Road cost intelligent measuring and processing method, system and medium

Abstract

The invention provides a road cost intelligent measuring and processing method and system and a medium. The method comprises the following steps: obtaining roadbed engineering cost data, pavement engineering cost data, bridge engineering cost data and tunnel engineering cost data corresponding to a plurality of to-be-determined road construction schemes, and carrying out statistics to obtain engineering direct cost data, land acquisition and removal cost data and investigation and design cost data; processing to obtain engineering indirect cost data, obtaining construction accessory cost data, processing in combination with the engineering direct cost data and the engineering indirect cost data to obtain a construction economic index, obtaining traffic function characteristic data, processing to obtain a traffic function matching degree index, and obtaining engineering technical characteristic data; the engineering construction difficulty index is obtained through processing, the construction comprehensive evaluation index is obtained through processing by combining the construction economy index and the traffic function matching degree index, and the optimal road construction scheme is obtained through sorting and comparison, so that the technology of intelligent measurement and processing of the road construction cost is achieved.

Description

Technical Field

[0001] The present application relates to the technical field of highway cost, and in particular to a method, system and medium for intelligently measuring and processing highway cost. Background Art

[0002] Highway construction projects require huge investments. Different construction plans have significant differences in route planning, material selection, and construction technology, which directly affect the construction cost and later benefits. Traditional cost assessments are mostly static estimates, which make it difficult to reflect the impact of construction emergencies, material price fluctuations, and construction difficulty on costs in real time, which can easily cause the selected plan to be out of touch with reality, resulting in frequent budget overruns and construction delays.

[0003] In view of the above problems, effective technical solutions are urgently needed. Summary of the invention

[0004] The purpose of the present application is to provide a method, system and medium for intelligent measurement and processing of highway cost. The method can obtain the construction ancillary cost data corresponding to multiple pending highway construction plans, and process them in combination with the direct cost data of the project and the indirect cost data of the project to obtain the construction economic index, obtain the traffic function characteristic data, process them to obtain the traffic function matching index, obtain the engineering technology characteristic data, process them to obtain the engineering construction difficulty index, combine the construction economic index and the traffic function matching index to obtain the construction comprehensive evaluation index, and sort and compare to obtain the optimal highway construction plan, so as to realize the technology of intelligent measurement and processing of highway cost.

[0005] The present application also provides a method for intelligently measuring and processing highway construction costs, comprising the following steps: Acquire roadbed engineering characteristic data and pavement engineering characteristic data corresponding to a plurality of pending highway construction plans, and process them to obtain corresponding roadbed engineering cost data and pavement engineering cost data respectively; Acquire bridge engineering characteristic data and tunnel engineering characteristic data corresponding to the plurality of pending highway construction plans, and process them to obtain corresponding bridge engineering cost data and tunnel engineering cost data respectively; Perform statistical processing based on the roadbed engineering cost data and the pavement engineering cost data in combination with the bridge engineering cost data and the tunnel engineering cost data to obtain corresponding engineering direct cost data; Acquire the land acquisition and demolition characteristic data and the survey and design characteristic data corresponding to the plurality of pending highway construction plans, and process and obtain the corresponding engineering indirect cost data; Acquire the construction subsidiary cost data corresponding to the plurality of pending highway construction plans, and process them in combination with the engineering direct cost data and the engineering indirect cost data to obtain the corresponding construction economic efficiency index; Acquire the traffic function characteristic data corresponding to the plurality of pending highway construction plans, and process and obtain the corresponding traffic function matching index; Acquire engineering technical characteristic data corresponding to the plurality of pending highway construction plans, and process and obtain an engineering construction difficulty index; The construction economy index, traffic function matching index and engineering construction difficulty index are processed to obtain the construction comprehensive evaluation index corresponding to the multiple pending highway construction plans, and they are sorted and compared to obtain the optimal highway construction plan.

[0006] Optionally, in the method for intelligently determining and processing highway construction costs described in the present application, the step of obtaining the roadbed engineering characteristic data and the pavement engineering characteristic data corresponding to the plurality of pending highway construction plans, and respectively processing and obtaining the corresponding roadbed engineering cost data and pavement engineering cost data, comprises: Obtaining roadbed engineering characteristic data and pavement engineering characteristic data corresponding to multiple pending highway construction plans; The roadbed engineering characteristic data includes fill volume data, unit fill comprehensive cost data, excavation volume data and unit excavation comprehensive cost data; Perform statistical processing on the filling volume data, the unit filling comprehensive cost data, the excavation volume data and the unit excavation comprehensive cost data to obtain the roadbed engineering cost data; The pavement engineering characteristic data includes route length data, pavement width data, pavement thickness data and unit construction cost data; Statistical processing is performed based on the route length data, road surface width data, road surface thickness data and unit construction cost data to obtain road surface engineering cost data.

[0007] Optionally, in the method for intelligently determining and processing highway construction costs described in the present application, the step of obtaining bridge engineering characteristic data and tunnel engineering characteristic data corresponding to the plurality of pending highway construction plans, and respectively processing to obtain corresponding bridge engineering cost data and tunnel engineering cost data, comprises: Acquire bridge engineering characteristic data and tunnel engineering characteristic data corresponding to the plurality of pending highway construction plans; The bridge engineering characteristic data includes bridge type data, bridge geological condition data, bridge span data and bridge length data; Processing the bridge type data, bridge geological condition data, bridge span data, and bridge length data through a preset bridge cost assessment model to obtain bridge engineering cost data; The tunnel engineering characteristic data includes bridge and tunnel geological condition data, support method data, tunnel width data and tunnel length data; The tunnel geological condition data, support method data, tunnel width data and tunnel length data are processed through a preset tunnel cost assessment model to obtain tunnel engineering cost data.

[0008] Optionally, in the method for intelligently determining and processing highway construction costs described in the present application, the step of obtaining the land acquisition and demolition characteristic data and the survey and design characteristic data corresponding to the plurality of pending highway construction plans, and processing to obtain the corresponding engineering indirect cost data, includes: Acquire land acquisition and demolition feature data and survey and design feature data corresponding to the plurality of pending highway construction plans; The land acquisition and demolition characteristic data include occupied land area data, land type data, house demolition area data, house type data and geographical location data; The land acquisition and demolition cost data are obtained by processing the occupied land area data, land type data, house demolition area data, house type data and geographical location data through a pre-land acquisition and demolition compensation assessment model; The survey and design characteristic data include project scale data, project complexity data and design workload data; Processing the engineering scale data, engineering complexity data and design workload data through a preset survey and design cost assessment model to obtain survey and design cost data; Statistical processing is performed on the land acquisition and demolition cost data and the survey and design cost data to obtain engineering indirect cost data.

[0009] Optionally, in the method for intelligently determining and processing highway construction costs described in the present application, the acquisition of construction subsidiary cost data corresponding to the plurality of pending highway construction plans, and processing in combination with the engineering direct cost data and the engineering indirect cost data to obtain a corresponding construction economic index includes: Acquire construction ancillary cost data corresponding to the plurality of pending highway construction plans, including loan amount data, construction period data, and natural disaster impact data; The loan amount data, construction period data and natural disaster impact data are processed by a preset highway cost assessment model to obtain construction ancillary cost data; According to the construction ancillary cost data, combined with the engineering direct cost data and the engineering indirect cost data, statistical processing is performed to obtain the total cost data corresponding to the multiple pending highway construction plans; Processing the total cost data of the scheme and the route length data to obtain unit cost data; The total cost data and the unit cost data of the scheme are processed to obtain the construction economic indexes corresponding to the multiple pending highway construction schemes.

[0010] Optionally, in the method for intelligently measuring and processing highway construction costs described in the present application, the processing is performed according to the construction economy index, the traffic function matching index, and the engineering construction difficulty index to obtain the construction comprehensive evaluation indexes corresponding to the multiple pending highway construction plans, and the ranking and comparison are performed to obtain the optimal highway construction plan, including: Processing is performed according to the construction economy index, the traffic function matching index and the engineering construction difficulty index to obtain the construction comprehensive evaluation index corresponding to the plurality of pending highway construction plans; Comparing the comprehensive construction evaluation indexes to obtain the maximum value data; The pending highway construction plan corresponding to the maximum value data is the optimal highway construction plan.

[0011] In a second aspect, the present application provides a highway cost intelligent measurement and processing system, the system comprising: a memory and a processor, the memory comprising a program of a highway cost intelligent measurement and processing method, the program of the highway cost intelligent measurement and processing method being executed by the processor to implement the following steps: Acquire roadbed engineering characteristic data and pavement engineering characteristic data corresponding to a plurality of pending highway construction plans, and process them to obtain corresponding roadbed engineering cost data and pavement engineering cost data respectively; Acquire bridge engineering characteristic data and tunnel engineering characteristic data corresponding to the plurality of pending highway construction plans, and process them to obtain corresponding bridge engineering cost data and tunnel engineering cost data respectively; Perform statistical processing based on the roadbed engineering cost data and the pavement engineering cost data in combination with the bridge engineering cost data and the tunnel engineering cost data to obtain corresponding engineering direct cost data; Acquire the land acquisition and demolition characteristic data and the survey and design characteristic data corresponding to the plurality of pending highway construction plans, and process and obtain the corresponding engineering indirect cost data; Acquire the construction subsidiary cost data corresponding to the plurality of pending highway construction plans, and process them in combination with the engineering direct cost data and the engineering indirect cost data to obtain the corresponding construction economic efficiency index; Acquire the traffic function characteristic data corresponding to the plurality of pending highway construction plans, and process and obtain the corresponding traffic function matching index; Acquire engineering technical characteristic data corresponding to the plurality of pending highway construction plans, and process and obtain an engineering construction difficulty index; The construction economy index, traffic function matching index and engineering construction difficulty index are processed to obtain the construction comprehensive evaluation index corresponding to the multiple pending highway construction plans, and they are sorted and compared to obtain the optimal highway construction plan.

[0012] Optionally, in the highway cost intelligent determination and processing system described in the present application, the step of obtaining the roadbed engineering characteristic data and the pavement engineering characteristic data corresponding to the plurality of pending highway construction plans, and respectively processing to obtain the corresponding roadbed engineering cost data and the pavement engineering cost data, comprises: Obtaining roadbed engineering characteristic data and pavement engineering characteristic data corresponding to multiple pending highway construction plans; The roadbed engineering characteristic data includes fill volume data, unit fill comprehensive cost data, excavation volume data and unit excavation comprehensive cost data; Perform statistical processing on the filling volume data, the unit filling comprehensive cost data, the excavation volume data and the unit excavation comprehensive cost data to obtain the roadbed engineering cost data; The pavement engineering characteristic data includes route length data, pavement width data, pavement thickness data and unit construction cost data; Statistical processing is performed based on the route length data, road surface width data, road surface thickness data and unit construction cost data to obtain road surface engineering cost data.

[0013] Optionally, in the highway cost intelligent determination and processing system described in the present application, the step of obtaining the bridge engineering characteristic data and the tunnel engineering characteristic data corresponding to the plurality of pending highway construction schemes, and respectively processing to obtain the corresponding bridge engineering cost data and the tunnel engineering cost data, comprises: Acquire bridge engineering characteristic data and tunnel engineering characteristic data corresponding to the plurality of pending highway construction plans; The bridge engineering characteristic data includes bridge type data, bridge geological condition data, bridge span data and bridge length data; Processing the bridge type data, bridge geological condition data, bridge span data, and bridge length data through a preset bridge cost assessment model to obtain bridge engineering cost data; The tunnel engineering characteristic data includes bridge and tunnel geological condition data, support method data, tunnel width data and tunnel length data; The tunnel geological condition data, support method data, tunnel width data and tunnel length data are processed through a preset tunnel cost assessment model to obtain tunnel engineering cost data.

[0014] In a third aspect, the present application also provides a computer-readable storage medium, which stores a program for a method for intelligently determining and processing highway costs. When the program for intelligently determining and processing highway costs is executed by a processor, the steps of the method for intelligently determining and processing highway costs as described in any one of the above items are implemented.

[0015] As can be seen from the above, the intelligent highway cost determination and processing method, system and medium disclosed in the present invention obtains the roadbed engineering characteristic data and pavement engineering characteristic data corresponding to multiple pending highway construction plans, respectively processes and obtains the corresponding roadbed engineering cost data and pavement engineering cost data, obtains the bridge engineering characteristic data and tunnel engineering characteristic data corresponding to multiple pending highway construction plans, respectively processes and obtains the corresponding bridge engineering cost data and tunnel engineering cost data, performs statistical processing based on the roadbed engineering cost data and pavement engineering cost data, combines the bridge engineering cost data and the tunnel engineering cost data, obtains the corresponding engineering direct cost data, obtains the land acquisition and demolition characteristic data and the survey and design characteristic data corresponding to multiple pending highway construction plans, The corresponding engineering indirect cost data is obtained by processing, the construction ancillary cost data corresponding to multiple pending highway construction plans are obtained, and the engineering direct cost data and the engineering indirect cost data are combined for processing to obtain the corresponding construction economic index, the traffic function characteristic data corresponding to multiple pending highway construction plans are obtained by processing to obtain the corresponding traffic function matching index, the engineering technical characteristic data corresponding to multiple pending highway construction plans are obtained by processing to obtain the engineering construction difficulty index, and the construction comprehensive evaluation index corresponding to multiple pending highway construction plans is obtained according to the construction economic index, the traffic function matching index and the engineering construction difficulty index, and the optimal highway construction plan is obtained by sorting and comparing. The technology of intelligent measurement and processing of highway cost is realized.

[0016] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or understood by practicing the embodiments of the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 A flowchart of a method for intelligently measuring and processing highway construction costs provided in an embodiment of the present application; Figure 2 A flowchart of obtaining roadbed engineering cost data and pavement engineering cost data of the method for intelligently measuring and processing highway construction costs provided in an embodiment of the present application; Figure 3A flowchart of obtaining bridge engineering cost data and tunnel engineering cost data in the method for intelligently measuring and processing highway construction costs provided in an embodiment of the present application; Figure 4 A flowchart of obtaining engineering indirect cost data for the method for intelligently measuring and processing highway construction costs provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application 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 application claimed 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.

[0020] 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.

[0021] Please refer to Figure 1 , Figure 1 The figure is a flow chart of a method for intelligently measuring and processing highway costs in some embodiments of the present application. The method for intelligently measuring and processing highway costs is used in a terminal device, such as a computer, a mobile phone terminal, etc. The method for intelligently measuring and processing highway costs comprises the following steps: S11, obtaining roadbed engineering characteristic data and pavement engineering characteristic data corresponding to a plurality of pending highway construction plans, and processing them to obtain corresponding roadbed engineering cost data and pavement engineering cost data respectively; S12, obtaining bridge engineering characteristic data and tunnel engineering characteristic data corresponding to the plurality of pending highway construction plans, and respectively processing to obtain corresponding bridge engineering cost data and tunnel engineering cost data; S13, performing statistical processing based on the roadbed engineering cost data and the pavement engineering cost data, combined with the bridge engineering cost data and the tunnel engineering cost data, to obtain corresponding engineering direct cost data; S14, obtaining the land acquisition and demolition characteristic data and the survey and design characteristic data corresponding to the plurality of pending highway construction plans, and processing and obtaining the corresponding engineering indirect cost data; S15, obtaining construction subsidiary cost data corresponding to the plurality of pending highway construction plans, and processing them in combination with the engineering direct cost data and the engineering indirect cost data to obtain a corresponding construction economic efficiency index; S16, obtaining the traffic function characteristic data corresponding to the plurality of pending highway construction plans, and processing to obtain the corresponding traffic function matching index; S17, obtaining engineering technical characteristic data corresponding to the plurality of pending highway construction plans, and processing to obtain an engineering construction difficulty index; S18. Processing is performed according to the construction economy index, traffic function matching index and engineering construction difficulty index to obtain the construction comprehensive evaluation index corresponding to the multiple pending highway construction plans, and the plans are sorted and compared to obtain the optimal highway construction plan.

[0022] It should be noted that highway construction projects require huge investments, and different construction plans have significant differences in route planning, material selection, and construction technology, which directly affect the construction cost and later benefits. Traditional cost assessments are mostly static estimates, which are difficult to reflect the impact of construction emergencies, material price fluctuations, and construction difficulty on costs, and can easily cause the selected plan to be out of touch with reality, resulting in frequent budget overruns and construction delays. In order to select the optimal highway construction plan, in this embodiment, first, by obtaining the roadbed engineering feature data and pavement engineering feature data corresponding to a plurality of pending highway construction plans, respectively processing to obtain the corresponding roadbed engineering cost data and pavement engineering cost data, obtaining the bridge engineering feature data and tunnel engineering feature data corresponding to a plurality of pending highway construction plans, respectively processing to obtain the corresponding bridge engineering cost data and tunnel engineering cost data, and then performing the cost analysis based on the roadbed engineering cost data and pavement engineering cost data in combination with the bridge engineering cost data and tunnel engineering cost data. Statistical processing is performed to obtain the corresponding direct engineering cost data, obtain the land acquisition and demolition characteristic data and the survey and design characteristic data corresponding to multiple pending highway construction plans, process and obtain the corresponding indirect engineering cost data, obtain the construction ancillary cost data corresponding to multiple pending highway construction plans, and process them in combination with the direct engineering cost data and the indirect engineering cost data to obtain the corresponding construction economic index, obtain the traffic function characteristic data corresponding to multiple pending highway construction plans, process and obtain the corresponding traffic function matching index, obtain the engineering technical characteristic data corresponding to multiple pending highway construction plans, process and obtain the engineering construction difficulty index, and process according to the construction economic index, the traffic function matching index and the engineering construction difficulty index to obtain the construction comprehensive evaluation index corresponding to multiple pending highway construction plans, and rank and compare them to obtain the optimal highway construction plan, and make corresponding adjustments, thereby realizing the technology of intelligent measurement and processing of highway cost.

[0023] Please refer to Figure 2 , Figure 2The present invention is a flowchart of obtaining roadbed engineering cost data and pavement engineering cost data of a method for intelligently determining and processing highway construction costs in some embodiments of the present application. According to an embodiment of the present invention, the roadbed engineering feature data and pavement engineering feature data corresponding to a plurality of pending highway construction plans are obtained, and the corresponding roadbed engineering cost data and pavement engineering cost data are obtained by processing them respectively, including: S21, obtaining roadbed engineering characteristic data and pavement engineering characteristic data corresponding to a plurality of pending highway construction plans; S22, the roadbed engineering characteristic data includes fill volume data, unit fill comprehensive cost data, excavation volume data and unit excavation comprehensive cost data; S23, performing statistical processing on the filling volume data, the unit filling comprehensive cost data, the excavation volume data and the unit excavation comprehensive cost data to obtain roadbed engineering cost data; S24, the pavement engineering characteristic data includes route length data, pavement width data, pavement thickness data and unit construction cost data; S25. Perform statistical processing based on the route length data, road width data, road thickness data and unit construction cost data to obtain road construction cost data.

[0024] It should be noted that the roadbed engineering cost and pavement engineering cost are direct costs of highway construction. Among them, the roadbed engineering cost can be obtained by adding the filling cost and the excavation cost, and the pavement engineering cost can be calculated by route length, pavement width, pavement thickness and unit construction cost.

[0025] Please refer to Figure 3 , Figure 3 The present invention is a flowchart of obtaining bridge engineering cost data and tunnel engineering cost data of a method for intelligently determining and processing highway construction costs in some embodiments of the present application. According to an embodiment of the present invention, the obtaining of bridge engineering feature data and tunnel engineering feature data corresponding to the plurality of pending highway construction plans, and the processing to obtain the corresponding bridge engineering cost data and tunnel engineering cost data respectively, include: S31, obtaining bridge engineering characteristic data and tunnel engineering characteristic data corresponding to the plurality of pending highway construction plans; S32, the bridge engineering characteristic data includes bridge type data, bridge geological condition data, bridge span data and bridge length data; S33, processing the bridge type data, bridge geological condition data, bridge span data, and bridge length data through a preset bridge cost evaluation model to obtain bridge engineering cost data; S34, the tunnel engineering characteristic data includes bridge and tunnel geological condition data, support method data, tunnel width data and tunnel length data; S35. Processing the tunnel geological condition data, support method data, tunnel width data and tunnel length data through a preset tunnel cost assessment model to obtain tunnel engineering cost data.

[0026] It should be noted that the cost assessment of bridges and tunnels is crucial to the entire highway cost, so it is necessary to conduct a separate assessment of the engineering costs of bridges and tunnels. The bridge cost can be obtained by inputting the bridge type, bridge geological conditions, bridge span and bridge length into the preset bridge cost assessment model. Among them, different types of bridges (such as beam bridges, arch bridges, cable-stayed bridges, suspension bridges, etc.) have very different structural characteristics and cost structures. For example, the structure of a beam bridge is relatively simple, and the main costs are concentrated in the prefabrication or cast-in-place of the beam body, pier foundations, etc., while the cost of a suspension bridge is higher due to the complex structure of the main cable, cable tower, etc., and it is necessary to clarify the cost of the bridge. The specific type and its key parameters are recorded. A detailed geological survey report is the basis. The geological conditions include soil type (such as clay, sand, rock, etc.), groundwater level depth, foundation bearing capacity, etc. For example, building a bridge on a soft soil foundation may require foundation treatment, such as pile foundation reinforcement, which will increase the cost of the foundation part. According to the geological conditions, determine the appropriate foundation form (such as expanded foundation, pile foundation, caisson foundation, etc.), and record the design parameters of the foundation, such as pile length, pile diameter, number of piles, etc. These data are the key to calculating the foundation cost. Accurately measure the span of the bridge (single span or multiple spans) and the total length. The span determines the upper The stress form and component size of the internal structure. For example, a long-span bridge may need to use prestressed structure or higher-grade steel to meet the stress requirements, thereby increasing the cost. The length affects the overall project volume, including factors such as material consumption and construction period. The bridge cost evaluation model is a cost prediction model based on machine learning. It is trained based on a large number of case data of built bridge projects, including information such as bridge type, geological conditions, span, length and actual cost, to obtain a well-trained, result-verified and adjusted bridge cost evaluation model. For tunnel cost, the tunnel geological conditions, support method, tunnel width and tunnel length can be used to input The preset tunnel cost assessment model is used for processing, among which a detailed geological survey report is the key. The geological conditions include rock type (such as granite, shale, limestone, etc.), rock strength, geological structure (such as faults, folds, etc.), groundwater conditions, etc. For example, under soft rock or broken zone geological conditions, tunnel construction is difficult and requires more frequent support and reinforcement measures. The geological conditions can be classified and quantified. Rocks can be divided into soft rock, medium hard rock, hard rock and other categories according to their uniaxial compressive strength. Different levels of geological structure complexity are represented by numbers or codes, such as simple geological structure is 1, and complex geological structure (with multiple faults and folds) is 3. At the same time, record the water level, water volume and water pressure of groundwater. Different support methods have different materials and construction costs. For example, anchor support needs to calculate the length, diameter, spacing and number of anchors, as well as the cost of anchor materials (such as steel bars or steel strands). Sprayed concrete support needs to consider parameters such as concrete grade, thickness and spraying area. For complex support systems, such as advanced support (advanced small guide tubes, pipe sheds, etc.),Record detailed information such as its type, length, spacing and layout range. These parameters will directly affect the cost of the support part. The width of the tunnel determines the size of the excavation section and the size of the support structure. For example, a wider tunnel requires more support materials and a larger excavation workload. The length of the tunnel is a key factor in calculating the overall workload. For example, the excavation volume and lining length are proportional to the tunnel length. The width and length data are standardized to ensure the accuracy and consistency of the data so that they can be input into the cost evaluation model. The tunnel cost evaluation model is a cost prediction model based on machine learning. It is trained based on a large number of tunnel engineering case data, including geological conditions, support methods, width, length and actual cost information, to obtain a well-trained, result-verified and adjusted tunnel cost evaluation model.

[0027] Please refer to Figure 4 , Figure 4 The method for intelligently measuring and processing highway construction costs in some embodiments of the present application is a flowchart for obtaining engineering indirect cost data. According to the embodiment of the present invention, the method of obtaining the land acquisition and demolition feature data and the survey and design feature data corresponding to the plurality of pending highway construction plans, and processing and obtaining the corresponding engineering indirect cost data includes: S41, obtaining land acquisition and demolition feature data and survey and design feature data corresponding to the plurality of pending highway construction plans; S42, the land acquisition and demolition characteristic data includes occupied land area data, land type data, house demolition area data, house type data and geographical location data; S43, processing the occupied land area data, land type data, house demolition area data, house type data and geographical location data through a pre-land acquisition and demolition compensation assessment model to obtain land acquisition and demolition cost data; S44, the survey and design characteristic data includes project scale data, project complexity data and design workload data; S45, processing the engineering scale data, engineering complexity data and design workload data through a preset survey and design cost evaluation model to obtain survey and design cost data; S46. Perform statistical processing on the land acquisition and demolition cost data and the survey and design cost data to obtain engineering indirect cost data.

[0028] It should be noted that in the process of highway construction, some indirect engineering costs will be generated, including land acquisition and demolition costs and survey and design costs. The land acquisition and demolition costs include land acquisition compensation costs and demolition costs. The data can be obtained by statistically analyzing the occupied land area, land type, house demolition area, house type, and the geographical location of the land and the house, and then inputting the preset pre-land acquisition and demolition compensation assessment model for processing to obtain the land acquisition and demolition costs. Among them, the accurate measurement of the occupied land area can be completed through professional surveying and mapping tools and methods. The land types are divided into agricultural land (such as cultivated land, forest land, grassland, etc.), construction land (such as homestead, factory land, etc.) and unused land, and the compensation standards for different land types are different. The standards vary greatly. For agricultural land, it is necessary to further clarify its land quality grade, such as the fertility grade of cultivated land, irrigation conditions, etc. These factors will affect the compensation price. The house demolition area should be accurately measured, including area data under different measurement standards such as building area and usable area. House types are divided into rural residential, urban commercial housing, factory buildings and other types. The building structure of the house (such as brick-concrete structure, frame structure, etc.) should be recorded in detail. The demolition cost will be different for different building structures. For rural residential, the area and value of ancillary facilities (such as yards, biogas tanks, etc.) should also be considered. For factory buildings, factors such as the relocation or disposal costs of production equipment should be considered. The geographical location includes the area where the land is located (such as the city center, suburbs, rural areas In general, the value of land and houses in the city center or areas with convenient transportation is higher, and the compensation standard is also correspondingly higher. The land acquisition and demolition compensation assessment model belongs to the market comparison method model. The principle is to compare the land and houses to be relocated with similar land and houses in the surrounding areas that have been sold. For land, according to its type, area, geographical location and other factors, find the transaction price of the same type of land that has been recently traded in the surrounding area, and determine the compensation price through a certain correction coefficient (such as considering the difference in land quality, the difference in transportation convenience, etc.). For houses, according to the house type, building structure, area and other conditions, find the market transaction price of similar houses in the surrounding area. For example, for the demolition of urban commercial housing, refer to the same small The transaction price of second-hand houses in the district or similar communities in the surrounding area can be corrected in combination with factors such as the decoration of the house and the floor to obtain the compensation price for house demolition. The survey and design cost is related to the scale of the highway construction project, the complexity of the project and the design workload. These key data can be input into the preset survey and design cost evaluation model for processing to obtain the survey and design cost. The survey and design cost evaluation model is an estimation model based on cost drivers. The model considers the main driving factors affecting the survey and design cost, such as the scale of the project, the complexity and the design workload. First, the cost coefficient of each driving factor is determined. These coefficients can be obtained by regression analysis of a large amount of historical project data. For example, for every increase of 1 km in highway length, the survey and design cost increases by a certain amount. For every increase in geological complexity, the cost increases by a percentage, etc.Multiply the actual value of each driving factor by the corresponding cost coefficient, then summarize the costs of all driving factors, and then consider basic management expenses, profits and taxes to obtain the survey and design cost.

[0029] According to an embodiment of the present invention, the obtaining of the construction subsidiary cost data corresponding to the plurality of pending highway construction plans, and processing in combination with the engineering direct cost data and the engineering indirect cost data to obtain the corresponding construction economic index, includes: Acquire construction ancillary cost data corresponding to the plurality of pending highway construction plans, including loan amount data, construction period data, and natural disaster impact data; The loan amount data, construction period data and natural disaster impact data are processed by a preset highway cost assessment model to obtain construction ancillary cost data; According to the construction ancillary cost data, combined with the engineering direct cost data and the engineering indirect cost data, statistical processing is performed to obtain the total cost data corresponding to the multiple pending highway construction plans; Processing the total cost data of the scheme and the route length data to obtain unit cost data; The total cost data and the unit cost data of the scheme are processed to obtain the construction economic indexes corresponding to the multiple pending highway construction schemes.

[0030] It should be noted that one of the important indicators for comparing highway construction plans is the economic indicator, which is related to the total construction cost and unit construction cost. Therefore, it is necessary to first obtain the total construction cost of each pending highway construction plan, which is composed of construction ancillary costs, direct project costs and indirect project costs. Construction ancillary costs include the interest generated by construction loans and the additional costs caused by natural disasters. Among them, the specific value of the loan amount, as well as the loan interest rate, repayment method (such as equal principal and interest, equal principal, etc.) and loan term are clearly defined. This information will be used to calculate loan interest, which is an important part of the ancillary costs of construction. The planned construction period of the highway construction, including the start date and completion date, is accurately recorded. At the same time, factors that may affect the construction period are collected, such as the impact of the construction season (rainy season, winter, etc.) on construction efficiency, as well as key nodes and milestones in the construction process. In addition, natural disasters in the highway construction area are investigated, including the types of natural disasters (such as floods, earthquakes, mudslides, etc.), frequency and intensity of occurrence. Historical data from local meteorological, geological and other departments can be referred to, and different stages of highway construction can be evaluated according to the degree of impact of natural disasters. The highway cost evaluation model belongs to the traditional cost-plus model, which first calculates the known basic Ancillary costs, such as loan interest and management fees, are then estimated based on factors such as the construction period and the impact of natural disasters. The costs that may increase are finally added together. For example, for loan interest, it is calculated based on the loan amount, interest rate and loan term. For the cost increase caused by the extension of the construction period, it is calculated by estimating the labor, material and equipment costs during the extended construction period. For natural disaster risks, based on the risk assessment results, the possible losses and repair costs are estimated, and then a certain risk reserve is added. Then, after obtaining the total cost, the unit cost can be obtained in combination with the route length of the highway in the plan. The total cost data and unit cost data of the plan are further processed to obtain the construction economy index corresponding to multiple pending highway construction plans; The calculation formula of the construction economy index is: ; in, is the construction economy index corresponding to the i-th pending highway construction plan, , are the total cost data and unit cost data corresponding to the i-th pending highway construction plan, , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset highway cost database).

[0031] According to an embodiment of the present invention, the construction economy index, the traffic function matching index and the engineering construction difficulty index are processed to obtain the construction comprehensive evaluation indexes corresponding to the multiple pending highway construction plans, and the ranking and comparison are performed to obtain the optimal highway construction plan, including: Processing is performed according to the construction economy index, the traffic function matching index and the engineering construction difficulty index to obtain the construction comprehensive evaluation index corresponding to the plurality of pending highway construction plans; Comparing the comprehensive construction evaluation indexes to obtain the maximum value data; The pending highway construction plan corresponding to the maximum value data is the optimal highway construction plan.

[0032] It should be noted that, according to the construction economy index, traffic function matching index and engineering construction difficulty index obtained by processing, the construction comprehensive evaluation index corresponding to multiple pending highway construction plans is obtained, and then the one with the largest index concentration value is screened out, and the highway construction plan corresponding to it is the optimal highway construction plan; The calculation formula of the construction comprehensive evaluation index is: ; in, is the comprehensive evaluation index of the construction corresponding to the i-th pending highway construction plan, , , are the construction economy index, traffic function matching index, and engineering construction difficulty index corresponding to the i-th pending highway construction plan, , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset highway cost database).

[0033] According to an embodiment of the present invention, it also includes: The step of obtaining the traffic function characteristic data corresponding to the plurality of pending highway construction plans and processing to obtain the corresponding traffic function matching index specifically includes: Acquiring traffic function characteristic data corresponding to the plurality of pending highway construction plans, including design traffic flow adaptability data, design traffic efficiency data, and road congestion coefficient data; Processing the designed traffic flow adaptability data, the designed traffic efficiency data, and the road congestion coefficient data to obtain the traffic function matching index corresponding to the plurality of pending highway construction plans; The calculation formula of the traffic function matching index is: ; in, is the traffic function matching index corresponding to the i-th pending highway construction plan, , , are the design traffic flow adaptability data, design traffic efficiency data, and road congestion coefficient data corresponding to the i-th pending highway construction plan, , , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset highway cost database).

[0034] It should be noted that, on the other hand, the evaluation of the schemes also needs to consider the traffic function matching of each scheme, including: 1. Adaptability to traffic flow. Even if a scheme has a low cost, it may not be the optimal scheme if it cannot meet the needs of future traffic flow growth. The design traffic flow adaptability data is obtained based on the predicted traffic flow in the next 20 years. 2. Design traffic efficiency. A higher design speed usually means better traffic efficiency. If the design speed of Scheme 1 is 100 km / h and the design speed of Scheme 2 is 80 km / h, Scheme 1 may be more suitable for long-distance transportation or traffic scenarios with high timeliness requirements. 3. Road congestion coefficient. For example, although a highway construction scheme has a low cost, it has a small number of lanes. It is expected that traffic congestion will occur in the next 5-10 years, which indicates that its road congestion coefficient is large. The road congestion coefficient can be obtained through traffic network model processing based on the number of lanes, design speed, future traffic flow and road network results.

[0035] According to an embodiment of the present invention, it also includes: The step of obtaining the engineering technical characteristic data corresponding to the plurality of pending highway construction plans and processing to obtain the engineering construction difficulty index specifically includes: Processing the bridge engineering cost data and the tunnel engineering cost data in combination with the total cost data of the scheme to obtain bridge cost proportion data and tunnel cost proportion data; According to the bridge cost proportion data and the tunnel cost proportion data, combined with the filling volume data and the excavation volume data, the engineering construction difficulty index corresponding to the multiple pending highway construction plans is obtained; The calculation formula of the engineering construction difficulty index is: ; in, is the engineering construction difficulty index corresponding to the i-th pending highway construction plan, , , , are the bridge cost proportion data, tunnel cost proportion data, filling volume data, and excavation volume data corresponding to the i-th pending highway construction plan, respectively. , , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset highway cost database).

[0036] It should be noted that the evaluation of the plans also needs to take into account the difficulty of the engineering construction of each plan. Among them, the construction of bridges and tunnels will increase the difficulty of road construction. Therefore, the data on the proportion of bridge cost, tunnel cost, filling volume and excavation volume are counted, and then the above data are processed to obtain the engineering construction difficulty index corresponding to each pending highway construction plan.

[0037] In a second aspect, the present invention further discloses a highway cost intelligent determination and processing system, including a memory and a processor, wherein the memory includes a highway cost intelligent determination and processing method program, and when the highway cost intelligent determination and processing method program is executed by the processor, the following steps are implemented: Acquire roadbed engineering characteristic data and pavement engineering characteristic data corresponding to a plurality of pending highway construction plans, and process them to obtain corresponding roadbed engineering cost data and pavement engineering cost data respectively; Acquire bridge engineering characteristic data and tunnel engineering characteristic data corresponding to the plurality of pending highway construction plans, and process them to obtain corresponding bridge engineering cost data and tunnel engineering cost data respectively; Perform statistical processing based on the roadbed engineering cost data and the pavement engineering cost data in combination with the bridge engineering cost data and the tunnel engineering cost data to obtain corresponding engineering direct cost data; Acquire the land acquisition and demolition characteristic data and the survey and design characteristic data corresponding to the plurality of pending highway construction plans, and process and obtain the corresponding engineering indirect cost data; Acquire the construction subsidiary cost data corresponding to the plurality of pending highway construction plans, and process them in combination with the engineering direct cost data and the engineering indirect cost data to obtain the corresponding construction economic efficiency index; Acquire the traffic function characteristic data corresponding to the plurality of pending highway construction plans, and process and obtain the corresponding traffic function matching index; Acquire engineering technical characteristic data corresponding to the plurality of pending highway construction plans, and process and obtain an engineering construction difficulty index; The construction economy index, traffic function matching index and engineering construction difficulty index are processed to obtain the construction comprehensive evaluation index corresponding to the multiple pending highway construction plans, and they are sorted and compared to obtain the optimal highway construction plan.

[0038] It should be noted that highway construction projects require huge investments, and different construction plans have significant differences in route planning, material selection, and construction technology, which directly affect the construction cost and later benefits. Traditional cost assessments are mostly static estimates, which are difficult to reflect the impact of construction emergencies, material price fluctuations, and construction difficulty on costs, and can easily cause the selected plan to be out of touch with reality, resulting in frequent budget overruns and construction delays. In order to select the optimal highway construction plan, in this embodiment, first, by obtaining the roadbed engineering feature data and pavement engineering feature data corresponding to a plurality of pending highway construction plans, respectively processing to obtain the corresponding roadbed engineering cost data and pavement engineering cost data, obtaining the bridge engineering feature data and tunnel engineering feature data corresponding to a plurality of pending highway construction plans, respectively processing to obtain the corresponding bridge engineering cost data and tunnel engineering cost data, and then performing the cost analysis based on the roadbed engineering cost data and pavement engineering cost data in combination with the bridge engineering cost data and tunnel engineering cost data. Statistical processing is performed to obtain the corresponding direct engineering cost data, obtain the land acquisition and demolition characteristic data and the survey and design characteristic data corresponding to multiple pending highway construction plans, process and obtain the corresponding indirect engineering cost data, obtain the construction ancillary cost data corresponding to multiple pending highway construction plans, and process them in combination with the direct engineering cost data and the indirect engineering cost data to obtain the corresponding construction economic index, obtain the traffic function characteristic data corresponding to multiple pending highway construction plans, process and obtain the corresponding traffic function matching index, obtain the engineering technical characteristic data corresponding to multiple pending highway construction plans, process and obtain the engineering construction difficulty index, and process according to the construction economic index, the traffic function matching index and the engineering construction difficulty index to obtain the construction comprehensive evaluation index corresponding to multiple pending highway construction plans, and rank and compare them to obtain the optimal highway construction plan, and make corresponding adjustments, thereby realizing the technology of intelligent measurement and processing of highway cost.

[0039] According to an embodiment of the present invention, the step of obtaining the roadbed engineering characteristic data and the pavement engineering characteristic data corresponding to the plurality of pending highway construction plans, and respectively processing and obtaining the corresponding roadbed engineering cost data and the pavement engineering cost data, comprises: Obtaining roadbed engineering characteristic data and pavement engineering characteristic data corresponding to multiple pending highway construction plans; The roadbed engineering characteristic data includes fill volume data, unit fill comprehensive cost data, excavation volume data and unit excavation comprehensive cost data; Perform statistical processing on the filling volume data, the unit filling comprehensive cost data, the excavation volume data and the unit excavation comprehensive cost data to obtain the roadbed engineering cost data; The pavement engineering characteristic data includes route length data, pavement width data, pavement thickness data and unit construction cost data; Statistical processing is performed based on the route length data, road surface width data, road surface thickness data and unit construction cost data to obtain road surface engineering cost data.

[0040] It should be noted that the roadbed engineering cost and pavement engineering cost are direct costs of highway construction. Among them, the roadbed engineering cost can be obtained by adding the filling cost and the excavation cost, and the pavement engineering cost can be calculated by route length, pavement width, pavement thickness and unit construction cost.

[0041] According to an embodiment of the present invention, the step of obtaining bridge engineering characteristic data and tunnel engineering characteristic data corresponding to the plurality of pending highway construction plans, and respectively processing to obtain corresponding bridge engineering cost data and tunnel engineering cost data, includes: Acquire bridge engineering characteristic data and tunnel engineering characteristic data corresponding to the plurality of pending highway construction plans; The bridge engineering characteristic data includes bridge type data, bridge geological condition data, bridge span data and bridge length data; Processing the bridge type data, bridge geological condition data, bridge span data, and bridge length data through a preset bridge cost assessment model to obtain bridge engineering cost data; The tunnel engineering characteristic data includes bridge and tunnel geological condition data, support method data, tunnel width data and tunnel length data; The tunnel geological condition data, support method data, tunnel width data and tunnel length data are processed through a preset tunnel cost assessment model to obtain tunnel engineering cost data.

[0042] It should be noted that the cost assessment of bridges and tunnels is crucial to the entire highway cost, so it is necessary to conduct a separate assessment of the engineering costs of bridges and tunnels. The bridge cost can be obtained by inputting the bridge type, bridge geological conditions, bridge span and bridge length into the preset bridge cost assessment model. Among them, different types of bridges (such as beam bridges, arch bridges, cable-stayed bridges, suspension bridges, etc.) have very different structural characteristics and cost structures. For example, the structure of a beam bridge is relatively simple, and the main costs are concentrated in the prefabrication or cast-in-place of the beam body, pier foundations, etc., while the cost of a suspension bridge is higher due to the complex structure of the main cable, cable tower, etc., and it is necessary to clarify the cost of the bridge. The specific type and its key parameters are recorded. A detailed geological survey report is the basis. The geological conditions include soil type (such as clay, sand, rock, etc.), groundwater level depth, foundation bearing capacity, etc. For example, building a bridge on a soft soil foundation may require foundation treatment, such as pile foundation reinforcement, which will increase the cost of the foundation part. According to the geological conditions, determine the appropriate foundation form (such as expanded foundation, pile foundation, caisson foundation, etc.), and record the design parameters of the foundation, such as pile length, pile diameter, number of piles, etc. These data are the key to calculating the foundation cost. Accurately measure the span of the bridge (single span or multiple spans) and the total length. The span determines the upper The stress form and component size of the internal structure. For example, a long-span bridge may need to use prestressed structure or higher-grade steel to meet the stress requirements, thereby increasing the cost. The length affects the overall project volume, including factors such as material consumption and construction period. The bridge cost evaluation model is a cost prediction model based on machine learning. It is trained based on a large number of case data of built bridge projects, including information such as bridge type, geological conditions, span, length and actual cost, to obtain a well-trained, result-verified and adjusted bridge cost evaluation model. For tunnel cost, the tunnel geological conditions, support method, tunnel width and tunnel length can be used to input The preset tunnel cost assessment model is used for processing, among which a detailed geological survey report is the key. The geological conditions include rock type (such as granite, shale, limestone, etc.), rock strength, geological structure (such as faults, folds, etc.), groundwater conditions, etc. For example, under soft rock or broken zone geological conditions, tunnel construction is difficult and requires more frequent support and reinforcement measures. The geological conditions can be classified and quantified. Rocks can be divided into soft rock, medium hard rock, hard rock and other categories according to their uniaxial compressive strength. Different levels of geological structure complexity are represented by numbers or codes, such as simple geological structure is 1, and complex geological structure (with multiple faults and folds) is 3. At the same time, record the water level, water volume and water pressure of groundwater. Different support methods have different materials and construction costs. For example, anchor support needs to calculate the length, diameter, spacing and number of anchors, as well as the cost of anchor materials (such as steel bars or steel strands). Sprayed concrete support needs to consider parameters such as concrete grade, thickness and spraying area. For complex support systems, such as advanced support (advanced small guide tubes, pipe sheds, etc.),Record detailed information such as its type, length, spacing and layout range. These parameters will directly affect the cost of the support part. The width of the tunnel determines the size of the excavation section and the size of the support structure. For example, a wider tunnel requires more support materials and a larger excavation workload. The length of the tunnel is a key factor in calculating the overall workload. For example, the excavation volume and lining length are proportional to the tunnel length. The width and length data are standardized to ensure the accuracy and consistency of the data so that they can be input into the cost evaluation model. The tunnel cost evaluation model is a cost prediction model based on machine learning. It is trained based on a large number of tunnel engineering case data, including geological conditions, support methods, width, length and actual cost information, to obtain a well-trained, result-verified and adjusted tunnel cost evaluation model.

[0043] According to an embodiment of the present invention, the step of obtaining the land acquisition and demolition feature data and the survey and design feature data corresponding to the plurality of pending highway construction plans and processing to obtain the corresponding engineering indirect cost data includes: Acquire land acquisition and demolition feature data and survey and design feature data corresponding to the plurality of pending highway construction plans; The land acquisition and demolition characteristic data include occupied land area data, land type data, house demolition area data, house type data and geographical location data; The land acquisition and demolition cost data are obtained by processing the occupied land area data, land type data, house demolition area data, house type data and geographical location data through a pre-land acquisition and demolition compensation assessment model; The survey and design characteristic data include project scale data, project complexity data and design workload data; Processing the engineering scale data, engineering complexity data and design workload data through a preset survey and design cost assessment model to obtain survey and design cost data; Statistical processing is performed on the land acquisition and demolition cost data and the survey and design cost data to obtain engineering indirect cost data.

[0044] It should be noted that in the process of highway construction, some indirect engineering costs will be generated, including land acquisition and demolition costs and survey and design costs. The land acquisition and demolition costs include land acquisition compensation costs and demolition costs. The data can be obtained by statistically analyzing the occupied land area, land type, house demolition area, house type, and the geographical location of the land and the house, and then inputting the preset pre-land acquisition and demolition compensation assessment model for processing to obtain the land acquisition and demolition costs. Among them, the accurate measurement of the occupied land area can be completed through professional surveying and mapping tools and methods. The land types are divided into agricultural land (such as cultivated land, forest land, grassland, etc.), construction land (such as homestead, factory land, etc.) and unused land, and the compensation standards for different land types are different. The standards vary greatly. For agricultural land, it is necessary to further clarify its land quality grade, such as the fertility grade of cultivated land, irrigation conditions, etc. These factors will affect the compensation price. The house demolition area should be accurately measured, including area data under different measurement standards such as building area and usable area. House types are divided into rural residential, urban commercial housing, factory buildings and other types. The building structure of the house (such as brick-concrete structure, frame structure, etc.) should be recorded in detail. The demolition cost will be different for different building structures. For rural residential, the area and value of ancillary facilities (such as yards, biogas tanks, etc.) should also be considered. For factory buildings, factors such as the relocation or disposal costs of production equipment should be considered. The geographical location includes the area where the land is located (such as the city center, suburbs, rural areas In general, the value of land and houses in the city center or areas with convenient transportation is higher, and the compensation standard is also correspondingly higher. The land acquisition and demolition compensation assessment model belongs to the market comparison method model. The principle is to compare the land and houses to be relocated with similar land and houses in the surrounding areas that have been sold. For land, according to its type, area, geographical location and other factors, find the transaction price of the same type of land that has been recently traded in the surrounding area, and determine the compensation price through a certain correction coefficient (such as considering the difference in land quality, the difference in transportation convenience, etc.). For houses, according to the house type, building structure, area and other conditions, find the market transaction price of similar houses in the surrounding area. For example, for the demolition of urban commercial housing, refer to the same small The transaction price of second-hand houses in the district or similar communities in the surrounding area can be corrected in combination with factors such as the decoration of the house and the floor to obtain the compensation price for house demolition. The survey and design cost is related to the scale of the highway construction project, the complexity of the project and the design workload. These key data can be input into the preset survey and design cost evaluation model for processing to obtain the survey and design cost. The survey and design cost evaluation model is an estimation model based on cost drivers. The model considers the main driving factors affecting the survey and design cost, such as the scale of the project, the complexity and the design workload. First, the cost coefficient of each driving factor is determined. These coefficients can be obtained by regression analysis of a large amount of historical project data. For example, for every increase of 1 km in highway length, the survey and design cost increases by a certain amount. For every increase in geological complexity, the cost increases by a percentage, etc.Multiply the actual value of each driving factor by the corresponding cost coefficient, then summarize the costs of all driving factors, and then consider basic management expenses, profits and taxes to obtain the survey and design cost.

[0045] According to an embodiment of the present invention, the obtaining of the construction subsidiary cost data corresponding to the plurality of pending highway construction plans, and processing in combination with the engineering direct cost data and the engineering indirect cost data to obtain the corresponding construction economic index, includes: Acquire construction ancillary cost data corresponding to the plurality of pending highway construction plans, including loan amount data, construction period data, and natural disaster impact data; The loan amount data, construction period data and natural disaster impact data are processed by a preset highway cost assessment model to obtain construction ancillary cost data; According to the construction ancillary cost data, combined with the engineering direct cost data and the engineering indirect cost data, statistical processing is performed to obtain the total cost data corresponding to the multiple pending highway construction plans; Processing the total cost data of the scheme and the route length data to obtain unit cost data; The total cost data and the unit cost data of the scheme are processed to obtain the construction economic indexes corresponding to the multiple pending highway construction schemes.

[0046] It should be noted that one of the important indicators for comparing highway construction plans is the economic indicator, which is related to the total construction cost and unit construction cost. Therefore, it is necessary to first obtain the total construction cost of each pending highway construction plan, which is composed of construction ancillary costs, direct project costs and indirect project costs. Construction ancillary costs include the interest generated by construction loans and the additional costs caused by natural disasters. Among them, the specific value of the loan amount, as well as the loan interest rate, repayment method (such as equal principal and interest, equal principal, etc.) and loan term are clearly defined. This information will be used to calculate loan interest, which is an important part of the ancillary costs of construction. The planned construction period of the highway construction, including the start date and completion date, is accurately recorded. At the same time, factors that may affect the construction period are collected, such as the impact of the construction season (rainy season, winter, etc.) on construction efficiency, as well as key nodes and milestones in the construction process. In addition, natural disasters in the highway construction area are investigated, including the types of natural disasters (such as floods, earthquakes, mudslides, etc.), frequency and intensity of occurrence. Historical data from local meteorological, geological and other departments can be referred to, and different stages of highway construction can be evaluated according to the degree of impact of natural disasters. The highway cost evaluation model belongs to the traditional cost-plus model, which first calculates the known basic Ancillary costs, such as loan interest and management fees, are then estimated based on factors such as the construction period and the impact of natural disasters. The costs that may increase are finally added together. For example, for loan interest, it is calculated based on the loan amount, interest rate and loan term. For the cost increase caused by the extension of the construction period, it is calculated by estimating the labor, material and equipment costs during the extended construction period. For natural disaster risks, based on the risk assessment results, the possible losses and repair costs are estimated, and then a certain risk reserve is added. Then, after obtaining the total cost, the unit cost can be obtained in combination with the route length of the highway in the plan. The total cost data and unit cost data of the plan are further processed to obtain the construction economy index corresponding to multiple pending highway construction plans; The calculation formula of the construction economy index is: ; in, is the construction economy index corresponding to the i-th pending highway construction plan, , are the total cost data and unit cost data corresponding to the i-th pending highway construction plan, , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset highway cost database).

[0047] According to an embodiment of the present invention, the construction economy index, the traffic function matching index and the engineering construction difficulty index are processed to obtain the construction comprehensive evaluation indexes corresponding to the multiple pending highway construction plans, and the ranking and comparison are performed to obtain the optimal highway construction plan, including: Processing is performed according to the construction economy index, the traffic function matching index and the engineering construction difficulty index to obtain the construction comprehensive evaluation index corresponding to the plurality of pending highway construction plans; Comparing the comprehensive construction evaluation indexes to obtain the maximum value data; The pending highway construction plan corresponding to the maximum value data is the optimal highway construction plan.

[0048] It should be noted that, according to the construction economy index, traffic function matching index and engineering construction difficulty index obtained by processing, the construction comprehensive evaluation index corresponding to multiple pending highway construction plans is obtained, and then the one with the largest index concentration value is screened out, and the highway construction plan corresponding to it is the optimal highway construction plan; The calculation formula of the construction comprehensive evaluation index is: ; in, is the comprehensive evaluation index of the construction corresponding to the i-th pending highway construction plan, , , are the construction economy index, traffic function matching index, and engineering construction difficulty index corresponding to the i-th pending highway construction plan, , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset highway cost database).

[0049] According to an embodiment of the present invention, it also includes: The step of obtaining the traffic function characteristic data corresponding to the plurality of pending highway construction plans and processing to obtain the corresponding traffic function matching index specifically includes: Acquiring traffic function characteristic data corresponding to the plurality of pending highway construction plans, including design traffic flow adaptability data, design traffic efficiency data, and road congestion coefficient data; Processing the designed traffic flow adaptability data, the designed traffic efficiency data, and the road congestion coefficient data to obtain the traffic function matching index corresponding to the plurality of pending highway construction plans; The calculation formula of the traffic function matching index is: ; in, is the traffic function matching index corresponding to the i-th pending highway construction plan, , , are the design traffic flow adaptability data, design traffic efficiency data, and road congestion coefficient data corresponding to the i-th pending highway construction plan, , , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset highway cost database).

[0050] It should be noted that, on the other hand, the evaluation of the schemes also needs to consider the traffic function matching of each scheme, including: 1. Adaptability to traffic flow. Even if a scheme has a low cost, it may not be the optimal scheme if it cannot meet the needs of future traffic flow growth. The design traffic flow adaptability data is obtained based on the predicted traffic flow in the next 20 years. 2. Design traffic efficiency. A higher design speed usually means better traffic efficiency. If the design speed of Scheme 1 is 100 km / h and the design speed of Scheme 2 is 80 km / h, Scheme 1 may be more suitable for long-distance transportation or traffic scenarios with high timeliness requirements. 3. Road congestion coefficient. For example, although a highway construction scheme has a low cost, it has a small number of lanes. It is expected that traffic congestion will occur in the next 5-10 years, which indicates that its road congestion coefficient is large. The road congestion coefficient can be obtained through traffic network model processing based on the number of lanes, design speed, future traffic flow and road network results.

[0051] According to an embodiment of the present invention, it also includes: The step of obtaining the engineering technical characteristic data corresponding to the plurality of pending highway construction plans and processing to obtain the engineering construction difficulty index specifically includes: Processing the bridge engineering cost data and the tunnel engineering cost data in combination with the total cost data of the scheme to obtain bridge cost proportion data and tunnel cost proportion data; According to the bridge cost proportion data and the tunnel cost proportion data, combined with the filling volume data and the excavation volume data, the engineering construction difficulty index corresponding to the multiple pending highway construction plans is obtained; The calculation formula of the engineering construction difficulty index is: ; in, is the engineering construction difficulty index corresponding to the i-th pending highway construction plan, , , , are the bridge cost proportion data, tunnel cost proportion data, filling volume data, and excavation volume data corresponding to the i-th pending highway construction plan, respectively. , , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset highway cost database).

[0052] It should be noted that the evaluation of the plans also needs to take into account the difficulty of the engineering construction of each plan. Among them, the construction of bridges and tunnels will increase the difficulty of road construction. Therefore, the data on the proportion of bridge cost, tunnel cost, filling volume and excavation volume are counted, and then the above data are processed to obtain the engineering construction difficulty index corresponding to each pending highway construction plan.

[0053] The third aspect of the present invention provides a readable storage medium, which stores a program for the method for intelligently determining and processing highway costs. When the program for the method for intelligently determining and processing highway costs is executed by a processor, the steps of the method for intelligently determining and processing highway costs as described in any one of the above items are implemented.

[0054] The method, system and medium for intelligently determining and processing highway construction costs disclosed in the present invention obtain the characteristic data of roadbed engineering and pavement engineering corresponding to a plurality of pending highway construction plans, respectively process and obtain the corresponding roadbed engineering cost data and pavement engineering cost data, obtain the characteristic data of bridge engineering and tunnel engineering corresponding to a plurality of pending highway construction plans, respectively process and obtain the corresponding bridge engineering cost data and tunnel engineering cost data, perform statistical processing based on the roadbed engineering cost data and pavement engineering cost data, in combination with the bridge engineering cost data and the tunnel engineering cost data, obtain the corresponding engineering direct cost data, obtain the characteristic data of land acquisition and demolition and the characteristic data of survey and design corresponding to a plurality of pending highway construction plans, and process Obtain the corresponding engineering indirect cost data, obtain the construction ancillary cost data corresponding to multiple pending highway construction plans, and process them in combination with the engineering direct cost data and the engineering indirect cost data to obtain the corresponding construction economic index, obtain the traffic function characteristic data corresponding to multiple pending highway construction plans, process to obtain the corresponding traffic function matching index, obtain the engineering technical characteristic data corresponding to multiple pending highway construction plans, process to obtain the engineering construction difficulty index, process according to the construction economic index, the traffic function matching index and the engineering construction difficulty index, obtain the construction comprehensive evaluation index corresponding to multiple pending highway construction plans, and rank and compare them to obtain the optimal highway construction plan, thereby realizing the technology of intelligent measurement and processing of highway cost.

[0055] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0056] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0057] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0058] Those skilled in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, the aforementioned program can be stored in a readable storage medium, and when the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, and other media that can store program codes.

[0059] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

Claims

1. A method for intelligently measuring and processing highway construction costs, characterized in that: The following steps are involved: Acquire roadbed engineering characteristic data and pavement engineering characteristic data corresponding to a plurality of pending highway construction plans, and process them to obtain corresponding roadbed engineering cost data and pavement engineering cost data respectively; Acquire bridge engineering characteristic data and tunnel engineering characteristic data corresponding to the plurality of pending highway construction plans, and process them to obtain corresponding bridge engineering cost data and tunnel engineering cost data respectively; Perform statistical processing based on the roadbed engineering cost data and the pavement engineering cost data in combination with the bridge engineering cost data and the tunnel engineering cost data to obtain corresponding engineering direct cost data; Acquire the land acquisition and demolition characteristic data and the survey and design characteristic data corresponding to the plurality of pending highway construction plans, and process and obtain the corresponding engineering indirect cost data; Acquire the construction subsidiary cost data corresponding to the plurality of pending highway construction plans, and process them in combination with the engineering direct cost data and the engineering indirect cost data to obtain the corresponding construction economic efficiency index; Acquire the traffic function characteristic data corresponding to the plurality of pending highway construction plans, and process and obtain the corresponding traffic function matching index; Acquire engineering technical characteristic data corresponding to the plurality of pending highway construction plans, and process and obtain an engineering construction difficulty index; The construction economy index, traffic function matching index and engineering construction difficulty index are processed to obtain the construction comprehensive evaluation index corresponding to the multiple pending highway construction plans, and they are sorted and compared to obtain the optimal highway construction plan.

2. The method for intelligently measuring and processing highway construction cost according to claim 1 is characterized in that: The step of obtaining the roadbed engineering characteristic data and the pavement engineering characteristic data corresponding to the plurality of pending highway construction plans, and respectively processing and obtaining the corresponding roadbed engineering cost data and the pavement engineering cost data, comprises: Obtaining roadbed engineering characteristic data and pavement engineering characteristic data corresponding to multiple pending highway construction plans; The roadbed engineering characteristic data includes fill volume data, unit fill comprehensive cost data, excavation volume data and unit excavation comprehensive cost data; Perform statistical processing on the filling volume data, the unit filling comprehensive cost data, the excavation volume data and the unit excavation comprehensive cost data to obtain the roadbed engineering cost data; The pavement engineering characteristic data includes route length data, pavement width data, pavement thickness data and unit construction cost data; Statistical processing is performed based on the route length data, road surface width data, road surface thickness data and unit construction cost data to obtain road surface engineering cost data.

3. The method for intelligently measuring and processing highway construction cost according to claim 2 is characterized in that: The step of obtaining bridge engineering characteristic data and tunnel engineering characteristic data corresponding to the plurality of pending highway construction plans, and respectively processing to obtain corresponding bridge engineering cost data and tunnel engineering cost data, comprises: Acquire bridge engineering characteristic data and tunnel engineering characteristic data corresponding to the plurality of pending highway construction plans; The bridge engineering characteristic data includes bridge type data, bridge geological condition data, bridge span data and bridge length data; Processing the bridge type data, bridge geological condition data, bridge span data, and bridge length data through a preset bridge cost assessment model to obtain bridge engineering cost data; The tunnel engineering characteristic data includes bridge and tunnel geological condition data, support method data, tunnel width data and tunnel length data; The tunnel geological condition data, support method data, tunnel width data and tunnel length data are processed through a preset tunnel cost assessment model to obtain tunnel engineering cost data.

4. The method for intelligently measuring and processing highway construction cost according to claim 3 is characterized in that: The step of obtaining the land acquisition and demolition characteristic data and the survey and design characteristic data corresponding to the plurality of pending highway construction plans and processing and obtaining the corresponding engineering indirect cost data includes: Acquire land acquisition and demolition feature data and survey and design feature data corresponding to the plurality of pending highway construction plans; The land acquisition and demolition characteristic data include occupied land area data, land type data, house demolition area data, house type data and geographical location data; The land acquisition and demolition cost data are obtained by processing the occupied land area data, land type data, house demolition area data, house type data and geographical location data through a pre-land acquisition and demolition compensation assessment model; The survey and design characteristic data include project scale data, project complexity data and design workload data; Processing the engineering scale data, engineering complexity data and design workload data through a preset survey and design cost assessment model to obtain survey and design cost data; Statistical processing is performed on the land acquisition and demolition cost data and the survey and design cost data to obtain engineering indirect cost data.

5. The method for intelligently measuring and processing highway construction cost according to claim 4 is characterized in that: The obtaining of the construction subsidiary cost data corresponding to the plurality of pending highway construction plans and processing in combination with the engineering direct cost data and the engineering indirect cost data to obtain the corresponding construction economic index includes: Acquire construction ancillary cost data corresponding to the plurality of pending highway construction plans, including loan amount data, construction period data, and natural disaster impact data; The loan amount data, construction period data and natural disaster impact data are processed by a preset highway cost assessment model to obtain construction ancillary cost data; According to the construction ancillary cost data, combined with the engineering direct cost data and the engineering indirect cost data, statistical processing is performed to obtain the total cost data corresponding to the multiple pending highway construction plans; Processing the total cost data of the scheme and the route length data to obtain unit cost data; The total cost data and the unit cost data of the scheme are processed to obtain the construction economic indexes corresponding to the multiple pending highway construction schemes.

6. The method for intelligently measuring and processing highway construction cost according to claim 5 is characterized in that: The processing according to the construction economy index, the traffic function matching index and the engineering construction difficulty index is performed to obtain the construction comprehensive evaluation index corresponding to the multiple pending highway construction plans, and the ranking and comparison are performed to obtain the optimal highway construction plan, including: Processing is performed according to the construction economy index, the traffic function matching index and the engineering construction difficulty index to obtain the construction comprehensive evaluation index corresponding to the plurality of pending highway construction plans; Comparing the comprehensive construction evaluation indexes to obtain the maximum value data; The pending highway construction plan corresponding to the maximum value data is the optimal highway construction plan.

7. A highway cost intelligent measurement and processing system, characterized in that: The system includes: a memory and a processor, wherein the memory includes a program of a method for intelligently measuring and processing highway construction costs, and when the program of the method for intelligently measuring and processing highway construction costs is executed by the processor, the following steps are implemented: Acquire roadbed engineering characteristic data and pavement engineering characteristic data corresponding to a plurality of pending highway construction plans, and process them to obtain corresponding roadbed engineering cost data and pavement engineering cost data respectively; Acquire bridge engineering characteristic data and tunnel engineering characteristic data corresponding to the plurality of pending highway construction plans, and process them to obtain corresponding bridge engineering cost data and tunnel engineering cost data respectively; Perform statistical processing based on the roadbed engineering cost data and the pavement engineering cost data in combination with the bridge engineering cost data and the tunnel engineering cost data to obtain corresponding engineering direct cost data; Acquire the land acquisition and demolition characteristic data and the survey and design characteristic data corresponding to the plurality of pending highway construction plans, and process and obtain the corresponding engineering indirect cost data; Acquire the construction subsidiary cost data corresponding to the plurality of pending highway construction plans, and process them in combination with the engineering direct cost data and the engineering indirect cost data to obtain the corresponding construction economic efficiency index; Acquire the traffic function characteristic data corresponding to the plurality of pending highway construction plans, and process and obtain the corresponding traffic function matching index; Acquire engineering technical characteristic data corresponding to the plurality of pending highway construction plans, and process and obtain an engineering construction difficulty index; The construction economy index, traffic function matching index and engineering construction difficulty index are processed to obtain the construction comprehensive evaluation index corresponding to the multiple pending highway construction plans, and they are sorted and compared to obtain the optimal highway construction plan.

8. The highway cost intelligent measurement and processing system according to claim 7 is characterized in that: The step of obtaining the roadbed engineering characteristic data and the pavement engineering characteristic data corresponding to the plurality of pending highway construction plans, and respectively processing and obtaining the corresponding roadbed engineering cost data and the pavement engineering cost data, comprises: Obtaining roadbed engineering characteristic data and pavement engineering characteristic data corresponding to multiple pending highway construction plans; The roadbed engineering characteristic data includes fill volume data, unit fill comprehensive cost data, excavation volume data and unit excavation comprehensive cost data; Perform statistical processing on the filling volume data, the unit filling comprehensive cost data, the excavation volume data and the unit excavation comprehensive cost data to obtain the roadbed engineering cost data; The pavement engineering characteristic data includes route length data, pavement width data, pavement thickness data and unit construction cost data; Statistical processing is performed based on the route length data, road surface width data, road surface thickness data and unit construction cost data to obtain road surface engineering cost data.

9. The highway cost intelligent measurement and processing system according to claim 8 is characterized in that: The step of obtaining bridge engineering characteristic data and tunnel engineering characteristic data corresponding to the plurality of pending highway construction plans, and respectively processing to obtain corresponding bridge engineering cost data and tunnel engineering cost data, comprises: Acquire bridge engineering characteristic data and tunnel engineering characteristic data corresponding to the plurality of pending highway construction plans; The bridge engineering characteristic data includes bridge type data, bridge geological condition data, bridge span data and bridge length data; Processing the bridge type data, bridge geological condition data, bridge span data, and bridge length data through a preset bridge cost assessment model to obtain bridge engineering cost data; The tunnel engineering characteristic data includes bridge and tunnel geological condition data, support method data, tunnel width data and tunnel length data; The tunnel geological condition data, support method data, tunnel width data and tunnel length data are processed through a preset tunnel cost assessment model to obtain tunnel engineering cost data.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a method program for intelligently measuring and processing highway costs. When the method program for intelligently measuring and processing highway costs is executed by a processor, the steps of the method for intelligently measuring and processing highway costs as described in any one of claims 1 to 6 are implemented.

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