Intelligent evaluation system and method of sponge city construction effect based on data analysis

Abstract

The present invention relates to the technical field of data intelligent evaluation system, and more specifically, to an intelligent evaluation system and method for the construction effect of a sponge city based on data analysis, including: a data acquisition module for collecting rainfall data, runoff data, water purification data and sponge facility operation and maintenance data in a sponge city construction area; a data processing module for processing and analyzing the data collected by the data acquisition module; an intelligent evaluation module for evaluating the construction effect of a sponge city based on the analysis results of the data processing module. The data acquisition module comprehensively collects various types of data in the sponge city construction area to provide a rich data source for subsequent analysis. The data processing module abstracts the complex sponge city system into quantifiable indicators through a series of innovative mathematical models, such as rainfall-runoff topological matrix, sponge facility influencing factors, etc. The intelligent evaluation module gives the final evaluation results based on these processed data.

Description

Technical Field

[0001] The present invention relates to the technical field of data intelligent evaluation systems, and more specifically, to a system and method for intelligent evaluation of sponge city construction effects based on data analysis. Background Art

[0002] In recent years, with the acceleration of urbanization and the increasing impact of climate change, urban waterlogging and water shortage have become increasingly prominent. In response to these challenges, the concept of sponge city construction has emerged and has been widely promoted and applied around the world. Sponge cities aim to achieve sustainable use of water resources and improve the urban ecological environment by changing the traditional urban development model and enhancing the city's adaptability to natural precipitation and artificial water cycles.

[0003] However, with the deepening of sponge city construction practice, how to accurately and comprehensively evaluate the effect of sponge city construction has become an urgent problem to be solved. Traditional evaluation methods mainly rely on a single or a few indicators, such as runoff coefficient, pollutant removal rate, etc., which are difficult to fully reflect the comprehensive benefits of sponge cities. These methods often ignore the impact of sponge city construction on the overall ecosystem, and it is difficult to capture the synergistic effects between different construction measures.

[0004] In addition, most existing evaluation methods rely on expert experience and judgment, lacking objective and quantitative evaluation criteria. This not only leads to poor comparability and repeatability of evaluation results, but also makes it difficult to provide clear and intuitive guidance for decision makers. At the same time, with the development of Internet of Things technology and big data analysis technology, sponge city construction has generated a large amount of real-time monitoring data, but existing evaluation methods are difficult to fully utilize these rich data resources and cannot achieve dynamic and real-time evaluation of the effects of sponge city construction.

[0005] Another significant problem is that existing evaluation methods often simply equate the effects of sponge city construction with its hydrological effects, ignoring the comprehensive impact of sponge cities on urban ecosystems. For example, some evaluation methods only focus on runoff control and water quality improvement, while ignoring the contributions of sponge cities to biodiversity, microclimate regulation, etc. This one-sided evaluation method may cause sponge city construction to deviate from its original intention of comprehensively improving the quality of urban ecological environment.

[0006] In view of the above problems, there is an urgent need for an intelligent evaluation system and method that can comprehensively consider multiple factors, make full use of big data resources, and objectively and quantitatively evaluate the effect of sponge city construction. This system and method should be able to achieve a comprehensive, dynamic, and objective evaluation of the effect of sponge city construction, and provide a scientific basis for the planning, construction, and management of sponge cities. Summary of the invention

[0007] The present invention is proposed to solve the above technical problems. The present invention provides a data analysis-based intelligent evaluation system and method for the construction effect of sponge cities, which realizes a comprehensive and objective evaluation of the construction effect of sponge cities through multi-dimensional data collection, innovative mathematical model construction and intelligent algorithm application.

[0008] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0009] The intelligent evaluation system of sponge city construction effect based on data analysis includes:

[0010] The data collection module is used to collect rainfall data, runoff data, water purification data and sponge facility operation and maintenance data in the sponge city construction area;

[0011] A data processing module, used for processing and analyzing the data collected by the data collection module;

[0012] The intelligent evaluation module is used to evaluate the effect of sponge city construction based on the analysis results of the data processing module.

[0013] Preferably, the data processing module comprises:

[0014] A rainfall-runoff topological matrix construction unit is used to construct a topological matrix describing the relationship between rainfall and runoff;

[0015] A sponge facility impact factor calculation unit, used to calculate the impact factor of the sponge facility based on the topological matrix;

[0016] A water purification efficiency evaluation unit, used to evaluate the water purification efficiency based on the sponge facility influencing factor;

[0017] An ecosystem service function evaluation unit, used to evaluate the ecosystem service function based on the water purification efficiency;

[0018] The final score calculation unit is used to calculate the final score of the sponge city construction effect based on the ecosystem service function.

[0019] Preferably, the topological matrix R constructed by the rainfall-runoff topological matrix construction unit is defined as:

[0020] The topological matrix constructed by the rainfall-runoff topological matrix construction unit Defined as:

[0021] in, For the The rainfall points The influence coefficient of the runoff point is is the number of rainfall monitoring points, is the number of runoff monitoring points.

[0022] Preferably, the sponge facility impact factor S calculated by the sponge facility impact factor calculation unit is defined as:

[0023] in, is the nxn unit matrix, α is the adjustment parameter , is the eigenvalue of the matrix R, Represents the matrix determinant.

[0024] Preferably, the water purification efficiency Q evaluated by the water purification efficiency evaluation unit is defined as:

[0025] Among them, K is the number of monitored water quality indicators, is the influent concentration of the i-th water quality index, is the effluent concentration of the i-th water quality indicator, is the weight of the i-th water quality index and , tanh(-) is the hyperbolic tangent function.

[0026] Preferably, the ecosystem service function E evaluated by the ecosystem service function evaluation unit is defined as:

[0027] Among them, f(z) is a holomorphic function describing the complexity of the ecosystem, and γ is the enclosing A simple closed curve, is the complex plane representation of the evaluation points.

[0028] Preferably, the final score F of the sponge city construction effect calculated by the final score calculation unit is defined as:

[0029] in, To adjust the parameters used to control the sensitivity of the score, is the cumulative distribution function of the standard normal distribution.

[0030] The intelligent evaluation method for the sponge city construction effect based on data analysis using the system includes the following steps:

[0031] Collect rainfall data, runoff data, water purification data and sponge facility operation and maintenance data in the sponge city construction area;

[0032] Processing and analyzing the collected data;

[0033] Based on the analysis results, the effect of sponge city construction is evaluated.

[0034] Preferably, the step of processing and analyzing the collected data further comprises:

[0035] Construct a topological matrix describing the relationship between rainfall and runoff;

[0036] Calculating the impact factor of the sponge facility based on the topological matrix;

[0037] Evaluate water purification efficiency based on the influencing factors of the sponge facility;

[0038] Assessing ecosystem service functions based on the water purification efficiency;

[0039] The final score of the sponge city construction effect is calculated based on the ecosystem service functions.

[0040] Preferably, the specific calculation process of constructing a topological matrix describing the relationship between rainfall and runoff, calculating the impact factors of sponge facilities, evaluating water purification efficiency, evaluating ecosystem service functions and calculating the final score of sponge city construction effects is the same as the described calculation process.

[0041] Compared with the prior art, the beneficial effects of the present invention are embodied in the following aspects:

[0042] The system of the present invention includes a data acquisition module, a data processing module and an intelligent evaluation module. The three modules work closely together to form a complete evaluation chain. The data acquisition module comprehensively collects various types of data in the sponge city construction area, providing a rich data source for subsequent analysis. The data processing module abstracts the complex sponge city system into quantifiable indicators through a series of innovative mathematical models, such as rainfall-runoff topological matrix, sponge facility impact factor, etc. The intelligent evaluation module gives the final evaluation results based on these processed data.

[0043] This modular design not only improves the flexibility and scalability of the system, but also realizes the automation of the entire process from data collection to final evaluation. The close collaboration between the modules of the system solves the problems of insufficient data utilization and single evaluation indicators in traditional evaluation methods. At the same time, by introducing complex mathematical models and algorithms, this system can capture the nonlinear characteristics of the sponge city construction effect, which is difficult to achieve with traditional evaluation methods.

[0044] More importantly, the system of the present invention incorporates the impact of sponge city construction on the overall ecological environment into the evaluation system by introducing the ecosystem service function evaluation, thus achieving a comprehensive evaluation of the effect of sponge city construction. This evaluation method not only considers the direct hydrological effect, but also focuses on the long-term impact of sponge city construction on the ecosystem, thus providing decision makers with more comprehensive and valuable information support.

[0045] In general, the system and method of the present invention achieves a comprehensive, objective and dynamic evaluation of the effect of sponge city construction through innovative technical means, providing a powerful tool for the scientific planning and effective management of sponge cities. This not only helps to improve the efficiency and effect of sponge city construction, but also makes an important contribution to promoting sustainable urban development. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a flowchart of the overall system of the present invention.

[0047] Figure 2 It is a logic block diagram of the data processing module of the present invention.

[0048] Figure 3 It is a logic block diagram of the rainfall-runoff topology matrix construction unit of the present invention.

[0049] Figure 4 It is a logic block diagram of the sponge facility impact factor calculation unit of the present invention.

[0050] Figure 5 It is a logic block diagram of the water purification efficiency evaluation unit of the present invention.

[0051] Figure 6 This is a logic block diagram of the ecosystem service function evaluation unit of the present invention.

[0052] Figure 7 It is a logic block diagram of the final score calculation unit of the present invention. DETAILED DESCRIPTION

[0053] like Figure 1-7 As shown, the present invention provides a system and method for intelligent evaluation of sponge city construction effects based on data analysis. The system includes a data acquisition module 2, a data processing module 3 and an intelligent evaluation module 4, which collects, processes and analyzes multi-dimensional data of the sponge city construction area, and finally conducts a comprehensive and objective evaluation of the sponge city construction effect.

[0054] Specifically, the intelligent evaluation system for sponge city construction effect based on data analysis of the present invention includes the following modules:

[0055] Data collection module 1 is used to collect rainfall data, runoff data, water purification data and sponge facility operation and maintenance data in the sponge city construction area. This module collects relevant data in real time through various sensors and monitoring equipment deployed in the sponge city construction area. For example, rainfall data can be obtained through a rain gauge, runoff data can be measured through a flow meter, water purification data can be collected through water quality monitoring equipment, and sponge facility operation and maintenance data can be recorded in real time through IoT devices.

[0056] The data processing module 2 is used to process and analyze the data collected by the data collection module 1. The module first cleans, standardizes and preprocesses the original data, and then uses the original algorithm of the present invention to perform in-depth analysis. The core of the data processing module 2 lies in its unique analysis method, which can extract valuable information from multi-dimensional data and provide a solid foundation for subsequent intelligent evaluation.

[0057] The intelligent evaluation module 3 is used to evaluate the effect of sponge city construction based on the analysis results of the data processing module 2. This module comprehensively considers multiple indicators and finally gives a quantitative evaluation result of the effect of sponge city construction through a complex algorithm model.

[0058] Preferably, the data processing module 2 of the present invention includes the following units:

[0059] The rainfall-runoff topology matrix construction unit 21 is used to construct a topology matrix describing the relationship between rainfall and runoff. This unit innovatively introduces the concept of topology and expresses the complex relationship between rainfall and runoff in the form of a matrix. Specifically, the topology matrix R is defined as follows:

[0060] in, For the The rainfall points The influence coefficient of the runoff point is is the number of rainfall monitoring points, is the number of runoff monitoring points. This representation method can intuitively reflect the spatial relationship between rainfall and runoff, laying the foundation for subsequent analysis.

[0061] The topological matrix R is used to describe the spatial relationship between rainfall points and runoff points. In sponge city construction, the relationship between rainfall points (such as rain gauge monitoring points) and runoff points (such as rivers, lakes and other water body monitoring points) is very complex, especially in urban environments, where factors such as terrain, buildings, and greenery will affect how rainfall is converted into runoff.

[0062] matrix is a The matrix of is the number of rainfall monitoring points, is the number of runoff monitoring points. Each element Indicates The rainfall points The coefficient of influence of a runoff point can be determined through historical data, geographic information system (GIS) analysis, or physical models. For example, if a rainfall point is located on high ground and close to a river, it may have a greater impact on the runoff of the river, and the corresponding The value will also be higher.

[0063] By constructing such a topological matrix, the system can quantify the relationship between rainfall and runoff, thus providing a basis for subsequent hydrological simulation and prediction. This matrix form can not only intuitively display spatial relationships, but can also be used for further mathematical operations, such as matrix multiplication, eigenvalue decomposition, etc., to reveal deeper laws.

[0064] The sponge facility impact factor calculation unit 22 is used to calculate the impact factor of the sponge facility based on the topological matrix. This unit quantifies the impact of the sponge facility on the rainfall-runoff relationship into an impact factor through complex mathematical operations. The specific calculation formula is as follows:

[0065] in, is the nxn unit matrix, α is the adjustment parameter , is the eigenvalue of the matrix R, This calculation method takes into account the impact of the sponge facility on the entire system, not just the local effect.

[0066] Sponge facilities (such as rain gardens, permeable pavement, green roofs, etc.) are an important part of sponge city construction. They reduce flood risks and improve water quality by regulating the rainfall-runoff relationship. In order to evaluate the effectiveness of these facilities, a quantitative indicator needs to be introduced - the sponge facility impact factor .

[0067] The core of this formula is the matrix The determinant and eigenvalue of . Specifically: yes The identity matrix represents the system state when there is no sponge facility. is a tuning parameter with a value range of , used to control the impact intensity of sponge facilities. Indicates that the sponge facility has a greater impact on the system, and a smaller It means the impact is weak. is a matrix No. The eigenvalues ​​reflect the coupling strength between different rainfall points and runoff points in the system. The larger the eigenvalue, the more significant the impact of the rainfall point on the runoff. represents the stability or "response" of the entire system in the presence of the sponge facility. The determinant is a measure of whether the matrix is ​​reversible, and here it reflects the change in the overall behavior of the system caused by the sponge facility. The denominator It is a correction term for all eigenvalues, ensuring that the result of the formula will not be distorted by some extreme eigenvalues.

[0068] By calculating the sponge facility impact factor , the system can quantify the comprehensive impact of sponge facilities on the entire hydrological system. This factor can not only be used to evaluate the effectiveness of existing facilities, but also provide a reference for future design and optimization. For example, if a certain area The low value indicates that the sponge facilities in this area may be insufficient and need to be further strengthened.

[0069] The water purification efficiency evaluation unit 23 is used to evaluate the water purification efficiency based on the sponge facility influencing factor. This unit innovatively associates the water purification efficiency with the sponge facility influencing factor and maps it through a nonlinear function. The specific calculation formula is as follows:

[0070] Among them, K is the number of monitored water quality indicators, is the influent concentration of the i-th water quality indicator, is the effluent concentration of the i-th water quality indicator, is the weight of the i-th water quality index and , tanh(-) is the hyperbolic tangent function. This calculation method not only takes into account multiple water quality indicators, but also better reflects the actual effect of water purification through nonlinear mapping.

[0071] Water purification is one of the important goals of sponge city construction. Especially in the process of urbanization, rainwater runoff often carries a large amount of pollutants, which will affect the water quality after entering the water body. Therefore, it is crucial to evaluate the water purification effect of sponge facilities.

[0072] It is a comprehensive score of water purification efficiency, with a value range of [0,1], where 1 indicates complete purification and 0 indicates no purification effect. It is the number of monitored water quality indicators, usually including dissolved oxygen, chemical oxygen demand (COD), ammonia nitrogen, total phosphorus, etc. and Respectively represent The inlet concentration and outlet concentration of each water quality indicator can be obtained in real time through water quality monitoring equipment. It is The weight of each water quality indicator reflects the importance of the indicator in the overall water quality assessment. The sum of the weights is 1, that is . is the hyperbolic tangent function, whose range is [-1,1]. ,The changes of water quality can be mapped into a nonlinear interval to better reflect the actual purification effect.

[0073] In particular, when When the water quality is improved, it means that the water quality has improved; otherwise, it means that the water quality has deteriorated. Will The output is mapped from [-1, 1] to [0, 1], and weighted average is performed according to the weights to finally obtain a comprehensive water purification score.

[0074] This formula not only takes into account multiple water quality indicators, but also better reflects the actual effect of water purification through nonlinear mapping. For example, for some sensitive water quality indicators (such as heavy metal content), even if their concentration changes are small, they may have a significant impact on the ecosystem, so they can be given a higher weight. In this way, the system can more accurately evaluate the purification effect of sponge facilities on water quality.

[0075] The ecosystem service function evaluation unit 24 and the final score calculation unit 25 will be described in detail in the subsequent claims.

[0076] The system of the present invention realizes a comprehensive and objective evaluation of the effect of sponge city construction through the collaborative work of the above modules and units. The innovation of this system lies in: first, it adopts a multi-dimensional data collection method, which comprehensively covers all aspects that affect the effect of sponge cities; second, it introduces the concept of topology and describes the complex relationship between rainfall and runoff in the form of a matrix; third, it quantifies the impact of sponge facilities, water purification efficiency and other factors into comparable indicators through complex mathematical models; finally, it adopts advanced mathematical methods such as nonlinear mapping to better reflect the complex relationship between various factors.

[0077] In general, the system of the present invention provides a new and scientific method for evaluating the effect of sponge city construction, which is expected to play an important role in practical applications. The ecosystem service function evaluation unit 24 is used to evaluate the ecosystem service function based on water purification efficiency. This unit innovatively introduces the theory of complex variable functions and describes the complexity of the ecosystem through holomorphic functions. The specific calculation formula is as follows:

[0078] Among them, f(z) is a holomorphic function describing the complexity of the ecosystem, and γ is the enclosing A simple closed curve, The advantage of this method is that it can capture the nonlinear characteristics and integrity of the ecosystem, thereby more accurately evaluating the impact of sponge cities on the ecosystem.

[0079] In a preferred embodiment of the present invention, You can choose a polynomial function, such as ,in, is a constant determined according to the actual characteristics of the ecosystem. This choice not only ensures the feasibility of the calculation, but also reflects the complexity of the ecosystem to a certain extent.

[0080] Ecosystem service functions refer to the various services that ecosystems provide to humans, such as water supply, climate regulation, biodiversity protection, etc. In the construction of sponge cities, in addition to the direct hydrological effects, its long-term impact on the entire urban ecosystem also needs to be considered.

[0081] It is the ecosystem service function index, and its value range is [0,1], where 1 indicates the strongest ecosystem service function and 0 indicates the weakest. It is the aforementioned water purification efficiency score, which reflects the effect of the sponge facility on improving water quality. Good water quality is the basis of a healthy ecosystem, so It plays an important role in the assessment of ecosystem service functions.

[0082] It is a form of complex variable function integral, which is used to describe the holomorphic function of the complexity of the ecosystem. .here, It is surrounded A simple closed curve, is the complex plane representation of the evaluation point. Complex variable function theory is a powerful mathematical tool that can capture the nonlinear characteristics and integrity of the system. By introducing complex variable functions , the system can more accurately describe the dynamic changes of the ecosystem. For example, species diversity, energy flow, material circulation, etc. in the ecosystem can be modeled in the form of complex functions. is an application of the Cauchy integral formula, which can calculate the average value of a function over a region on the complex plane. In this formula, describes the distribution of ecosystem complexity, while represents the location of the assessment point. In this way, the system can quantify the ecosystem service functions at different locations.

[0083] This formula links water purification efficiency with ecosystem service functions, reflecting that sponge city construction not only focuses on direct hydrological effects, but also considers its impact on the entire urban ecosystem. By introducing complex function theory, the system can more accurately evaluate the impact of sponge cities on the ecosystem, thus providing a scientific basis for the sustainable development of cities.

[0084] The final score calculation unit 25 is used to calculate the final score of the sponge city construction effect based on the ecosystem service function. This unit uses a combination of the sigmoid function and the normal distribution cumulative function, which not only ensures that the score result is between 0 and 1, but also gives the score result probabilistic meaning. The specific calculation formula is as follows:

[0085] in, To adjust the parameters used to control the sensitivity of the score, is the cumulative distribution function of the standard normal distribution.

[0086] Preferably, The value of can be adjusted according to the specific application scenario. For example, when λ=1, the scoring result is more sensitive to changes in ecosystem service functions; when λ=0.5, the scoring result is relatively gentle to changes in ecosystem service functions. This flexibility enables the system to adapt to different evaluation needs.

[0087] Final Rating It is a comprehensive evaluation of the effect of sponge city construction, with a value range of [0,1], where 1 represents the best construction effect and 0 represents the worst. This scoring result can be directly used for horizontal comparison between different sponge city projects, and can also provide important reference for decision makers.

[0088] Part I is the sigmoid function, which is often used to map real values ​​to the interval [0,1]. The characteristics of the sigmoid function are: when the input value is large, the output is close to 1; when the input value is small, the output is close to 0. is a tuning parameter that controls the sensitivity of the score. will make the score more sensitive to changes in ecosystem service functions, while smaller This will make the ratings more even.

[0089] Part 2 is the cumulative distribution function (CDF) of the standard normal distribution, denoted by Its value range is [0,1], indicating the ecosystem service function Cumulative probability under standard normal distribution. The role of this part is to give probabilistic meaning to the scoring results, so that the score is not just a simple numerical value, but a probability value with statistical significance. By combining the siqmoid function with the normal distribution cumulative function, the system can give probabilistic meaning to the scoring results while ensuring the intuitiveness of the scoring results. This allows the scoring results to be used not only for comparison of different projects, but also to provide more information support for decision makers.

[0090] Final Rating Comprehensive consideration of ecosystem service functions The impact of the evaluation results is analyzed and converted into an easy-to-understand and easy-to-use score through a mathematical model. This scoring method not only ensures the intuitiveness of the results, but also gives the results probabilistic meaning, making the evaluation results more convincing. When , the scoring results are more sensitive to changes in ecosystem service functions; when When , the scoring result is relatively flat, which is suitable for different evaluation needs.

[0091] The system of the present invention realizes the full process analysis from raw data to final score through the above series of innovative calculation units. Each unit is closely connected, and the output of the previous unit is used as the input of the next unit, forming a complete evaluation chain. This design not only ensures the consistency and reliability of the evaluation process, but also can capture multiple aspects of the sponge city construction effect in the evaluation process.

[0092] For example, through the rainfall-runoff topology matrix, the system can accurately describe the impact of rainfall on runoff in different regions, which is crucial for evaluating the rainwater management effect of sponge cities. The introduction of sponge facility influencing factors allows the system to consider the contribution of sponge facilities of different types and sizes to the overall effect. The evaluation of water purification efficiency directly reflects the performance of sponge cities in improving the water environment, which is one of the core goals of sponge city construction.

[0093] Furthermore, the innovation of this system lies in incorporating ecosystem service functions into the evaluation system. This practice reflects that sponge city construction not only focuses on direct hydrological effects, but also considers its impact on the entire urban ecosystem. By introducing complex variable function theory, this system can quantify this complex ecological impact in a mathematically rigorous and practically meaningful way.

[0094] Finally, the design of the final scoring calculation unit ensures the intuitiveness of the scoring results (a value between 0 and 1) and gives the results probabilistic meaning. This design enables the evaluation results to be used not only for horizontal comparisons between different sponge city projects, but also to provide more information support for decision makers.

[0095] In general, the system of the present invention achieves a comprehensive, objective and scientific evaluation of the effect of sponge city construction through a series of innovative mathematical models and algorithms. This evaluation method not only takes into account traditional hydrological indicators, but also takes into account broader factors such as ecosystem service functions, providing a new paradigm for the evaluation of sponge city construction effects.

[0096] The present invention also provides a method for intelligently evaluating the effect of sponge city construction based on data analysis. This method is closely related to the aforementioned system and is a specific implementation step of the system function. Specifically, this method includes the following steps:

[0097] First, collect rainfall data, runoff data, water purification data, and sponge facility operation and maintenance data in the sponge city construction area. This step is the basis of the entire evaluation process and ensures the data source for subsequent analysis. In actual operation, various advanced sensors and monitoring equipment can be used for data collection. For example, automatic weather stations can be used to collect rainfall data, flow meters can be used to measure runoff, water purification data can be collected through online water quality monitors, and the operation and maintenance of sponge facilities can be recorded in real time through IoT devices.

[0098] Secondly, the collected data is processed and analyzed. This step is the core of the method and involves a complex data processing and analysis process. In a preferred embodiment of the present invention, this step further includes the following sub-steps:

[0099] Construct a topological matrix describing the relationship between rainfall and runoff. This substep uses the aforementioned rainfall-runoff topological matrix construction unit to express the complex rainfall-runoff relationship in the form of a matrix. This representation method provides a mathematical basis for subsequent analysis.

[0100] The influence factor of the sponge facility is calculated based on the topological matrix. This sub-step uses the aforementioned sponge facility influence factor calculation unit to quantify the influence of the sponge facility on the rainfall-runoff relationship into a specific value through complex mathematical operations.

[0101] Evaluate water purification efficiency based on sponge facility impact factors. This sub-step uses the aforementioned water purification efficiency evaluation unit to associate water purification efficiency with sponge facility impact factors and map them through nonlinear functions.

[0102] The ecosystem service function is evaluated based on water purification efficiency. This sub-step uses the aforementioned ecosystem service function evaluation unit, introduces complex variable function theory, and describes the complexity of the ecosystem through holomorphic functions.

[0103] The final score of the sponge city construction effect is calculated based on the ecosystem service function. This sub-step uses the aforementioned final score calculation unit and a combination of the sigmoid function and the normal distribution cumulative function to obtain the final evaluation result.

[0104] Finally, the effect of sponge city construction is evaluated based on the analysis results. This step converts the previous complex mathematical analysis results into practical evaluation conclusions to provide reference for decision makers.

[0105] Preferably, the specific calculation process in the method of the present invention is the same as the calculation process of each unit in the aforementioned system. This consistency ensures the coordination between the method and the system, so that the theory and practice of the present invention are closely combined.

[0106] For example, when constructing the rainfall-runoff topology matrix, the aforementioned matrix representation method is still used:

[0107] Similarly, the aforementioned corresponding formulas are used when calculating the impact factor of sponge facilities, evaluating water purification efficiency, evaluating ecosystem service functions, and calculating the final score.

[0108] The advantage of this method is that it provides a complete process from data collection to final evaluation. Each step has been carefully designed, taking into account both the rigor of the theory and the feasibility of practical application. For example, in the data collection stage, this method clearly points out the type of data that needs to be collected, which provides clear guidance for practical operations. In the data processing and analysis stage, this method introduces a series of innovative mathematical models that can not only handle complex sponge city systems, but also capture the nonlinear characteristics of the system.

[0109] It is particularly worth mentioning that this method introduces the important concept of ecosystem service function in the evaluation process. This reflects the comprehensive understanding of the effects of sponge city construction in this paper, which not only focuses on direct hydrological effects, but also considers broader ecological impacts. This comprehensive evaluation method helps decision makers make more scientific and reasonable decisions.

[0110] In general, the method of the present invention provides a systematic and scientific approach to the evaluation of the effect of sponge city construction. Through this method, the effect of sponge city construction can be objectively and comprehensively evaluated, providing important decision-making support for urban planning and management. The application of this method is expected to promote the development of sponge city construction in a more scientific and efficient direction.

[0111] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto; any person familiar with the art who, within the scope disclosed by the present invention, makes substitutions or changes based on the scheme and improved concepts of the present invention shall be covered within the protection scope of the present invention.

Claims

1. The intelligent evaluation system of sponge city construction effect based on data analysis is characterized by: include: Data collection module, used to collect rainfall data, runoff data, water purification data and sponge facility operation and maintenance data in the sponge city construction area; A data processing module, used for processing and analyzing the data collected by the data collection module; An intelligent evaluation module, used to evaluate the effect of sponge city construction based on the analysis results of the data processing module; The data processing module comprises: A rainfall-runoff topological matrix construction unit is used to construct a topological matrix describing the relationship between rainfall and runoff; A sponge facility impact factor calculation unit, used to calculate the impact factor of the sponge facility based on the topological matrix; A water purification efficiency evaluation unit, used to evaluate the water purification efficiency based on the sponge facility influencing factor; An ecosystem service function evaluation unit, used to evaluate the ecosystem service function based on the water purification efficiency; A final score calculation unit, used to calculate the final score of the sponge city construction effect based on the ecosystem service function; The topological matrix R constructed by the rainfall-runoff topological matrix construction unit is defined as: The topological matrix constructed by the rainfall-runoff topological matrix construction unit Defined as: ； in, For the The rainfall points The influence coefficient of the runoff point is is the number of rainfall monitoring points, is the number of runoff monitoring points; The sponge facility impact factor S calculated by the sponge facility impact factor calculation unit is defined as: ； in, is the nxn unit matrix, α is the adjustment parameter , is the eigenvalue of the matrix R, represents the matrix determinant; The water purification efficiency Q evaluated by the water purification efficiency evaluation unit is defined as: ； Among them, K is the number of monitored water quality indicators, is the influent concentration of the i-th water quality indicator, is the effluent concentration of the i-th water quality indicator, is the weight of the i-th water quality index and , tanh(-) is the hyperbolic tangent function; The ecosystem service function E evaluated by the ecosystem service function evaluation unit is defined as: ； Among them, f(z) is a holomorphic function describing the complexity of the ecosystem, and γ is the enclosing A simple closed curve, is the complex plane representation of the evaluation points.

2. The system according to claim 1, characterized in that The final score F of the sponge city construction effect calculated by the final score calculation unit is defined as: ； in, To adjust the parameters used to control the sensitivity of the score, is the cumulative distribution function of the standard normal distribution.

3. A method for intelligently evaluating the effect of sponge city construction based on data analysis using the system described in any one of claims 1-2, characterized in that: The following steps are involved: Collect rainfall data, runoff data, water purification data and sponge facility operation and maintenance data in the sponge city construction area; Processing and analyzing the collected data; Based on the analysis results, the effect of sponge city construction is evaluated.

4. The method according to claim 3, characterized in that: The steps of processing and analyzing the collected data further include: Construct a topological matrix describing the relationship between rainfall and runoff; Calculating the impact factor of the sponge facility based on the topological matrix; Evaluate water purification efficiency based on the influencing factors of the sponge facility; Assessing ecosystem service functions based on the water purification efficiency; The final score of the sponge city construction effect is calculated based on the ecosystem service functions.

5. The method according to claim 4, characterized in that The specific calculation process of constructing a topological matrix describing the relationship between rainfall and runoff, calculating the impact factor of sponge facilities, evaluating water purification efficiency, evaluating ecosystem service functions and calculating the final score of sponge city construction effect is the same as the calculation process described in claims 1 to 2.

Images