Differential analysis method, system and device for general cost scheme, and storage medium

Abstract

The invention provides a difference analysis method, system and device for a general cost scheme and a storage medium, and relates to the technical field of engineering cost, and the method comprises the steps: obtaining the historical cost data and market price data of each construction item in a target construction scheme of an engineering project, and combining the historical cost data and the market price data, generating a cost fluctuation coefficient of each construction item in a preset duration; according to the cost fluctuation coefficient, the initial project cost of each construction item is adjusted, and a first project cost is generated; according to the correlation degree of each construction item, generating an adjustment coefficient of each construction item; adjusting the first construction cost of each construction item according to the adjustment coefficient, and generating a second construction cost of each construction item within a preset time length; and adding the second project cost of each construction item to generate the total project cost of the target construction scheme, and when the total project cost exceeds a preset cost, generating early warning information. The technical effect of the invention is that the project cost is accurately predicted.

Description

Technical Field

[0001] The present application relates to the field of engineering cost technology, and in particular to a method, system, device and storage medium for analyzing differences in a general cost solution. Background Art

[0002] With the continuous advancement of urbanization, construction projects are increasing day by day. In order to improve the economic benefits of engineering projects, it is necessary to reasonably control the construction cost.

[0003] In the prior art, the quota pricing method is generally used to predict the project cost. This method applies the corresponding quota unit price based on the bill of quantities, calculates the cost of each construction item, and then summarizes the total project cost. However, the quota unit price is usually formulated based on historical data and cannot dynamically adapt to changes in the market environment. In the case of frequent market price fluctuations, the project cost calculated by applying the quota unit price often has a large deviation from the actual cost, resulting in the inability to accurately predict the project cost. Summary of the invention

[0004] The present application provides a method, system, device and storage medium for analyzing the differences of a general cost solution, which are used to accurately predict the project cost.

[0005] In a first aspect, the present application provides a method for analyzing differences in a general cost scheme, the method comprising: obtaining an initial construction cost of each construction item in a target construction scheme of an engineering project; obtaining historical cost data and market price data of each of the construction items, and generating a cost fluctuation coefficient of each of the construction items within a preset time period by combining the historical cost data and the market price data; adjusting the initial construction cost of each of the construction items according to the cost fluctuation coefficient to generate a first construction cost of each of the construction items within the preset time period; obtaining a correlation between each of the construction items, and generating an adjustment coefficient of each of the construction items according to the correlation; adjusting the first construction cost of each of the construction items according to the adjustment coefficient to generate a second construction cost of each of the construction items within the preset time period; adding the second construction costs of each of the construction items to generate a total construction cost of the target construction scheme, and generating an early warning message when the total construction cost exceeds the preset cost.

[0006] By adopting the above technical solution, by introducing the dual adjustment mechanism of cost fluctuation coefficient and adjustment coefficient, accurate evaluation and dynamic monitoring of project cost are achieved. This method first generates cost fluctuation coefficient based on historical cost data and market price data, which can accurately reflect the price change trend of each construction item within the preset time; secondly, by calculating the correlation between construction items and converting it into an adjustment coefficient, the degree of mutual influence between construction items is effectively quantified. This dual adjustment mechanism that takes into account market fluctuations and related influences enables the second project cost to more truly reflect the cost changes during the construction process. At the same time, by setting up an early warning mechanism, when the total project cost exceeds the preset cost, early warning information is generated in time, providing project managers with timely risk warnings, which helps to take effective cost control measures, thereby accurately predicting project costs.

[0007] Optionally, the historical cost data and the market price data are combined to generate a cost fluctuation coefficient for each of the construction items within a preset time period, including: determining the historical cost change trend of each of the construction items based on the historical cost data; predicting the market cost change trend of each of the construction items within a preset time period based on the historical cost change trend of each of the construction items and based on the market price data; generating a cost fluctuation coefficient for each of the construction items within a preset time period based on the change amplitude of the market price change trend, wherein the cost fluctuation coefficient increases with an increase in the market price change trend.

[0008] By adopting the above technical solution, the historical change law of construction items is analyzed through historical cost data, and the future cost trend is predicted in combination with the current market price data, thus establishing a cost trend analysis chain from history to the future. By mapping the change amplitude of the market cost change trend to the cost fluctuation coefficient, and setting the corresponding relationship that the cost fluctuation coefficient increases with the increase of the market cost change trend, the quantitative expression of cost fluctuation is realized. This dual analysis mechanism based on historical data and market data can not only accurately grasp the price change law of construction items, but also timely reflect the impact of market price fluctuations, making the cost fluctuation coefficient more predictable and practical, and providing a scientific basis for subsequent cost adjustments.

[0009] Optionally, obtaining the correlation between the construction items includes: obtaining construction process information of each construction item; determining the construction sequence dependency between the construction items based on the construction process information of each construction item; calculating the process overlap between any two construction items based on the construction sequence dependency; determining the degree of resource sharing between the construction items based on the process overlap; and determining the correlation between the construction items based on the degree of resource sharing between the construction items.

[0010] By adopting the above technical solution, the sequential dependency relationship between construction items is established by analyzing the construction process information, and the resource sharing between construction items is quantified based on the process overlap, and finally the correlation degree reflecting the degree of mutual influence of construction items is generated, and a progressive analysis system from construction process to resource sharing and then to correlation degree is constructed. This correlation degree calculation method based on the actual characteristics of the construction process can accurately identify and quantify the mutual influence relationship between construction items, avoiding the deviation that may be caused by simple empirical estimation. By incorporating actual construction elements such as construction sequence, process overlap and resource sharing into the scope of correlation degree calculation, the determination of correlation degree is more objective and reasonable, providing more reliable data support for subsequent cost adjustment.

[0011] Optionally, the process overlap between any two of the construction items is calculated based on the construction sequence dependency, including: determining the time interval of the construction process of any two of the construction items; calculating the overlapping duration of the construction process time intervals of any two of the construction items; taking the construction process duration of the construction item with the smallest construction process duration among any two of the construction items as the benchmark duration; calculating the ratio of the overlapping duration to the benchmark duration, and obtaining the process overlap between any two of the construction items, wherein the process overlap increases with the increase of the ratio of the overlapping duration to the benchmark duration.

[0012] By adopting the above technical solution, the degree of process overlap is quantified by analyzing the time interval characteristics of the construction items, the process overlap is determined by calculating the proportional relationship between the overlapping duration and the benchmark duration, and a corresponding relationship is set in which the overlap increases as the proportion increases. The construction items with shorter duration are selected as the benchmark to avoid calculation deviations caused by large differences in construction duration. This calculation method based on the time dimension makes the determination of process overlap more in line with the actual construction situation, can accurately reflect the actual situation of process intersection during the construction process, and provides a reliable basis for evaluating the degree of resource sharing between construction items.

[0013] Optionally, generating an adjustment coefficient for each of the construction items based on the correlation includes: constructing an association matrix based on the correlation, wherein the element value between any two construction items in the association matrix is ​​the correlation between the two construction items; based on the association matrix, calculating the sum of the correlation between each of the construction items and all other construction items to generate a cumulative value of the correlation of each of the construction items; and normalizing the cumulative value of the correlation of each of the construction items to obtain the adjustment coefficient of each of the construction items.

[0014] By adopting the above technical solution, the correlation between construction items is systematically expressed by constructing a correlation matrix, and the cumulative correlation value is obtained by calculating the sum of the correlation between each construction item and other construction items, and then the adjustment coefficient is generated through normalization. This processing method not only takes into account the direct correlation between construction items, but also reflects the comprehensive correlation degree of construction items in the entire project through the calculation of cumulative values. Normalization makes the adjustment coefficient have good comparability, which is convenient for intuitively reflecting the relative degree of influence of the correlation on each construction item in the subsequent cost adjustment, thereby providing a more accurate reference basis for cost adjustment.

[0015] Optionally, when the total project cost exceeds a preset cost, a warning message is generated, including: calculating the excess amount of the total project cost over the preset cost; determining a warning level according to the ratio of the excess amount to the preset cost; obtaining the ratio of the second project cost of each construction item to the total project cost; sorting each construction item in descending order according to the cost ratio of each construction item; and generating a warning message including the warning level, the excess amount, and the sorted information of each construction item.

[0016] By adopting the above technical solution, the hierarchical management of cost overrun risks is achieved by calculating the excess amount and setting the warning level. At the same time, by calculating the cost ratio of each construction item and sorting them in descending order, the contribution of each construction item to the total cost is clearly shown. This early warning mechanism, which includes warning level, excess amount and construction item sorting information, can not only intuitively reflect the severity of cost overruns, but also quickly identify key construction items with a high cost ratio, which helps project managers give priority to and control key construction items, and provides clear direction guidance for formulating targeted cost control measures.

[0017] Optionally, when the total project cost exceeds the preset cost, after generating the warning information, it also includes: obtaining alternative construction plans for each of the construction items; calculating the second project cost of each of the alternative construction plans; generating cost optimization suggestions based on the second project cost of each of the alternative construction plans; and adding the cost optimization suggestions to the warning information.

[0018] By adopting the above technical solution, by obtaining and analyzing the second engineering cost of alternative construction solutions, a specific and feasible optimization path is provided for cost control. By adding cost optimization suggestions to the early warning information, a complete closed loop from problem discovery to solution is formed, so that the early warning information not only has a prompting function, but also has guiding significance. This combination of early warning and optimization provides project managers with more comprehensive decision-making support, helps to take effective cost control measures in a timely manner, and improves the practicality and operability of cost management.

[0019] In a second aspect, the present application provides a system for analyzing differences in a general cost scheme, the system comprising: an acquisition module, a first generation module, an adjustment module, a second generation module, a third generation module and an output module; wherein the acquisition module is used to acquire the initial project cost of each construction item in the target construction scheme of the engineering project; the first generation module is used to acquire the historical cost data and market price data of each of the construction items, and generate a cost fluctuation coefficient of each of the construction items within a preset time period by combining the historical cost data and the market price data; the adjustment module is used to adjust the cost fluctuation coefficient of each of the construction items according to the cost fluctuation coefficient. The initial construction cost of the construction item is used to generate the first construction cost of each construction item within the preset time period; the second generating module is used to obtain the correlation between each construction item, and generate the adjustment coefficient of each construction item according to the correlation; the third generating module is used to adjust the first construction cost of each construction item according to the adjustment coefficient to generate the second construction cost of each construction item within the preset time period; the output module is used to add the second construction cost of each construction item to generate the total construction cost of the target construction plan, and generate a warning message when the total construction cost exceeds the preset cost.

[0020] In a third aspect, the present application provides an electronic device, adopting the following technical solution: comprising a processor, a memory, a user interface and a network interface, the memory being used to store instructions, the user interface and the network interface being used to communicate with other devices, and the processor being used to execute the instructions stored in the memory so that the electronic device executes a computer program of a difference analysis method such as any of the above-mentioned general cost schemes.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: a computer program that can be loaded by a processor and execute a difference analysis method of any of the above-mentioned general cost schemes is stored.

[0022] In summary, the present application includes at least one of the following beneficial technical effects: 1. By introducing the dual adjustment mechanism of cost fluctuation coefficient and adjustment coefficient, accurate evaluation and dynamic monitoring of project cost are achieved. This method first generates cost fluctuation coefficient based on historical cost data and market price data, which can accurately reflect the price change trend of each construction item within the preset time; secondly, by calculating the correlation between construction items and converting it into an adjustment coefficient, the degree of mutual influence between construction items is effectively quantified. This dual adjustment mechanism that takes into account market fluctuations and related influences enables the second project cost to more truly reflect the cost changes during the construction process. At the same time, by setting up an early warning mechanism, when the total project cost exceeds the preset cost, early warning information is generated in time, providing project managers with timely risk warnings, which helps to take effective cost control measures, thereby achieving accurate prediction of project costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flow chart of a difference analysis method of a general cost scheme provided in an embodiment of the present application; Figure 2 It is a structural schematic diagram of a difference analysis system for a general cost solution provided in an embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0024] Description of reference numerals: 1000, electronic device; 1001, processor; 1002, communication bus; 1003, user interface; 1004, network interface; 1005, memory. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0026] In the description of the embodiments of the present application, words such as "illustrative", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "illustrative", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "illustrative", "for example" or "for example" is intended to present related concepts in a concrete way.

[0027] With the rapid development of the construction industry, the scale and complexity of engineering projects are constantly increasing, and accurate engineering cost budgeting and control are becoming increasingly important. Current cost analysis methods are often based on price data at a fixed point in time, which cannot effectively respond to the dynamic changes in the prices of building materials, labor costs and other factors. This static estimation method is difficult to accurately reflect the actual cost changes during the project implementation cycle, which is easy to cause budget deviations.

[0028] Traditional methods usually treat each construction project as a relatively independent unit for cost accounting, without fully considering the various relationships between projects during the construction process, such as process dependence and resource sharing, which will have a significant impact on the overall cost. Existing cost analysis methods also have the problem of imperfect early warning mechanisms, and often problems can only be discovered after cost overruns have occurred. This lag limits the implementation of cost control measures and increases the difficulty of project cost control.

[0029] At the same time, when cost problems are discovered, existing methods are difficult to provide targeted optimization suggestions and lack a systematic alternative analysis mechanism. Although the engineering construction industry has accumulated a large amount of historical cost data, these data have not been fully utilized. Existing methods rarely consider historical data analysis and market trend forecasts, and different types of engineering projects often use different cost analysis methods. There is a lack of unified analysis standards and processes, which increases the complexity of cost management and is not conducive to the accumulation and promotion of experience.

[0030] Therefore, there is an urgent need for a general cost scheme difference analysis method that can comprehensively consider cost volatility and project correlation and has early warning and optimization functions to improve the scientificity and effectiveness of engineering cost management.

[0031] Figure 1 1 is a flow chart of a method for analyzing the difference of a general cost scheme provided in an embodiment of the present application. Figure 1 As shown, the method includes S101-S106: S101, obtaining the initial construction cost of each construction item in the target construction plan of the engineering project.

[0032] An engineering project is a general term for construction activities carried out to meet specific functional requirements, such as housing construction, municipal engineering, roads and bridges, and other construction projects.

[0033] The target construction plan refers to a specific implementation plan formulated for an engineering project, which includes construction process arrangements, resource allocation, technical requirements, etc., and is used to guide the specific implementation of the engineering project.

[0034] A construction item refers to a sub-item in an engineering project with relatively independent functions, such as earthwork, foundation engineering, main structure engineering, decoration engineering, etc. Each construction item contains corresponding construction content and quality requirements.

[0035] The initial project cost refers to the expected cost of each construction item calculated based on design documents and relevant specifications and standards before the start of the project. It reflects the benchmark cost level of the construction item under standard conditions.

[0036] When implementing it, we first need to obtain the initial construction cost of each construction item in the target construction plan of the project, which is the basic data for cost difference analysis. The target construction plan usually includes multiple construction items, such as earthwork, foundation engineering, main structure engineering, decoration engineering, etc. Each construction item has its corresponding initial construction cost.

[0037] The initial project cost can be obtained through the following ways: extracting the engineering quantity data of each construction item from the construction project's bill of quantities, and combining it with basic data such as engineering cost pricing quotas, material price information, and labor costs, using the quota pricing method to calculate the initial project cost of each construction item; or directly obtaining the contract price of each construction item from the project's construction contract, bidding documents and other materials as the initial project cost; or exporting the budget cost data of each construction item as the initial project cost through the engineering cost management system. The accuracy of the initial project cost data directly affects the reliability of subsequent cost analysis, so it is necessary to verify the authenticity and integrity of the data during the acquisition process to ensure that the data source is reliable.

[0038] By obtaining the initial project cost, we can establish benchmark data for cost analysis, provide data support for subsequent dynamic adjustments based on the cost fluctuation coefficient and cost adjustments based on the correlation of construction items, and also facilitate comparison with the preset cost to realize the cost early warning function.

[0039] S102, obtaining historical cost data and market price data of each construction item, combining the historical cost data and the market price data, and generating a cost fluctuation coefficient of each construction item within a preset time period.

[0040] Considering that the construction cost will fluctuate due to various factors during the implementation of the project, it is difficult to accurately reflect the actual cost changes of the construction items based solely on the initial construction cost. Therefore, it is necessary to obtain historical cost data and market price data of each construction item to predict the cost change trend.

[0041] Among them, historical cost data refers to the actual cost records of similar construction items in similar engineering projects in the past, including but not limited to detailed data such as material prices, labor costs, and machinery usage fees; market price data refers to real-time data such as raw material prices, labor prices, and machinery rental prices related to construction items in the current market.

[0042] On the basis of obtaining these data, firstly, according to the historical cost data, the historical cost change trend of each construction item is determined through data statistical analysis methods. This trend can reflect the cyclical change law and long-term change direction of the construction item cost. Then, the historical cost change trend is combined with the current market price data, and trend extrapolation, regression analysis and other methods are used to predict the market cost change trend of each construction item within the preset time, where the preset time refers to the estimated construction period from the start of the project to its completion.

[0043] Based on the predicted range of market cost trends, the cost fluctuation coefficient of each construction item within a preset period of time is calculated. The cost fluctuation coefficient increases with the increase in the market price trend, and can quantitatively reflect the fluctuation risk of the construction item cost.

[0044] The cost fluctuation coefficient is a numerical indicator used to quantify the range of changes in the cost of a construction item. It reflects the degree of instability of the cost of a construction item within a preset period of time. Specifically, the cost fluctuation coefficient is calculated by analyzing the trend of changes in historical cost data and market price data. Its calculation method can be the coefficient of variation method, that is, the ratio of the standard deviation of the cost of a construction item during the forecast period to the average cost is used as the cost fluctuation coefficient.

[0045] For example, if the cost fluctuation coefficient of a construction item is 0.15, it means that the cost of the construction item may fluctuate by 15% within the preset time. When the cost fluctuation coefficient is large, it means that the cost of the construction item is greatly affected by market factors and there is a high risk of cost changes; conversely, a small cost fluctuation coefficient indicates that the cost of the construction item is relatively stable.

[0046] In specific implementation, the cost change rate at each time point can be calculated based on historical cost data, and then combined with the current market price trend, the cost fluctuation coefficient can be obtained through mathematical statistics. For example, for the construction item of concrete engineering, by analyzing the changes in factors such as concrete material prices and labor costs in recent years, combined with market expectations, its cost fluctuation coefficient can be calculated, and then the cost risk level of the construction item can be evaluated.

[0047] Based on the above embodiment, as an optional implementation, in S102, combining historical cost data and market price data to generate the cost fluctuation coefficient of each construction item within a preset time period specifically includes S201-S203: S201, determining the historical cost change trend of each construction item based on the historical cost data.

[0048] S202, based on the historical cost change trend of each construction item and according to the market price data, predict the market cost change trend of each construction item within a preset period of time.

[0049] In order to more accurately predict the cost change trend of construction items, it is necessary to conduct a comprehensive analysis and forecast based on the historical cost change trend and combined with the current market price data.

[0050] First, by conducting a time series analysis of historical cost data, the cyclical characteristics, seasonal fluctuations, and long-term change trends of construction item cost changes are identified. Then, data on key factors that affect the cost of construction items in the current market are collected, such as market price data on raw material prices, labor costs, equipment rental costs, etc. These data can reflect the latest changes in the market. On this basis, trend extrapolation, regression analysis and other forecasting methods are used to combine historical cost change trends with market price data to predict the market cost change trends of each construction item within a preset period of time.

[0051] For example, for the construction item of reinforced concrete engineering, by analyzing its historical cost data, it is found that there are obvious seasonal fluctuations. At the same time, the current steel price is on the rise. When predicting the market cost change trend of this construction item, it is necessary to consider both seasonal factors and the impact of rising raw material prices. In the forecasting process, the historical cost trend can be used as the basis, and the market price change can be used as a correction factor to obtain a more realistic cost change trend forecast result. This forecasting method not only maintains the reference value of historical data, but also fully considers the dynamic changes of the market, and can provide a more accurate forecast of cost change trends.

[0052] S203, generating a cost fluctuation coefficient of each construction item within a preset time period according to the change range of the market cost change trend, wherein the cost fluctuation coefficient increases as the market cost change trend increases.

[0053] In order to quantitatively reflect the cost fluctuation risk of construction items within a preset time, it is necessary to generate a cost fluctuation coefficient based on the market cost change trend. The generation process uses mathematical statistics methods. First, the standard deviation and average value of the market cost change trend within the preset time are calculated, and then the cost fluctuation coefficient is calculated by the coefficient of variation method, that is, the standard deviation is divided by the average value to obtain the basic fluctuation coefficient. Considering that the increase in the market price change trend will increase the cost risk, it is necessary to introduce a trend correction factor on the basis of the basic fluctuation coefficient. When the market price change trend is rising, the trend correction factor is greater than 1, otherwise it is less than 1.

[0054] For example, the market cost change trend data of a construction item within a preset period of time shows that its standard deviation is 0.12 and the average value is 1.0, so the basic fluctuation coefficient is 0.12; if the market price of the construction item shows a clear upward trend, the trend correction factor may be 1.2, and the final cost fluctuation coefficient is 0.144. Through this calculation method, the cost fluctuation coefficient not only reflects the degree of discreteness of cost changes, but also reflects the impact of market trends on cost risks. For construction items with a clear upward trend in market price changes, their cost fluctuation coefficient increases accordingly. This design conforms to the risk law in actual projects: when market prices continue to rise, the risk of cost fluctuations usually increases accordingly. The generation of the cost fluctuation coefficient provides a scientific basis for subsequent cost adjustments, and also helps project managers identify high-risk construction items and take corresponding risk prevention and control measures in a timely manner.

[0055] S103, adjusting the initial construction cost of each construction item according to the cost fluctuation coefficient, and generating a first construction cost of each construction item within a preset time period.

[0056] In order to make the project cost forecast more in line with the actual situation, it is necessary to take the cost fluctuation factor into consideration. Therefore, this step uses the cost fluctuation coefficient obtained above to adjust the initial project cost. The adjustment process uses a mathematical model method to calculate the initial project cost of each construction item and the corresponding cost fluctuation coefficient to obtain the first project cost within the preset time.

[0057] The specific adjustment method is: multiply the initial project cost of the construction item by (1±cost fluctuation coefficient), where the choice of positive and negative signs is based on the judgment of the market price trend. When the market price is predicted to show an upward trend, a positive sign is taken, otherwise a negative sign is taken.

[0058] For example, if the initial construction cost of a construction item is 1 million yuan, the cost fluctuation coefficient is 0.15, and the market price is predicted to rise, then the first construction cost of the construction item is 100×(1+0.15)=1.15 million yuan. Through this adjustment, the construction cost forecast better reflects the impact of market changes. For construction items with a large cost fluctuation coefficient, the difference between the adjusted first construction cost and the initial construction cost is also relatively large, and this difference just reflects the higher cost risk of the construction item. The generation of the first construction cost provides basic data for the subsequent consideration of the impact of the correlation of construction items, and also makes the cost forecast closer to the actual project, which helps to improve the accuracy and reliability of cost control.

[0059] S104, obtaining the correlation degree of each construction item, and generating the adjustment coefficient of each construction item according to the correlation degree.

[0060] During the implementation of engineering projects, there are various relationships between construction items, such as process connection and resource sharing. These relationships will affect the actual cost of the construction items. Therefore, it is necessary to quantify this impact by obtaining the correlation between construction items.

[0061] The correlation refers to the degree of mutual influence between different construction items, which can be determined by analyzing factors such as process dependency, resource usage overlap, and technical requirement relevance between construction items. The specific method of obtaining it is: first, establish a construction item correlation matrix, where the element value in the matrix represents the correlation degree between two construction items. The correlation degree can be expressed as a value of 0-1, where 0 represents no correlation and 1 represents complete correlation; then, calculate the comprehensive correlation degree of each construction item based on the correlation matrix, that is, the sum of the correlation degrees of the construction item and all other construction items.

[0062] For example, in a certain project, the correlation between the foundation project and the main structure project is 0.8, indicating that there is a strong correlation between the two construction items. After obtaining the correlation, it needs to be converted into an adjustment coefficient that can be used for cost adjustment.

[0063] The method for generating the adjustment coefficient is: normalize the comprehensive correlation of the construction items, and determine the value range of the adjustment coefficient based on engineering experience. Generally, the adjustment coefficient can be set between 0.9 and 1.1. The greater the correlation of the construction item, the greater the deviation of its adjustment coefficient, which reflects the characteristic that the construction item is greatly affected by other construction items. For example, a construction item with a high comprehensive correlation may result in an adjustment coefficient of 1.08, indicating that the cost of the construction item may increase by 8% due to the correlation. By introducing the adjustment coefficient, the correlation effect between construction items can be quantified as a specific basis for cost adjustment, making the cost forecast results more complete and accurate. This cost adjustment method based on correlation helps to identify and control the cost risks caused by the correlation of construction items, and provide a more reliable basis for project management decisions.

[0064] Based on the above embodiment, as an optional implementation, in S103, obtaining the correlation of each construction item specifically includes S301-S305: S301, obtaining construction process information of each construction item.

[0065] S302: Determine the construction sequence dependency relationship between the construction items according to the construction process information of the construction items.

[0066] In order to accurately analyze the correlation between construction items, it is first necessary to clarify the construction sequence dependencies between the construction items. These dependencies directly affect the construction organization and resource allocation, and thus affect the project cost. The process of determining the construction sequence dependencies needs to be based on the process information of the construction items, including the construction characteristics, technical requirements and process flow of each construction item.

[0067] The specific determination method is: first, organize the construction process information of each construction item into a process network diagram, mark the start node and completion node of each construction item, and then analyze the logical relationship between the construction items to identify the subsequent construction items that must be started after a certain construction item is completed. This kind of front-to-back connection relationship is the construction sequence dependency relationship.

[0068] For example, in a housing construction project, the foundation project can only start after the earthwork excavation is completed, and the main structure project can only be constructed after the foundation project is completed. These constitute a clear construction sequence dependency relationship. Through the analysis of the construction sequence dependency relationship, a construction item dependency matrix can be established. The elements in the matrix are represented by 0 and 1, 1 indicates that there is a dependency relationship, and 0 indicates that there is no dependency relationship. This matrix expression method facilitates the subsequent calculation of correlation and generation of adjustment coefficients. The determination of the construction sequence dependency relationship is of great significance for identifying key construction items and optimizing construction organization, and also provides a basic basis for evaluating the cost impact between construction items.

[0069] For example, when the construction progress of a construction item is delayed, the affected subsequent construction items can be quickly identified through the construction sequence dependency, and the scope of cost impact can be evaluated.

[0070] S303, calculating the process overlap between any two construction items according to the construction sequence dependency.

[0071] Based on the above embodiment, as an optional implementation, in S103, calculating the process overlap between any two construction items according to the construction sequence dependency specifically includes S401-S404: S401, determining the time interval of the construction procedures of any two construction items.

[0072] S402, calculating the overlapping duration of the construction process time intervals of any two construction items.

[0073] S403: The construction process duration of the construction item with the smallest construction process duration among any two construction items is taken as the reference duration.

[0074] S404, calculating the ratio of the overlapping time to the benchmark time, and obtaining the process overlap between any two construction items, wherein the process overlap increases as the ratio of the overlapping time to the benchmark time increases.

[0075] In order to accurately quantify the overlap of processes between construction items, it is necessary to calculate the degree of process overlap through systematic steps. First, according to the construction schedule and process arrangement, the specific construction time interval of each construction item, including the start time and end time, is determined.

[0076] For example, the time interval of construction item A is from March 1 to April 15, and the time interval of construction item B is from April 1 to May 15. After determining the time interval, calculate the overlapping part of the time intervals of the two construction items, that is, the duration from the later start time point to the earlier end time point. Taking the above example as an example, the overlapping time interval of construction items A and B is from April 1 to April 15, and the overlapping duration is 15 days. In order to make the calculation of process overlap more comparable, it is necessary to select a suitable reference benchmark. Here, the smaller value of the process duration of the two construction items is used as the benchmark duration. Still using the above example for analysis, the duration of construction item A is 46 days, and the duration of construction item B is 45 days, so 45 days is selected as the benchmark duration. Finally, by calculating the ratio of the overlapping duration to the benchmark duration, the process overlap is obtained. In this example, the process overlap is 15 / 45≈0.33, indicating that the process overlap of the two construction items is 33%. The design of process overlap follows the positive correlation principle, that is, the greater the proportion of overlapping time to benchmark time, the greater the process overlap. This design conforms to the law of the impact of process intersection on resource sharing and construction cost in actual engineering.

[0077] For example, when two construction items completely overlap, the overlapping duration is equal to the duration of the smaller construction item. At this time, the process overlap reaches the maximum value of 1, indicating that the process overlap degree of the two construction items is the highest.

[0078] S304: Determine the degree of resource sharing between construction items according to the degree of process overlap.

[0079] S305: Determine the correlation between the construction items according to the resource sharing degree between the construction items.

[0080] During the construction process, there is often overlap in processes and resource sharing between different construction items, which directly affects the construction organization efficiency and project cost. Therefore, it is necessary to determine the degree of resource sharing by analyzing the process overlap, and then determine the correlation between construction items.

[0081] First, based on the construction item schedule and process arrangement, calculate the proportion of the process overlap time between any two construction items to the total construction period, that is, the process overlap degree. For example, if the total construction period of two construction items is 100 days, of which 30 days have process overlap, the process overlap degree is 0.3. According to the process overlap degree, combined with the use of resources such as personnel, equipment, and materials at the construction site, the degree of resource sharing between construction items can be determined. The calculation of the resource sharing degree takes into account the number and importance of shared resources. The weighted average method can be used to comprehensively quantify the sharing of different types of resources.

[0082] For example, two construction items share crane equipment and construction personnel, where the equipment sharing weight is 0.6 and the personnel sharing weight is 0.4. The comprehensive resource sharing degree can be calculated based on these weights and the actual sharing degree. After determining the resource sharing degree, the correlation between the construction items is further calculated. The calculation of the correlation adopts a composite evaluation model, taking the process overlap and resource sharing degree as the main evaluation indicators, and considering the influence of the construction sequence dependency.

[0083] The specific calculation method is: weighted sum the process overlap, resource sharing and dependency strength according to the preset weights to obtain the correlation between the two construction items. For example, the process overlap of two construction items is 0.3, the resource sharing is 0.5, the dependency strength is 0.4, and the corresponding weights are 0.3, 0.4 and 0.3 respectively. The correlation between the two construction items is 0.3×0.3+0.5×0.4+0.4×0.3=0.41. The correlation determined by this method reflects both the physical correlation characteristics between construction items and the correlation characteristics of resource use, providing a more comprehensive and accurate basis for subsequent cost adjustment. It should be noted that the determination of the correlation should be dynamically adjusted according to the actual situation of the project to ensure that it reflects the actual construction correlation status.

[0084] Based on the above embodiment, as an optional implementation, in S104, generating the adjustment coefficient of each construction item according to the correlation degree specifically includes S501-S503: S501, constructing an association matrix according to the association degree, wherein the element value between any two construction items in the association matrix is ​​the association degree of the two construction items.

[0085] S502: Based on the association matrix, the sum of the associations between each construction item and all other construction items is calculated to generate a cumulative association value for each construction item.

[0086] S503, normalizing the cumulative value of the correlation degree of each construction item to obtain the adjustment coefficient of each construction item.

[0087] In order to scientifically quantify the degree of mutual influence between construction items and generate reasonable adjustment coefficients, it is necessary to construct and process the correlation matrix. First, the correlation between the construction items is organized in matrix form to construct an n×n correlation matrix (n is the number of construction items). The element value in the i-th row and j-th column of the matrix represents the correlation between the i-th construction item and the j-th construction item.

[0088] For example, in a project with four construction items, the association matrix may be in the form of [[1.0, 0.41, 0.25, 0.18], [0.41, 1.0, 0.33, 0.22], [0.25, 0.33, 1.0, 0.37], [0.18, 0.22, 0.37, 1.0]], where the diagonal elements are 1, indicating the association between the construction item and itself, and the off-diagonal elements indicate the association between different construction items. After constructing the association matrix, it is necessary to calculate the sum of the association between each construction item and all other construction items, that is, the cumulative association value. The calculation method is to add the elements of each row in the association matrix to obtain the cumulative association value of the construction item corresponding to that row.

[0089] In the above example, the cumulative correlation value of the first construction item is 1.0+0.41+0.25+0.18=1.84. In order to make the adjustment coefficient comparable and practical, the cumulative correlation value needs to be normalized. The normalization method is to divide the cumulative correlation value of each construction item by the sum of the cumulative correlation values ​​of all construction items, and the result is the adjustment coefficient of the construction item.

[0090] Assuming that the cumulative correlation values ​​of the four construction items are 1.84, 1.96, 1.95 and 1.77 respectively, the total is 7.52, and the adjustment coefficient of the first construction item is 1.84 / 7.52≈0.245. The adjustment coefficient obtained by this method not only reflects the correlation strength between the construction item and other construction items, but also ensures that the sum of the adjustment coefficients is 1, which is convenient for reasonable allocation in subsequent cost adjustments. The larger the adjustment coefficient, the higher the correlation between the construction item and other construction items, and more mutual influences need to be considered in cost adjustments.

[0091] S105, adjusting the first construction cost of each construction item according to the adjustment coefficient to generate a second construction cost of each construction item within a preset time period.

[0092] In order to further improve the accuracy of project cost forecasts, it is necessary to incorporate the correlation effects between construction items into cost calculations. This requires using the adjustment coefficient obtained above to adjust the first project cost, so as to obtain a second project cost that is more in line with reality.

[0093] The calculation method used in the adjustment process is: multiply the first engineering cost of each construction item by the corresponding adjustment coefficient to obtain the second engineering cost after considering the correlation effect. For example, the first engineering cost of a construction item is 1.15 million yuan, and its adjustment coefficient is 1.08, then the second engineering cost of the construction item is 115×1.08=1.242 million yuan. This adjustment method reflects the impact of the correlation of construction items on the cost: for construction items with a high correlation with other construction items, the degree of deviation of the adjustment coefficient from 1.0 is large, so the difference between the adjusted second engineering cost and the first engineering cost is also large, which reflects the cost changes that may be caused by the correlation effect during the actual construction process of the construction item. By generating the second engineering cost, not only the impact of market fluctuations is considered, but also the correlation effect between construction items is taken into consideration, making the cost forecast result more comprehensive and reasonable. The generation of the second engineering cost provides more accurate basic data for subsequent cost warning and optimization, which helps project managers better grasp the engineering cost risks and formulate more targeted cost control measures.

[0094] S106, adding up the second project costs of each construction item to generate a total project cost of the target construction solution, and generating a warning message when the total project cost exceeds a preset cost.

[0095] In order to comprehensively evaluate the overall cost level of the project and promptly identify cost risks, it is necessary to summarize the second engineering cost of each construction item to obtain the total engineering cost of the target construction plan.

[0096] The calculation method is to simply add up the second engineering costs of all construction items. For example, if a project contains n construction items, its total engineering cost is equal to the sum of the second engineering costs of these n construction items. After obtaining the total engineering cost, it is necessary to compare it with the preset cost, where the preset cost refers to the cost control target determined in the early stage of the project, usually determined in the project establishment or engineering budget stage.

[0097] When the total cost of a project exceeds the preset cost, the system will automatically generate early warning information, which includes key information such as the overspending amount, overspending ratio, and major overspending construction items. For example, the preset cost of a project is 10 million yuan, and the total cost of the project calculated is 11.5 million yuan, which exceeds the preset cost by 1.5 million yuan, and the overspending ratio is 15%. At this time, the system will generate corresponding early warning information. The generation of early warning information enables project managers to discover cost risks in a timely manner and find out the key links of cost control by analyzing the composition of overspending construction items.

[0098] Based on the above embodiment, as an optional implementation, in S106, when the total construction cost exceeds the preset construction cost, generating warning information specifically includes S601-S605: S601, calculating the excess amount of the total project cost over the preset cost.

[0099] S602, determining the warning level according to the ratio of the excess amount to the preset construction cost.

[0100] S603, obtaining the proportion of the second project cost of each construction item to the total project cost.

[0101] S604, sorting the construction items in descending order according to the cost ratio of each construction item.

[0102] S605, generating warning information including warning level, excess amount and sorted information of each construction item.

[0103] In order to timely discover and respond to the situation where the project cost exceeds the budget, a complete early warning mechanism needs to be established. When the total project cost exceeds the preset cost, the excess amount is first calculated, that is, the difference between the total project cost and the preset cost.

[0104] For example, if the preset cost of a project is RMB 10 million and the current total cost is RMB 11.5 million, the excess amount is RMB 1.5 million. The warning level is determined based on the ratio of the excess amount to the preset cost. Different warning thresholds can be set, such as yellow warning for an excess ratio of less than 10%, orange warning for 10%-20%, and red warning for an excess ratio of more than 20%.

[0105] In the above example, the excess ratio is 15%, corresponding to the orange warning level. In order to identify the main factors causing cost overruns, it is necessary to analyze the proportion of each construction item in the total cost. By calculating the proportion of the second engineering cost of each construction item to the total cost of the project, such as reinforced concrete engineering accounts for 25%, decoration engineering accounts for 20%, and electromechanical installation engineering accounts for 15%. By sorting these construction items from large to small according to the cost ratio, the key construction items with a greater impact on the total cost can be intuitively displayed. Finally, the warning level, the excess amount, and the sorted information of each construction item are integrated to generate warning information to form a complete warning report. The content of the warning information should include: warning level (such as orange warning), excess amount (1.5 million yuan), cost ratio ranking of each construction item (such as "1. Reinforced concrete engineering 25%, 2. Decoration engineering 20%, 3. Electromechanical installation engineering 15%...") and other key information. This warning mechanism helps project managers quickly identify cost risks through quantitative indicators and clear analysis results, and provides a decision-making basis for formulating targeted control measures.

[0106] At the same time, the ranking information of the cost ratio helps managers to give priority to and control those construction items that have a greater impact on the total cost, thereby improving the efficiency and effectiveness of cost control. It should be noted that the early warning information should be updated in a timely manner, and the early warning threshold should be appropriately adjusted according to the actual situation to ensure the practicality and accuracy of the early warning mechanism.

[0107] When the total cost of the project exceeds the preset cost, after the early warning information is generated, it also includes: Obtain alternative construction plans for each construction item; calculate the second engineering cost of each alternative construction plan; generate cost optimization suggestions based on the second engineering cost of each alternative construction plan; and add the cost optimization suggestions to the early warning information.

[0108] In order to effectively control and reduce the construction cost, it is necessary to provide a specific and feasible optimization plan after issuing the early warning information. First, obtain the alternative construction plans for each construction item from the construction plan library or historical engineering cases. These plans need to meet the engineering quality requirements and technical specifications.

[0109] For example, for exterior wall decoration projects, alternative solutions may include using tiles of different specifications, using different brands of paint, or choosing different decorative materials; for concrete projects, alternative solutions may include adjusting the concrete grade, optimizing the mix ratio, or changing the construction process. After obtaining alternative solutions, it is necessary to calculate the secondary engineering cost of each alternative solution. The calculation process needs to take into account changes in material costs, labor costs, machinery usage fees, and other related costs caused by changes in construction processes.

[0110] For example, the cost of the second project of the original plan for an exterior wall decoration project is 2 million yuan, the cost of the plan to use domestic tiles instead of imported tiles is 1.6 million yuan, and the cost of the plan to use high-performance coatings is 1.5 million yuan. Based on the cost calculation results of each alternative plan, generate specific cost optimization suggestions, which should include specific measures for plan changes, expected cost savings, implementation difficulty assessment, and possible risk warnings.

[0111] Based on the above method, the present application also discloses a difference analysis system for a general cost scheme, such as Figure 2 As shown, Figure 2 : is a structural diagram of a difference analysis system for a general cost solution provided in an embodiment of the present application, the system comprises: an acquisition module, a first generation module, an adjustment module, a second generation module, a third generation module and an output module; wherein, An acquisition module is used to acquire the initial construction cost of each construction item in the target construction plan of the engineering project; a first generation module is used to acquire the historical cost data and market price data of each construction item, and generate the cost fluctuation coefficient of each construction item within a preset time period by combining the historical cost data and the market price data; an adjustment module is used to adjust the initial construction cost of each construction item according to the cost fluctuation coefficient, and generate the first construction cost of each construction item within the preset time period; a second generation module is used to acquire the correlation of each construction item, and generate the adjustment coefficient of each construction item according to the correlation; a third generation module is used to adjust the first construction cost of each construction item according to the adjustment coefficient, and generate the second construction cost of each construction item within the preset time period; an output module is used to add the second construction cost of each construction item to generate the total construction cost of the target construction plan, and generate an early warning message when the total construction cost exceeds the preset cost.

[0112] It should be noted that: when the system provided in the above embodiment realizes its functions, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0113] See also Figure 3 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 3 As shown, the electronic device 1000 may include: at least one processor 1001 , at least one network interface 1004 , a user interface 1003 , a memory 1005 , and at least one communication bus 1002 .

[0114] The communication bus 1002 is used to realize the connection and communication between these components.

[0115] The user interface 1003 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 1003 may also include a standard wired interface and a wireless interface.

[0116] The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0117] Among them, the processor 1001 may include one or more processing cores. The processor 1001 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 1005, and calling data stored in the memory 1005. Optionally, the processor 1001 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 1001 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 1001, and it can be implemented separately through a chip.

[0118] Among them, the memory 1005 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 1005 includes a non-transitory computer-readable storage medium. The memory 1005 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 1005 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 1005 may optionally also be at least one storage device located away from the aforementioned processor 1001. As Figure 3 As shown, the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program for a method for analyzing differences in a general cost solution.

[0119] exist Figure 3In the electronic device 1000 shown, the user interface 1003 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 1001 can be used to call an application program stored in the memory 1005 for a difference analysis method for a general cost scheme. When executed by one or more processors, the electronic device executes one or more methods described in the above embodiments.

[0120] An electronic device readable storage medium stores instructions, which, when executed by one or more processors, enable the electronic device to execute one or more of the methods described in the above embodiments.

[0121] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0122] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0123] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which 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 integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0124] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, 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 solution of this embodiment.

[0125] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0126] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory 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 steps of the method described in each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0127] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the specification and practicing the disclosure here, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for analyzing the difference of a general cost scheme, characterized in that: The method comprises: Obtain the initial construction cost of each construction item in the target construction plan of the project; Acquire historical cost data and market price data of each of the construction items, and generate a cost fluctuation coefficient of each of the construction items within a preset time period by combining the historical cost data and the market price data; According to the cost fluctuation coefficient, the initial construction cost of each construction item is adjusted to generate the first construction cost of each construction item within the preset time period; Obtaining the correlation degree of each of the construction items, and generating an adjustment coefficient of each of the construction items according to the correlation degree; The first engineering cost of each of the construction items is adjusted according to the adjustment coefficient to generate a second engineering cost of each of the construction items within the preset time period; The second engineering costs of the construction items are added together to generate a total engineering cost of the target construction plan. When the total engineering cost exceeds a preset cost, an early warning message is generated.

2. The difference analysis method of the general cost scheme according to claim 1 is characterized in that: The combining of the historical cost data and the market price data to generate the cost fluctuation coefficient of each construction item within a preset time period includes: Determine the historical cost change trend of each of the construction items according to the historical cost data; Based on the historical cost change trends of each of the construction items, and according to the market price data, predict the market cost change trends of each of the construction items within a preset period of time; According to the variation range of the market cost variation trend, a cost fluctuation coefficient of each construction item within a preset time period is generated, wherein the cost fluctuation coefficient increases as the market cost variation trend increases.

3. The difference analysis method of the general cost scheme according to claim 1 is characterized in that: The obtaining of the relevance of each of the construction items includes: Obtaining construction process information of each of the construction items; Determining the construction sequence dependency relationship between the construction items according to the construction process information of the construction items; Calculate the process overlap between any two construction items according to the construction sequence dependency relationship; Determining the degree of resource sharing between the construction items according to the degree of overlap of the process; The correlation degree of each construction item is determined according to the resource sharing degree between each construction item.

4. The difference analysis method of the general cost scheme according to claim 3 is characterized in that: The step of calculating the process overlap between any two of the construction items according to the construction sequence dependency relationship includes: Determine the time interval of the construction process of any two of the construction items; Calculate the overlapping duration of the construction process time intervals of any two construction items; The duration of the construction process of the construction item with the smallest duration of the construction process among any two of the construction items is taken as the benchmark duration; The ratio of the overlapping duration to the benchmark duration is calculated to obtain the process overlap between any two construction items, wherein the process overlap increases as the ratio of the overlapping duration to the benchmark duration increases.

5. The difference analysis method of the general cost scheme according to claim 1 is characterized in that: Generating the adjustment coefficient of each construction item according to the correlation degree includes: According to the correlation degree, a correlation matrix is ​​constructed, wherein the element value between any two construction items in the correlation matrix is ​​the correlation degree of the two construction items; Based on the association matrix, the sum of the associations between each construction item and all other construction items is calculated to generate a cumulative association value for each construction item; The cumulative value of the correlation degree of each construction item is normalized to obtain the adjustment coefficient of each construction item.

6. The difference analysis method of the general cost scheme according to claim 1 is characterized in that: When the total cost of the project exceeds the preset cost, an early warning message is generated, including: Calculate the excess amount of the total project cost over the preset cost; Determine the warning level according to the ratio of the excess amount to the preset construction cost; Obtaining the proportion of the second project cost of each of the construction items to the total project cost; According to the cost ratio of each construction item, sorting the construction items in descending order; Generate warning information including the warning level, the excess amount and sorted information of each of the construction items.

7. The difference analysis method of the general cost scheme according to claim 1 is characterized in that: When the total construction cost exceeds the preset construction cost, after generating the warning information, the method further includes: Obtaining alternative construction plans for each of the construction items; Calculate the second engineering cost of each of the alternative construction solutions; Generating cost optimization suggestions based on the second engineering costs of each of the alternative construction solutions; The cost optimization suggestion is added to the early warning information.

8. A differential analysis system for general cost solutions, characterized in that: The system comprises: an acquisition module, a first generation module, an adjustment module, a second generation module, a third generation module and an output module; wherein, The acquisition module is used to acquire the initial construction cost of each construction item in the target construction plan of the engineering project; The first generating module is used to obtain the historical cost data and market price data of each of the construction items, and generate the cost fluctuation coefficient of each of the construction items within a preset time period by combining the historical cost data and the market price data; The adjustment module is used to adjust the initial construction cost of each construction item according to the cost fluctuation coefficient to generate a first construction cost of each construction item within the preset time period; The second generating module is used to obtain the correlation degree of each of the construction items, and generate the adjustment coefficient of each of the construction items according to the correlation degree; The third generating module is used to adjust the first engineering cost of each construction item according to the adjustment coefficient to generate a second engineering cost of each construction item within the preset time period; The output module is used to add up the second engineering costs of each of the construction items to generate a total engineering cost of the target construction plan, and generate warning information when the total engineering cost exceeds a preset cost.

9. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 7.

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