoring model is established. This embodiment uses an improved analytic hierarchy process (AHP) to determine the weights of each parameter. After expert evaluation and consistency test, the weight of the elevation parameter is 0.4, the weight of the slope parameter is 0.35, and the weight of the soil parameter is 0.25. The terrain scoring model expression is: S = 0.4H + 0.35G + 0.25T Among them, H, G, and T are the normalized elevation, slope, and soil quality scores, respectively.

[0119] Then, the preprocessed elevation data, slope data, and soil data are input into the terrain scoring model. Preprocessing includes removing outliers, interpolating and filling missing data, etc. Data input is processed in batch mode, and high-performance computing clusters are used for parallel computing.

[0120] Next, a calculation formula for the position influence factor is established. This embodiment uses an improved Logistic function: F = 1 / (1 + e^(-0.1(S-50))) Among them, F is the location influence factor and S is the terrain score.

[0121] Finally, the terrain score is input into the location influence factor calculation formula to obtain the location influence factor of each location. The calculation results are separated by 0.01 to form a continuous location influence factor distribution map.

[0122] Through this implementation method, the present application can efficiently and accurately calculate the location influence factor of each location along the river, providing reliable basic data for subsequent time series weight coefficient calculation and value flow voucher generation.

[0123] Compared with the prior art, the technical solution of the present application has significant advantages. Traditional methods usually only consider a single or a few terrain factors, such as only considering elevation or slope, which makes it difficult to fully reflect the impact of terrain conditions on the value of the plot. The present application comprehensively considers multiple factors such as elevation, slope and soil quality, and can evaluate terrain conditions more comprehensively and accurately. In addition, traditional methods often use simple linear models or empirical formulas, which make it difficult to capture the complex relationship between terrain factors. The present application achieves a nonlinear conversion from original terrain data to location influence factors by establishing a scientific terrain scoring model and a location influence factor calculation formula, which better reflects the actual situation. Finally, traditional methods usually lack flexibility and are difficult to adapt to the special needs of different regions and projects. The method of the present application has good scalability and adaptability, and can meet the needs of various complex situations by adjusting model parameters and formulas. These advantages enable the technical solution of the present application to better solve the problem of how to calculate location influence factors based on terrain condition data, and provide more accurate and reliable basic data for the land securities trading system.

[0124] In some of the above-mentioned embodiments, during the implementation of the present application, there is still the problem of how to calculate the current value of each value unit based on the project progress information and the green space node location information.

[0125] In this regard, the present application further proposes to obtain the completion rate data of the project progress and the coordinate data of the green space nodes; establish a value calculation function including progress parameters and location parameters; generate a value flow model based on the value calculation function; input the project progress completion rate data and the green space node coordinate data into the value flow model; and obtain the current value of each value unit based on the calculation results of the value flow model.

[0126] The value calculation function can be implemented in many ways. For example, a linear weighted model can be used, where the progress parameter weight can be set to 0.6 and the location parameter weight can be set to 0.4. Alternatively, a nonlinear model can be used, where an exponential function is introduced to reflect the acceleration effect of progress on value. The location parameter can take into account the radiation range of the green space node, which is usually set to an influence radius of 300-500 meters.

[0127] In the process of generating the value flow model, it is necessary to consider the corresponding relationship between the progress completion rate and the value growth. When the project progress reaches 30%, the value growth rate is about 15%; when it reaches 60%, the growth rate can reach 40%; after completion, the growth rate can reach 80%. In terms of location parameters, the value decay rate is about 5% for every 100 meters away from the green space node.

[0128] By inputting the project progress completion rate data and green space node coordinate data, the value flow model can automatically calculate the value status of each value unit at different time points. This dynamic calculation method overcomes the limitations of traditional static evaluation methods and makes value evaluation more accurate and timely.

[0129] In the specific implementation, first obtain the project progress completion rate data, for example, the completion rate of a certain section is 45%. At the same time, obtain the green space node coordinate data, such as node A is located at (x=100, y=200). Establish a value calculation function V=P×W, where V is the current value, P is the progress impact function, and W is the location impact function. The progress impact function can be expressed as P=1+0.8×(C / 100), where C is the completion rate; the location impact function can be expressed as W=1-0.05×(D / 100), where D is the distance from the green space node (meters). Finally, substitute the data into the model to calculate the current value of the value unit.

[0130] Compared with the existing technology that only relies on static evaluation methods, this application establishes a dynamic value flow model, which can reflect the impact of project progress and location factors on value units in real time, thereby improving the accuracy and timeliness of value evaluation. At the same time, through standardized calculation methods, the subjectivity of the evaluation is reduced and the credibility of the evaluation results is improved.

[0131] In some of the above-mentioned embodiments, during the implementation of the present application, there is still the problem of how to establish value flow trading rules and execute transaction matching according to the current value.

[0132] In this regard, the present application further proposes to obtain the current value and transaction request data of each value unit; establish transaction rules including transaction price ranges and transaction volume limits; classify and sort transaction request data according to the transaction rules; perform transaction matching according to the principles of price priority and time priority; generate transaction result data and update value flow voucher holding information.

[0133] This application solves the problem of how to establish value flow voucher trading rules and perform transaction matching based on current value by establishing a complete set of trading rules and matching mechanisms. The solution first obtains the current value and transaction request data of each value unit, and then establishes rules including price ranges and transaction volume limits, which helps maintain market stability. Next, the matching efficiency is improved by classifying and sorting the transaction requests. Matching is carried out based on the principles of price priority and time priority to ensure the fairness of the transaction. Finally, by generating transaction results and updating holding information, the timeliness and accuracy of market information are guaranteed. This series of steps forms a complete transaction process that can effectively manage the transaction of value flow vouchers and adapt to changes in the current value of value units.

[0134] Specifically, the technical solution of this application includes the following key steps: Obtain the current value and transaction request data of each value unit: This step can be achieved through a real-time database or API interface. For example, you can set a scheduled task to obtain the latest current value of each value unit every 5 minutes, and extract unfulfilled transaction request data from the order pool of the trading system.

[0135] Establish trading rules including trading price range and trading volume limit: This step can be adjusted dynamically according to the current market situation. For example, the trading price range can be set to ±10% of the current value, and the trading volume limit can be set to 20% of the holdings of a single trader or 5% of the total circulation, whichever is smaller. These parameters can be adjusted in real time according to market fluctuations.

[0136] Classify and sort the transaction request data according to the transaction rules: a multi-level sorting algorithm can be used. First, classify according to the transaction type (buy / sell), then sort by price (from high to low when buying, from low to high when selling), and finally sort by time. This sorting method can improve the efficiency of subsequent matching.

[0137] Execute transaction matching according to the principle of price priority and time priority: This can be achieved by using the Order Book model. The system maintains a buy order queue and a sell order queue, and each time takes the order with the best price from the head of the queue for matching. If the prices are the same, they are matched in chronological order. This method can ensure the fairness and efficiency of transactions.

[0138] Generate transaction result data and update value flow voucher holding information: After each successful matchmaking, the system needs to generate a transaction record, including information such as the transaction parties, transaction price, and transaction quantity. At the same time, the number of value flow vouchers held by both parties needs to be updated. These operations can be done through database transactions to ensure data consistency.

[0139] The current value data obtained directly affects the formulation of transaction rules, which in turn determine how to classify and sort transaction requests. The sorted transaction request data is the basis for matching, and the matching results need to be updated to the holding information in a timely manner.

[0140] The technical solution of this application has the following advantages in solving the problem of how to establish value flow voucher trading rules and execute transaction matching based on the current value: First, by obtaining real-time current value data, trading rules can reflect market conditions in a timely manner, avoiding trading deviations that may be caused by using outdated data.

[0141] Secondly, establishing rules including price ranges and trading volume limits effectively prevents drastic price fluctuations and excessive speculation, and maintains market stability.

[0142] Thirdly, a multi-level sorting algorithm is used to process transaction requests, which improves the efficiency of subsequent matching and enables a faster response to market demand.

[0143] Finally, the matching principles of price priority and time priority are adopted to ensure the fairness of transactions, while the accuracy of market information is guaranteed by timely updating of transaction results and holding information.

[0144] As a preferred implementation, the present application can be applied in the following specific scenarios: Assume that the current value of a certain value unit A is 100 yuan / square meter, and the system obtains the following transaction request data: Buy request 1: 95 yuan / m2, 1000 m2, timestamp 10:00:00 Buy request 2: 98 yuan / m2, 800 m2, timestamp 10:00:05 Sell ​​request 1: 102 yuan / m2, 1500 m2, timestamp 10:00:02 Sell ​​request 2: 100 yuan / m2, 500 m2, timestamp 10:00:08 The system first establishes trading rules, setting the transaction price range to 90-110 yuan / square meter (±10% of the current value), and limiting the single transaction volume to within 2,000 square meters.

[0145] The transaction requests are then categorized and sorted: Buy queue: Request 2 (98 yuan), Request 1 (95 yuan) Selling queue: Request 2 (100 yuan), Request 1 (102 yuan) When executing a match, the system first matches buy request 2 and sell request 2.

[0146] Next, the system generates transaction result data, records the detailed information of the transaction, and updates the number of value flow vouchers held by the relevant account.

[0147] Through this specific example, it can be seen that the technical solution of the present application can effectively process complex transaction requests and improve transaction efficiency while ensuring transaction fairness.

[0148] Compared with the prior art, the technical solution of the present application has significant advantages. Traditional trading systems usually adopt fixed trading rules, which are difficult to adapt to the rapidly changing market environment. However, the present application greatly improves the flexibility and adaptability of the system by obtaining current value data in real time and dynamically adjusting trading rules. In addition, traditional systems often only focus on price matching and ignore the restrictions on trading volume, which easily leads to market fluctuations. The present application effectively controls market risks by introducing trading volume restrictions. These innovations make the present application more efficient and stable than the prior art when dealing with complex value flow transactions.

[0149] In some of the above-mentioned embodiments, during the implementation of the present application, there is still a technical problem of how to solve the contract standardization and transaction efficiency in the land securities transaction process.

[0150] In this regard, the present application further proposes to establish a standardized transaction contract template based on the value unit and the timing weight coefficient. The transaction contract template includes a value unit identification code, a timing weight coefficient, a transaction quantity, a transaction price and a transaction validity period.

[0151] This application achieves the standardization and efficiency of land transactions by establishing a standardized transaction contract template. The standardized template simplifies the transaction process, reduces information asymmetry, and improves transaction efficiency. At the same time, by introducing the value unit identification code and the time series weight coefficient, the contract template can accurately reflect the spatial characteristics and time value of the land, providing a basis for fair pricing. This method not only ensures the flexibility of the transaction, but also ensures the standardization and traceability of the transaction, and effectively solves the standardization and efficiency problems in complex land transactions.

[0152] In this application, the standardized transaction contract template contains several key elements: value unit identification code, timing weight coefficient, transaction quantity, transaction price and transaction validity period. Among them, the value unit identification code is used to uniquely identify each value unit, which is convenient for transaction tracking and management. The timing weight coefficient reflects the importance of different value units in the timing of river construction, which helps to reasonably price. The transaction quantity, transaction price and transaction validity period are the basic elements of the transaction to ensure the rights and interests of both parties to the transaction.

[0153] Specifically, the value unit identification code can be encoded in a variety of ways, such as a combination of letters and numbers, or a more advanced identification method such as a QR code. The time sequence weight coefficient can be dynamically adjusted according to the specific situation of the river construction, for example, it can be set to a decimal between 0 and 1, and the larger the value, the higher the importance of the value unit in the construction sequence. The transaction quantity can be in square meters, the transaction price can be in the form of a unit price per square meter, and the transaction validity period can be accurate to a specific date and time.

[0154] Furthermore, the standardized transaction contract template of the present application may also include other optional items, such as information of the transaction parties, payment methods, breach of contract clauses, etc. These additional information can be flexibly added according to specific transaction requirements to further improve the integrity and practicality of the contract.

[0155] Therefore, the standardized transaction contract template of this application not only simplifies the transaction process, but also provides a unified framework for complex land transactions. This standardized template can greatly reduce the communication costs of the two parties in the contract formulation process and reduce the risk of disputes caused by non-standard contracts. At the same time, since the template contains the value unit identification code and the time sequence weight coefficient, the two parties can more accurately evaluate the value of the land and make more reasonable transaction decisions.

[0156] As a preferred implementation, the present application can combine the standardized transaction contract template with the smart contract technology. For example, a blockchain-based smart contract system can be developed to encode information such as the value unit identification code and the timing weight coefficient into the smart contract. When the preset conditions are met, the smart contract automatically executes the transaction, further improving the transaction efficiency and security.

[0157] In the specific implementation process, the following steps can be followed to establish and use a standardized transaction contract template: 1. Design template structure: According to the characteristics of local securities transactions, design a spreadsheet or database structure that includes fields such as value unit identification code, timing weight coefficient, transaction quantity, transaction price and transaction validity period.

[0158] 2. Develop template generation tool: Develop a software tool that can automatically generate standardized transaction contract templates based on the input value unit information.

[0159] 3. Data filling: When a new value unit is divided, a unique identification code is automatically generated for it, and the corresponding timing weight coefficient is calculated based on the timing information of river construction and filled in the template.

[0160] 4. Transaction information entry: When conducting a specific transaction, both parties enter information such as transaction quantity, transaction price and transaction validity period through the system interface.

[0161] 5. Contract generation: The system automatically integrates all information and generates a complete standardized transaction contract.

[0162] 6. Electronic signature: Both parties to the transaction electronically sign the generated contract to confirm the content of the transaction.

[0163] 7. Contract storage: Store the signed contract in a secure database or blockchain system to ensure its immutability and traceability.

[0164] In this way, this application not only standardizes the land bond transaction process, but also greatly improves transaction efficiency. Compared with the traditional manual contract formulation method, the standardized transaction contract template of this application can significantly reduce the contract formulation time and reduce the risk of human error. At the same time, because the contract template contains the key information of the value unit, the transaction parties can understand the characteristics of the transaction subject more quickly and accurately, and make more informed decisions. In addition, the standardized contract format also facilitates subsequent data analysis and management, providing strong support for the healthy development of the land bond market.

[0165] In some of the above-mentioned embodiments, during the implementation of the present application, there is still a technical problem of how to solve the establishment of a standardized transaction contract template to realize value flow transactions.

[0166] In this regard, the present application further proposes the steps of establishing a standardized transaction contract template, including: obtaining a value unit identification code and a timing weight coefficient; entering the value unit identification code and the timing weight coefficient into a preset contract template database; generating an electronic contract based on the contract template database containing a value unit identification code, a timing weight coefficient, a transaction quantity, a transaction price and a transaction validity period; and digitally signing and encrypting the electronic contract for storage.

[0167] This application solves the problem of contract management in value flow voucher transactions by establishing a standardized transaction contract template. First, by obtaining the value unit identification code and the timing weight coefficient, it is ensured that each contract can uniquely correspond to a specific value unit and its timing characteristics. Then, by entering these data into the preset contract template database, standardized management of contract templates is achieved. Based on this database, the system can automatically generate an electronic contract containing all necessary information, which improves efficiency and reduces human errors. Finally, through digital signatures and encrypted storage, the security and legal effect of the contract are guaranteed. This method not only simplifies the transaction process, but also improves the transparency and traceability of transactions, providing reliable technical support for the transaction of value flow vouchers.

[0168] Furthermore, the technical solution of the present application involves multiple possible implementations of the following key features: There are many ways to obtain the value unit identification code and the timing weight coefficient. For example, the value unit identification code can be obtained by scanning a QR code, or by entering a string in a specific format. The timing weight coefficient can be automatically calculated according to the construction progress through a preset algorithm, or it can be manually entered by the system administrator.

[0169] The default contract template database can use a relational database such as MySQL, or a non-relational database such as MongoDB. The choice of database depends on the specific needs and performance requirements of the system.

[0170] Electronic contracts can be generated by either template filling or dynamic generation. Template filling is more suitable for contracts with a high degree of standardization, while dynamic generation is more flexible and can adapt to different transaction scenarios.

[0171] Digital signatures can use asymmetric encryption algorithms such as RSA or elliptic curve algorithms. Encrypted storage can use symmetric encryption algorithms such as AES to ensure the confidentiality of the contract content.

[0172] The value unit identification code and the time-series weight coefficient are the core elements of the contract, and their accurate acquisition directly affects the validity of the contract. The design of the contract template database determines the efficiency and flexibility of electronic contract generation. Digital signatures and encrypted storage provide security for the entire process.

[0173] The technical solution of this application solves the problem of establishing a standardized transaction contract template to realize value flow transactions as follows: First, by obtaining the value unit identification code and timing weight coefficient, each transaction contract is provided with a unique identification and timing characteristics. This step ensures the accuracy and traceability of the contract.

[0174] Secondly, these core data are entered into the preset contract template database. This step realizes the standardized management of contract templates and lays the foundation for subsequent automated processing. The design of the contract template database takes into account the structured storage and fast retrieval of data, improving the overall efficiency of the system.

[0175] Then, an electronic contract containing all necessary information is generated based on the contract template database. This step realizes the automation of contract generation, greatly reduces human errors and improves processing efficiency. The generated electronic contract contains key information such as value unit identification code, timing weight coefficient, transaction quantity, transaction price and transaction validity period, ensuring the integrity and accuracy of the contract.

[0176] Finally, the electronic contract is digitally signed and encrypted for storage. The digital signature ensures the immutability and legal validity of the contract, while the encrypted storage protects the confidentiality of the contract content. This step greatly improves the security and credibility of the transaction.

[0177] Through this series of steps, the technical solution of this application successfully solves the problem of establishing a standardized transaction contract template, and provides reliable, efficient and secure technical support for value flow transactions. Compared with traditional methods, the solution of this application has the advantages of high automation, low error rate and strong security, which effectively improves transaction efficiency and reliability.

[0178] As a preferred implementation: In a local securities trading system, the value unit identification code uses a 16-digit alphanumeric combination, such as "ABCD1234EFGH5678". The time series weight coefficient uses a floating point number between 0 and 1, accurate to four decimal places, such as "0.7523".

[0179] The contract template database uses the PostgreSQL relational database and designs a table named "contract_templates", which includes the following fields: id (primary key), unit_code (value unit identification code), time_weight (timing weight coefficient), template_version (template version number), created_at (creation time), and updated_at (updated time).

[0180] Electronic contract generation uses the Freemarker template engine written in Java. The template file contains a fixed contract framework and uses placeholders to mark the fields that need to be filled. For example: Contract Number: ${contractNumber} Value unit identification code: ${unitCode} Time weight coefficient: ${timeWeight} Transaction quantity: ${quantity} Transaction price: ${price} Transaction validity period: ${validityPeriod} The system automatically fills in these placeholders when generating the electronic contract.

[0181] The digital signature uses the RSA algorithm with a key length of 2048 bits. The signing process is as follows: 1. Calculate the SHA-256 hash value of the contract content; 2. Use the private key to encrypt the hash value and generate a digital signature; 3. Attach the digital signature to the end of the contract.

[0182] The encrypted storage uses the AES-256 algorithm, and the key is randomly generated by the system and securely stored using the key management system. The encrypted contract is stored in a dedicated encrypted file system.

[0183] Compared with the prior art, the technical solution of this application has the following advantages: High degree of automation: Traditional methods often rely on manual operations, which are error-prone and inefficient. This application greatly improves efficiency and accuracy through automated contract generation and management.

[0184] High degree of standardization: The existing technology usually lacks a unified contract template, resulting in inconsistent contract formats and difficult management. This application achieves a high degree of standardization through a preset contract template database, which is easy to manage and process.

[0185] Strong security: Traditional methods often have deficiencies in contract security. This application significantly improves the security and legal effectiveness of contracts through digital signatures and encrypted storage.

[0186] High flexibility: Existing technologies are usually difficult to adapt to different transaction scenarios. The solution of this application can flexibly respond to various transaction needs through parameterized design.

[0187] Strong traceability: Traditional methods often make it difficult to track the change history of a contract. This application provides strong traceability through a unique value unit identification code and a time-series weight coefficient.

[0188] These advantages make the technical solution of this application show obvious progress and innovation in solving the problem of establishing a standardized transaction contract template to realize value flow transactions.

[0189] In some of the above-mentioned embodiments, during the implementation of the present application, there is still the problem that the value flow model lacks a nonlinear feedback mechanism when calculating the current value of a plot of land.

[0190] In this regard, the present application further proposes a value flow model including: V(t,s) = ∑[αi × Pi(t) × Wi(s)], where V(t,s) represents the value of segment s at time t, αi represents the weight of the i-th influencing factor, Pi(t) represents the time-related progress function, and Wi(s) represents the space-related position function; the value flow model also includes a nonlinear feedback mechanism: V'(t,s) = V(t,s) + β × ∆V(t-1,s) × F(N), where V'(t,s) represents the value after adding nonlinear feedback, β represents the value adjustment coefficient, ∆V represents the value change rate, F(N) represents the neighboring effect function, t-1 represents the previous moment, and N represents the number of neighboring value units.

[0191] This application solves the problem of the lack of nonlinear feedback mechanism in the value flow model when calculating the current value of the plot by introducing a nonlinear feedback mechanism. The basic value flow model V(t,s) = ∑[αi × Pi(t) × Wi(s)] provides a value calculation framework that takes into account time and space factors. However, this model is linear and may not fully reflect complex real-world situations. To solve this problem, the solution introduces a nonlinear feedback mechanism V'(t,s) = V(t,s) +β × ∆V(t-1,s) × F(N).

[0192] This nonlinear feedback mechanism takes into account the acceleration effect of value changes (via ∆V(t-1,s)) and spatial interactions (via F(N)). The value adjustment coefficient β allows to adjust the intensity of nonlinear effects. This mechanism can capture complex phenomena such as rapid growth or decline in value and the mutual influence of neighboring plots, making the value calculation results more accurate and in line with reality.

[0193] By combining the basic value flow model and the nonlinear feedback mechanism, the solution can more accurately calculate and predict the current value of the land parcel, providing a more reliable basis for land transactions. This improvement is particularly important for dealing with complex changes in land parcel value. For example, during the construction of a river channel, the value of some land parcels may rise rapidly due to improvements in the surrounding environment, and this rapid change and surrounding impact is exactly what the nonlinear feedback mechanism can capture.

[0194] In this application, the value flow model V(t,s) = ∑[αi × Pi(t) × Wi(s)] is the basis for calculating the current value of the plot. Among them, αi represents the weights of different influencing factors, which can be adjusted according to actual conditions. For example, factors such as the progress of river construction, the location of green space nodes, and surrounding infrastructure can be used as influencing factors and assigned different weights according to their importance. Pi(t) is a time-related progress function that can reflect the impact of the progress of river construction on the value of the plot. This function can be linear or nonlinear, depending on the actual relationship between construction progress and value growth. Wi(s) is a space-related position function that is used to represent the impact of the spatial location of the plot on its value. For example, a plot close to a river or green space node may have a higher position function value.

[0195] The nonlinear feedback mechanism V'(t,s) = V(t,s) + β × ∆V(t-1,s) × F(N) further enhances the accuracy of the model. β is the value adjustment coefficient, which is used to control the strength of nonlinear feedback. ∆V(t-1,s) represents the value change rate at the previous moment, which can capture the acceleration effect of value change. F(N) is the neighboring effect function, where N represents the number of neighboring value units. This function can simulate the extent to which the value of a plot is affected by the surrounding plots. For example, F(N) can be designed as a function that increases with N, but the growth rate gradually slows down to reflect the marginal decreasing characteristics of the neighboring effect.

[0196] The combination of these two models enables this application to simulate complex plot value changes more accurately. The base model provides a framework for considering the impact of multiple factors, while the nonlinear feedback mechanism increases sensitivity to dynamic changes and spatial interactions. This combination not only reflects the direct impact of river channel construction progress on plot value, but also captures the rapid increase in value due to surrounding environmental improvements, as well as the mutual influence between neighboring plots.

[0197] Specifically, in practical applications, this model can be implemented through the following steps: 1. First, determine the influencing factors αi. This may include river construction progress, green space node location, traffic convenience, etc. Determine the weight of each factor through expert evaluation or historical data analysis.

[0198] 2. Design a time-dependent progress function Pi(t). For example, the progress of river channel construction can be mapped to a range of 0 to 1, where 0 means not started and 1 means fully completed. This function can be linear or S-shaped, depending on the relationship between the actual construction progress and value growth.

[0199] 3. Construct a spatially relevant position function Wi(s). This can be calculated based on the distance from the plot to the river and green space nodes. For example, a decay function can be used, where the closer the distance, the higher the function value.

[0200] 4. Calculate the base value V(t,s).

[0201] 5. Design a proximity effect function F(N). This can be a function that increases as N increases, but the growth rate gradually slows down. For example, F(N) = log(N + 1).

[0202] 6. Determine the value adjustment coefficient β. This requires historical data analysis or expert judgment to determine an appropriate value to balance the impact of basic value and nonlinear feedback.

[0203] 7. Calculate the rate of change of value ∆V(t-1,s), which is the difference between the value at the previous moment and the value at the moment before that.

[0204] 8. Finally, calculate the value V'(t,s) after adding nonlinear feedback.

[0205] In this way, the application can more accurately reflect the dynamic changes in the value of the land, especially in the complex river construction environment. This method not only takes into account the time and space factors, but also captures the acceleration effect of value changes and the mutual influence in space, thus providing a more reliable value assessment basis for land transactions.

[0206] As a preferred implementation, the following specific parameters and function forms may be considered: 1. Impact factor weight αi: River construction progress: α1 = 0.4 Green space node position: α2 = 0.3 Transportation convenience: α3 = 0.2 Surrounding supporting facilities: α4 = 0.1 2. Time-related progress function Pi(t): Pi(t) = 1 / (1 + e^(-k(t-t0))) where k is the growth rate parameter and t0 is the turning point time. This is an S-shaped function that can simulate the value growth process of slow growth in the early stage of construction, rapid growth in the middle stage, and stable growth in the later stage.

[0207] 3. Spatially related position function Wi(s): Wi(s) = 1 / (1 + (d / d0)^2) where d is the distance from the plot to the nearest river or green space node, and d0 is the reference distance. This function decreases as the distance increases.

[0208] 4. Proximity effect function F(N): F(N) = log(N + 1) / log(Nmax + 1) where Nmax is the preset maximum number of neighboring units. This function increases as N increases, but the growth rate gradually slows down.

[0209] 5. Value adjustment coefficient β: It can be set to 0.2, indicating that the impact of nonlinear feedback on the total value is 20%.

[0210] 6. Value change rate ∆V(t-1,s): ∆V(t-1,s) = (V(t-1,s) - V(t-2,s)) / V(t-2,s) Using these specific parameters and function forms, we can better simulate the dynamic changes in the value of the plot during the river construction process. For example, when the river construction enters a rapid development stage, Pi(t) will increase rapidly, causing the base value V(t,s) to rise. At the same time, if the value of the surrounding plots is also rising, the values ​​of ∆V(t-1,s) and F(N) will increase, further pushing up V'(t,s) through a nonlinear feedback mechanism. This approach can accurately capture the phenomenon of rapid increases in plot value caused by river construction and improvements in the surrounding environment.

[0211] Compared with the existing technology, the value flow model of this application has the following advantages: Dynamicity: By introducing the time-dependent progress function Pi(t), this model can reflect the impact of the river construction progress on the value of the land in real time, rather than relying on static value assessment.

[0212] Spatial correlation: Through the spatially correlated position function Wi(s), this model takes into account the impact of the spatial location of the plot on its value, which is particularly important in scenarios such as river construction that are highly dependent on spatial location.

[0213] Nonlinear feedback: By introducing a nonlinear feedback mechanism, this model can capture the acceleration effect of value changes and spatial interactions, which is impossible with traditional linear models.

[0214] Flexibility: By adjusting parameters such as the influencing factor weight αi and the value adjustment coefficient β, this model can adapt to different river construction scenarios and plot characteristics.

[0215] Comprehensiveness: This model not only considers the direct impact of river construction, but also considers the indirect impact of the surrounding environment through the neighboring effect function F(N), thus providing a more comprehensive value assessment.

[0216] These advantages enable the value flow model of this application to more accurately reflect the complex changes in the value of the land during the river channel construction process, providing a more reliable basis for land transactions, thereby effectively solving the problem that the value assessment in the existing technology is not dynamic and comprehensive enough.

[0217] Second, refer to Figure 2 The present application also proposes a land bond trading device, which includes: The first acquisition module 210 is used to acquire land parcel information and river construction zone information; A division module 220, for dividing the land parcel in the land parcel information into a plurality of value units according to the river channel construction zoning information; The second acquisition module 230 is used to acquire the timing information of the river construction; The first processing module 240 is used to assign a time sequence weight coefficient to each value unit according to the time sequence information of the river construction; The second processing module 250 is used to generate a value flow voucher according to the value unit and the time sequence weight coefficient, and the value flow voucher includes time sequence information and space information; The third acquisition module 260 is used to acquire project progress information and green space node location information; The fourth processing module 270 is used to calculate the current value of each value unit using a value flow model according to the project progress information and the green space node location information; The fifth processing module 280 is used to establish the value flow voucher transaction rules according to the current value and execute the transaction matching of the value flow voucher.

[0218] By dividing the land into value units and assigning time weight coefficients, value flow coupons containing time and space information are generated, the value is dynamically calculated using the value flow model, and transaction rules are established to execute matchmaking. This solves the problems that traditional methods are unable to adapt to dynamic spatial segmentation, deal with the impact of construction timing, consider future uncertainties, and dynamically adjust strategies. It has the advantages of being able to adapt to the dynamic spatial segmentation needs of land plots, effectively deal with the impact of project construction timing on land value, consider future value uncertainties, dynamically adjust transaction strategies during the project, and achieve optimal configuration of overall interests.

[0219] In addition, in some embodiments, a local security transaction device proposed in the present application can also perform any one of the steps in the above method.

[0220] The above description is only an embodiment of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A land bond trading method, characterized in that: The steps of the method include: Obtain land parcel information and river construction zoning information; Dividing the land parcels in the land parcel information into a plurality of value units according to the river channel construction zoning information; Obtain timing information of river construction; Assigning a time sequence weight coefficient to each value unit according to the time sequence information of the river channel construction; Generate a value flow voucher according to the value unit and the time sequence weight coefficient, wherein the value flow voucher includes the time sequence information and the space information; Obtain project progress information and green space node location information; According to the project progress information and the green space node location information, a value flow model is used to calculate the current value of each value unit; The value flow voucher trading rules are established according to the current value, and the transaction matching of the value flow voucher is performed.

2. A land bond trading method according to claim 1, characterized in that: The step of assigning a time sequence weight coefficient to each value unit according to the time sequence information of the river channel construction comprises: Obtaining location information of each of the value units; Determine the construction sequence of each value unit according to the timing information of the river channel construction; Establishing a time sequence weight coefficient calculation model, wherein the time sequence weight coefficient calculation model includes a construction sequence parameter and a location parameter; Inputting the construction sequence and the location information into the timing weight coefficient calculation model; A corresponding time sequence weight coefficient is assigned to each value unit according to the calculation result of the time sequence weight coefficient calculation model.

3. A land bond trading method according to claim 2, characterized in that: The step of establishing a time series weight coefficient calculation model comprises: Obtain historical data on river construction; Extracting the correlation coefficient of the impact of construction sequence on the value of the land plot based on the historical data; Obtain terrain condition data at various locations along the river; Calculating a location influence factor according to the terrain condition data; Establishing a mathematical model with the correlation coefficient and the position influence factor; The timing weight coefficient calculation model is generated according to the mathematical model.

4. A land bond trading method according to claim 3, characterized in that: The step of calculating the position influence factor according to the terrain condition data comprises: Obtain elevation data, slope data and soil data at various locations along the river; Establishing a terrain scoring model, wherein the terrain scoring model includes elevation parameters, slope parameters and soil quality parameters; Inputting the elevation data, slope data and soil quality data into the terrain scoring model; Obtaining a terrain score for each location according to a calculation result of the terrain scoring model; Establishing a position influence factor calculation formula, wherein the position influence factor calculation formula maps the terrain score to a position influence factor; Inputting the terrain score into the location influence factor calculation formula; The position influence factor of each position is obtained according to the calculation result of the position influence factor calculation formula.

5. A land bond trading method according to claim 1, characterized in that: The step of calculating the current value of each value unit using a value flow model according to the project progress information and the green space node location information includes: Obtain the completion rate data of the project progress and the coordinate data of the green space nodes; Establish a value calculation function that includes progress parameters and position parameters; Generate a value flow model according to the value calculation function; Inputting the engineering progress completion rate data and the green space node coordinate data into the value flow model; The current value of each value unit is obtained according to the calculation result of the value flow model.

6. A land bond trading method according to claim 1, characterized in that: The step of establishing the value flow voucher trading rules according to the current value and executing the transaction matching of the value flow voucher includes: Obtaining the current value and transaction request data of each of the value units; Establish trading rules including trading price ranges and trading volume limits; classifying and sorting the transaction request data according to the transaction rules; Execute transaction matching based on the principle of price priority and time priority; Generate transaction result data and update value flow voucher holding information.

7. A land bond trading method according to claim 1, characterized in that: The method further comprises: Based on the value unit and the timing weight coefficient, a standardized transaction contract template is established, and the transaction contract template includes a value unit identification code, a timing weight coefficient, a transaction quantity, a transaction price and a transaction validity period.

8. A land bond trading method according to claim 7, characterized in that: The steps of establishing a standardized transaction contract template include: Obtaining a value unit identification code and the timing weight coefficient; Entering the value unit identification code and the timing weight coefficient into a preset contract template database; Generate an electronic contract including a value unit identification code, a timing weight coefficient, a transaction quantity, a transaction price, and a transaction validity period based on the contract template database; The electronic contract is digitally signed and encrypted for storage.

9. A land bond trading method according to claim 1, characterized in that: The value flow model includes: V(t,s) = ∑[αi × Pi(t) × Wi(s)] Among them, V(t,s) represents the value of segment s at time t, αi represents the weight of the i-th influencing factor, Pi(t) represents the time-related progress function, and Wi(s) represents the space-related position function; The value flow model also includes a nonlinear feedback mechanism: V'(t,s) = V(t,s) + β × ΔV(t-1,s) × F(N) Among them, V'(t,s) represents the value after adding nonlinear feedback, β represents the value adjustment coefficient, ∆V represents the value change rate, F(N) represents the proximity effect function, t-1 represents the previous moment, and N represents the number of adjacent value units.

10. A land bond trading device, characterized in that: The device includes: The first acquisition module is used to acquire the land plot information and river construction zoning information; A division module, used for dividing the land parcels in the land parcel information into a plurality of value units according to the river channel construction zoning information; The second acquisition module is used to obtain the timing information of the river construction; A first processing module, configured to assign a time sequence weight coefficient to each value unit according to the time sequence information of the river channel construction; A second processing module, configured to generate a value flow voucher according to the value unit and the time sequence weight coefficient, wherein the value flow voucher includes the time sequence information and the space information; The third acquisition module is used to obtain project progress information and green space node location information A fourth processing module, configured to calculate the current value of each of the value units using a value flow model according to the project progress information and the green space node location information; The fifth processing module is used to establish the value flow voucher transaction rules according to the current value and execute the transaction matching of the value flow voucher.

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