Desert road sand prevention project benefit evaluation method based on variable weight matter element extension model

Abstract

The invention provides a desert road sand prevention project benefit evaluation method based on a variable weight matter element extension model, and relates to the technical field of sand prevention project benefit evaluation, and the method comprises the steps: collecting meteorological data and soil data of a sand prevention project region before and after the project is implemented, calculating a temperature and humidity comfort index, and collecting sand prevention project data; calculating an engineering cost index, an effect evaluation index and an environmental influence index by combining the dimensionless temperature and humidity comfort index, the meteorological data, the soil data and the sand prevention engineering data; a desert road sand prevention project benefit multi-dimensional evaluation index system is constructed, a time factor is introduced, project benefits are evaluated based on a variable weight matter element extension model, the project benefits are divided into three grades, namely high efficiency, medium efficiency and low efficiency, and the sand prevention project benefits are quantitatively evaluated according to evaluation results. Scientific, comprehensive and efficient decision support is provided for desertification control and highway safety guarantee.

Description

Technical Field

[0001] The invention relates to the technical field of engineering benefit evaluation, in particular to a method for evaluating the benefits of desert highway sand control engineering based on a variable weight matter-element extension model. Background Art

[0002] As the global desertification problem becomes increasingly serious, the ecological environment governance and infrastructure construction in desert areas face severe challenges. As an important transportation link connecting desert areas, the sand control project of desert highways is not only an important means to ensure highway safety, but also an important measure to improve the regional ecological environment. However, the current benefit evaluation of desert highway sand control projects is mostly focused on single-dimensional analysis, such as the calculation of engineering economic costs or simple changes in vegetation coverage. This method lacks systematicity and comprehensiveness, and it is difficult to effectively reflect the comprehensive impact of sand control projects on regional ecological environment, engineering input-output benefits and long-term sustainability. In addition, existing evaluation methods are usually limited to qualitative analysis or comparison of static data, ignoring the dynamic change characteristics of environmental factors such as climate and soil in the time dimension, resulting in insufficient accuracy and guidance of evaluation results.

[0003] In addition, the existing technology lacks effective methods for quantifying and processing complex environmental factors in desert areas. For example, the climate conditions in desert areas are significantly volatile, and traditional evaluations often fail to fully consider the interaction of meteorological factors such as temperature, humidity, wind speed, precipitation, and their impact on the ecosystem. At the same time, soil properties have a profound impact on the benefits of sand control projects, but existing methods fail to scientifically evaluate them through parameters such as particle size analysis and uniformity index. More importantly, the current evaluation method lacks a dynamic adjustment mechanism and cannot reflect the changing characteristics of project priorities and benefits at different stages, making it difficult to make adaptive analysis of real-time data during the evaluation process. These problems make it difficult for the results of existing sand control project benefit evaluations to meet the actual needs of desertification control and highway protection project optimization.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0005] The purpose of the present invention is to provide a method for evaluating the benefits of desert highway sand control projects based on a variable-weight matter-element extension model to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A method for evaluating the benefits of desert highway sand control projects based on a variable weight matter-element extension model, the specific steps include:

[0008] Step 1: Collect meteorological data and soil data in the sand control project area before and after the implementation of the project. The meteorological data includes temperature, humidity, wind speed and precipitation, and the soil data includes soil moisture and particle composition. Add data interaction items and hierarchical processing to the temperature and humidity data, calculate the temperature and humidity comfort index, and collect the project implementation effect, project investment and project implementation time as sand control project data;

[0009] Step 2: Calculate the particle uniformity index based on the particle composition of the soil, calculate the wind intensity index based on the wind speed and the number of days with precipitation, and calculate the engineering cost index, effect evaluation index and environmental impact index of the project to be evaluated by combining the dimensionless temperature and humidity comfort index, meteorological data, soil data and sand control engineering data;

[0010] Step 3: Construct a multi-dimensional evaluation index system for the benefits of desert highway sand control projects from the three dimensions of project cost, effect evaluation and environmental impact, introduce the time factor, evaluate the project benefits based on the variable weight matter-element extension model, and divide the project benefits into three levels, namely high efficiency, medium efficiency and low efficiency. According to the evaluation results, conduct a quantitative evaluation of the project to be evaluated.

[0011] Furthermore, the meteorological data and soil data of the sand control project area before and after the implementation of the project are collected, which refers to the meteorological data and soil data one year before the sand control project and one year after the implementation of the project;

[0012] Collect ambient temperature data of the project area from the meteorological station, record the daily average temperature and calculate the annual average temperature and standard deviation of the project area:

[0013]

[0014] Where, T avg is the annual average temperature, T std is the standard deviation of temperature, T i is the average daily temperature of the i-th day, n is the statistical day, and i is the index of the day;

[0015] Sub-index 1: Temperature stability index is calculated according to the following formula:

[0016]

[0017] In the formula, is the temperature stability index, T std is the standard deviation of temperature;

[0018] The relative humidity is collected by humidity sensors, the daily average humidity is recorded and the annual average humidity of the project area is calculated. Relative humidity greater than 60% is defined as wet:

[0019]

[0020] In the formula, H avg is the average annual humidity, H std is the standard deviation of humidity, H i is the average daily relative humidity on the i-th day, n is the statistical day, and i is the index of the day;

[0021] Sub-index 2: Humidity fluctuation index is calculated according to the following formula:

[0022]

[0023] In the formula, is the humidity fluctuation index, H std is the standard deviation of humidity;

[0024] According to the temperature and humidity interaction term, the temperature and humidity comfort index is calculated based on the following formula:

[0025]

[0026] In the formula, is the temperature and humidity comfort index, T avg is the average annual temperature, H avg is the annual average humidity, 22℃ and 50% are the comfortable temperature and humidity conditions for human body respectively;

[0027] Record the wind speed with an anemometer and calculate the average annual wind speed:

[0028]

[0029] Where V avg is the annual average wind speed, V i is the average daily wind speed on the i-th day, n is the statistical day, and i is the index of the day;

[0030] Collect precipitation data through rain gauges to count the total annual precipitation and number of days with precipitation:

[0031]

[0032] P days = count(P i >0)

[0033] Where P total is the total annual precipitation, P i is the precipitation on the i-th day, n is the statistical day, i is the index of the day, P days is the number of days with precipitation;

[0034] The wind intensity index is calculated based on the following formula:

[0035] Q wind =V avg*P days

[0036] In the formula, Q wind is the wind intensity index, V avg is the annual average wind speed, P days is the number of days with precipitation;

[0037] The specific logic for collecting soil moisture is as follows:

[0038] Use a soil moisture sensor to measure shallow, middle and deep soil moisture, and take the average as the soil moisture:

[0039]

[0040] In the formula, S w is soil moisture, S w,shallow is the shallow soil moisture, S w,middle is the middle soil moisture, S w,deep is deep soil moisture;

[0041] Collect a certain amount of soil in the sand control project area as samples, and use soil sampling equipment to collect the respective proportions of sand, silt and clay to meet the following requirements:

[0042] S s +S p +S c =100%

[0043] Among them, S s is the proportion of sandy soil, S p is the proportion of silt, S c is the proportion of clay;

[0044] The changes in vegetation coverage before and after the project implementation were analyzed through drone aerial photography, and the changes in vegetation coverage were used as the project implementation effect:

[0045] ΔM=M after -M before

[0046] In the formula, ΔM is the change in vegetation coverage, M after is the vegetation coverage rate after the project is implemented, and is the vegetation coverage rate before the project is implemented;

[0047] The total investment amount of the sand control project is obtained from the historical project financial data as the project investment, denoted as C input ;

[0048] The project implementation time is calculated based on the start and end time of the project completion record, denoted as T induration .

[0049] Furthermore, the particle uniformity index is calculated based on the formula:

[0050]

[0051] Where X is the particle uniformity index, S s is the proportion of sandy soil, S p is the proportion of silt, S c is the proportion of clay, μ s , μ p and μ c The ideal average value of sand, silt and clay is based on the international soil classification standard, σ s , σ p and σ c are the standard deviations of the ideal ranges for sand, silt, and clay, respectively;

[0052] The calculation of the engineering cost index is based on the following formula:

[0053]

[0054] Among them, COST is the engineering cost index, T induration is the project implementation time, C input For project investment, C unit is the unit area cost, in units of 10,000 yuan / hectare, which is used to reflect the investment intensity of the project in different areas and is obtained according to the project plan. α is the time-related cost coefficient, which indicates the additional cost per unit time. ln is the natural logarithm, which is used to adjust the nonlinear relationship and smooth the data behavior.

[0055] The calculation formula for the effect evaluation index is:

[0056]

[0057] In the formula, ECT is the effect evaluation index, ΔM is the change in vegetation coverage, Q wind is the wind intensity index, is the temperature and humidity comfort index, S w is soil moisture, S ref is the reference value of soil moisture, ω1, ω2, ω3 and ω4 are preset proportional coefficients, and ω1>ω2>ω3>ω4>0;

[0058] The environmental impact index is calculated based on the following formula:

[0059]

[0060] Where ENV is the environmental impact index, is the temperature stability index, is the humidity fluctuation index, ΔP adjis the adjusted precipitation change rate, X is the particle uniformity index, and X ideal is the ideal particle uniformity index, X ideal =1, is the preset scaling factor, and

[0061] ΔP adj The calculation formula is:

[0062]

[0063] Where ΔP is the precipitation change rate, ΔP opt is the ideal precipitation change rate, [ΔP max , ΔP min ] is the reference value range of precipitation change rate;

[0064] The calculation formula of ΔP is:

[0065]

[0066] Where P total,after is the total annual precipitation after the project is implemented, P total,before It is the total annual precipitation before the project implementation.

[0067] Furthermore, an evaluation system is constructed and evaluated based on the variable weight matter-element extension model. The specific logic is as follows:

[0068] The engineering cost dimension, effect evaluation dimension and environmental impact dimension are used as the main evaluation indicators of the desert highway sand control project benefits; among them, the engineering cost dimension corresponds to the engineering cost index COST, the effect evaluation dimension corresponds to the effect evaluation index ECT, and the environmental impact dimension corresponds to the environmental impact index ENV;

[0069] The project benefits are divided into three levels: high efficiency, medium efficiency, and low efficiency. The expression is as follows:

[0070] E k =(c k ,[a k ,b k ])

[0071] Where k is the index of the level, k∈{1,2,3}, E1, E2 and E3 represent high efficiency, medium efficiency and low efficiency respectively, c k is the reference center value of level k, usually determined by historical data or expert knowledge, [a k ,b k ] is the classical domain range of level k, that is, the interval range of benefit value, which is determined based on historical data and expert knowledge;

[0072] The correlation between each dimension and the classical domain is calculated according to the following formula:

[0073]

[0074] K is the value of the association degree, which indicates the compatibility of the attribute value x with the classical domain. The attribute value x is the representative indicator of each dimension, including the engineering cost index COST, the effect evaluation index ECT and the environmental impact index ENV. K∈[0,1]. The closer K is to 1, the closer x is to the classical domain. [a,b] is the classical domain range of the level, and [c,d] is the node domain range, that is, the global upper and lower limits of the attribute value.

[0075] Furthermore, the time factor is introduced to adjust the comprehensive benefit index through dynamic weights:

[0076] The time factor f(t) is expressed as follows:

[0077]

[0078] Where f(t) represents the time factor, which is used to represent the progress ratio of the entire project implementation cycle at time t, and its value range is [0,1]; T induration is the project implementation time, t represents the cumulative time from the start of the project to time t, and 0≤t≤T induration ;

[0079]

[0080] Among them, Z total is the comprehensive benefit index, K j is the value of the association degree of the jth dimension, is the weight, is the initial weight of the j-th dimension, β j is the weight change rate of the jth dimension, j is the index of the dimension;

[0081] The comprehensive benefit index is compared with the preset threshold and divided into multiple levels according to the comparison results:

[0082] When Z total When ≥0.8, it means that the project benefit evaluation is highly efficient, the project performs well in the three dimensions of economic cost, actual effect and environmental impact, and the comprehensive benefit index reaches the high efficiency standard;

[0083] When 0.5≤Z total When <0.8, it means that the project benefit evaluation is medium, and the project has certain effects in the three dimensions of economic cost, actual effect and environmental impact, but there is still room for improvement in some aspects;

[0084] When Z totalWhen <0.5, it means that the project benefit evaluation is inefficient, and the project performs poorly in the three dimensions of economic cost, actual effect and environmental impact, and fails to achieve the expected goals.

[0085] Compared with the prior art, the present invention has the following beneficial effects:

[0086] This scheme introduces a variable-weighted matter-element extension model to construct a multi-dimensional evaluation system with engineering cost, effect evaluation and environmental impact as the core, overcoming the shortcomings of the traditional evaluation method of being single and static, and being able to dynamically adjust the weights of each dimension to adapt to the characteristics of different stages of project implementation, and fully reflect the comprehensive benefits of desert highway sand control projects. Through scientifically quantified indicators such as temperature and humidity comfort index, particle uniformity index, wind intensity index, and a dynamic weight adjustment mechanism based on time factors, it not only reflects the systematic and dynamic nature of the evaluation, but also provides a clear guiding basis for the optimization of the project through hierarchical evaluation, and provides scientific, comprehensive and efficient decision-making support for desertification control and highway safety assurance. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1 It is a schematic diagram of the overall method flow of the present invention. DETAILED DESCRIPTION

[0088] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0089] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0090] Example:

[0091] See also Figure 1 , the present invention provides a technical solution:

[0092] A method for evaluating the benefits of desert highway sand control projects based on a variable weight matter-element extension model, the specific steps include:

[0093] Step 1: Collect meteorological data and soil data in the sand control project area before and after the implementation of the project. The meteorological data includes temperature, humidity, wind speed and precipitation, and the soil data includes soil moisture and particle composition. Add data interaction items and hierarchical processing to the temperature and humidity data, calculate the temperature and humidity comfort index, and collect the project implementation effect, project investment and project implementation time as sand control project data;

[0094] In this embodiment, the meteorological data and soil data collected in the sand control project area before and after the implementation of the project refer to the meteorological data and soil data collected one year before the sand control project and one year after the implementation of the project;

[0095] Collect ambient temperature data of the project area from the meteorological station, record the average daily temperature and calculate the annual average temperature and standard deviation of the project area:

[0096]

[0097] Where, T avg is the annual average temperature, T std is the standard deviation of temperature, T i is the average daily temperature of the i-th day, n is the statistical day, and i is the index of the day;

[0098] Sub-index 1: Temperature stability index is calculated according to the following formula:

[0099]

[0100] In the formula, is the temperature stability index, T std is the standard deviation of temperature;

[0101] The relative humidity is collected by humidity sensors, the daily average humidity is recorded and the annual average humidity of the project area is calculated. Relative humidity greater than 60% is defined as wet:

[0102]

[0103] In the formula, H avg is the average annual humidity, H std is the standard deviation of humidity, H i is the average daily relative humidity on the i-th day, n is the statistical day, and i is the index of the day;

[0104] Sub-index 2: Humidity fluctuation index is calculated according to the following formula:

[0105]

[0106] In the formula, is the humidity fluctuation index, H std is the standard deviation of humidity;

[0107] According to the temperature and humidity interaction term, the temperature and humidity comfort index is calculated based on the following formula:

[0108]

[0109] In the formula, is the temperature and humidity comfort index, T avg is the average annual temperature, H avg is the annual average humidity, 22℃ and 50% are the comfortable temperature and humidity conditions for human body respectively;

[0110] Record the wind speed with an anemometer and calculate the average annual wind speed:

[0111]

[0112] Where V avg is the annual average wind speed, V i is the average daily wind speed on the i-th day, n is the statistical day, and i is the index of the day;

[0113] Collect precipitation data through rain gauges to count the total annual precipitation and number of days with precipitation:

[0114]

[0115] P days = count(P i >0)

[0116] Where P total is the total annual precipitation, P i is the precipitation on the i-th day, n is the statistical day, i is the index of the day, P days is the number of days with precipitation;

[0117] The wind intensity index is calculated based on the following formula:

[0118] Q wind =V avg *P days

[0119] In the formula, Q wind is the wind intensity index, V avg is the annual average wind speed, P days is the number of days with precipitation;

[0120] The specific logic for collecting soil moisture is as follows:

[0121] Use a soil moisture sensor to measure shallow, middle and deep soil moisture, and take the average as the soil moisture:

[0122]

[0123] In the formula, Sw is soil moisture, S w,shallow is the shallow soil moisture, S w,middle is the middle soil moisture, S w,deep It is the deep soil moisture; shallow soil generally refers to the soil 0-10 cm below the surface, middle soil usually refers to the soil 10-40 cm deep, and deep soil generally refers to the soil 40-100 cm or deeper;

[0124] Collect a certain amount of soil in the sand control project area as samples, and use soil sampling equipment to collect the respective proportions of sand, silt and clay to meet the following requirements:

[0125] S s +S p +S c =100%

[0126] Among them, S s is the proportion of sandy soil, S p is the proportion of silt, S c is the proportion of clay;

[0127] The purpose of collecting soil particle composition in the sand control project area is to fully understand the physical properties and stability of the soil, which determines the soil's ability to resist wind erosion, retain water and nutrients, and is also an important basis for judging the degree of desertification, selecting suitable vegetation and sand fixation measures. Sand represents coarse particles, which have good water permeability and aeration, but poor water and nutrient retention, and are easily affected by wind erosion when the proportion is too high; silt represents medium particles, which have certain water retention and nutrient adsorption capacity, but relatively weak wind erosion resistance; clay is fine particles, with the strongest water retention and wind erosion resistance, but too much may cause soil compaction, which is not conducive to vegetation growth. The analysis of particle composition can evaluate whether the soil structure in the project area has the conditions to support vegetation growth, and provide a scientific basis for optimizing sand barrier design and control technology. Through regular sampling, the effect of sand control projects can be dynamically monitored, the progress of soil improvement and ecological restoration can be quantified, and the control strategy can be adjusted to achieve more accurate and effective sand control and sand fixation goals.

[0128] The changes in vegetation coverage before and after the project implementation were analyzed through drone aerial photography, and the changes in vegetation coverage were used as the project implementation effect:

[0129] ΔM=M after -M before

[0130] In the formula, ΔM is the change in vegetation coverage, M after is the vegetation coverage rate after the project is implemented, and is the vegetation coverage rate before the project is implemented;

[0131] The total investment amount of the sand control project is obtained from the historical project financial data as the project investment, denoted as Cinput ;

[0132] The project implementation time is calculated based on the start and end time of the project completion record, denoted as T induration .

[0133] Step 1 provides high-quality basic data support for subsequent evaluation by comprehensively collecting multi-dimensional data including meteorological, soil and engineering data in the sand control project area before and after implementation. In particular, the detailed collection of indicators such as temperature, humidity, wind speed, precipitation, soil moisture and particle composition, as well as the calculation of the temperature and humidity comfort index, can fully reflect the dynamic change characteristics of the project area in terms of climate and soil. This all-round data collection method avoids the limitations of a single data source and can more accurately reflect the implementation effect of the desert highway sand control project and the response of the regional environment.

[0134] Compared with the existing technology, this scheme is more systematic and scientific in data collection. The existing technology for the collection of meteorological and soil data usually stays at the level of simple indicators or single data, while this scheme significantly improves the depth and scientificity of data analysis by adding interactive and derivative indicators such as temperature and humidity comfort index and particle uniformity index. These data can more intuitively reflect the changing characteristics of the ecological environment in the sand control project area, and provide a more comprehensive and accurate basic support for the evaluation of project benefits. In this scheme, the implementation of step 1 provides comprehensive and accurate data input for the subsequent evaluation model, which directly determines the scientificity and reliability of the evaluation results. Through detailed data collection and indicator calculation, high-quality input data can be provided for the variable weight matter-element extension model, ensuring that the model can dynamically capture the benefit performance of the project in different periods and under changes in the external environment. At the same time, the comprehensiveness and flexibility of step 1 also make the overall scheme highly applicable and popularizable, laying a solid foundation for the benefit evaluation of sand control projects in different regions.

[0135] Step 2: Calculate the particle uniformity index based on the particle composition of the soil, calculate the wind intensity index based on the wind speed and the number of days with precipitation, and calculate the engineering cost index, effect evaluation index and environmental impact index of the project to be evaluated by combining the dimensionless temperature and humidity comfort index, meteorological data, soil data and sand control engineering data;

[0136] In this embodiment, the particle uniformity index is calculated based on the formula:

[0137]

[0138] Where X is the particle uniformity index, S s is the proportion of sandy soil, S p is the proportion of silt, S c is the proportion of clay, μ s , μ pand μ c The ideal average of sand, silt and clay. According to the international soil classification standard, the following particle ratios are generally considered to be ideal for vegetation growth and sand control engineering effects: sand: about 40%-60%, silt: about 20%-40%, clay: about 10%-20%, σ s , σ p and σ c are the standard deviations of the ideal ranges for sand, silt, and clay, respectively; when X is close to 1, the particle composition is close to the ideal state; when X is close to 0, the particle composition deviates from the ideal state;

[0139] The calculation of the engineering cost index is based on the following formula:

[0140]

[0141] Among them, COST is the engineering cost index, T induration is the project implementation time, C input For project investment, C unit is the unit area cost, in units of 10,000 yuan / hectare, which is used to reflect the investment intensity of the project in different areas and is obtained according to the project plan. α is the time-related cost coefficient, which indicates the additional cost per unit time. ln is the natural logarithm, which is used to adjust the nonlinear relationship and smooth the data behavior.

[0142] T induratin *C unit This item means that long-term project implementation can reduce the pressure of capital investment per unit time, thereby reducing the cost intensity of the project. This does not mean that the actual investment will be reduced, but from the perspective of cost intensity per unit time, long-term implementation will have the effect of alleviating the investment burden; the project cost index in the formula reflects the investment intensity per unit time, not the total cost itself; α*T induration It is an additional cost item directly related to time to reflect the extra cost caused by longer time.

[0143] The calculation formula for the effect evaluation index is:

[0144]

[0145] In the formula, ECT is the effect evaluation index, ΔM is the change in vegetation coverage, Q wind is the wind intensity index, is the temperature and humidity comfort index, S w is soil moisture, S refis the reference value of soil moisture, ω1, ω2, ω3 and ω4 are preset proportional coefficients, and ω1>ω2>ω3>ω4>0; this is because the change in vegetation coverage is the most intuitive manifestation of the effect of sand control projects, and directly reflects the degree of improvement of the ecological environment by the project. Vegetation restoration can not only effectively fix sand and dust, but also improve the stability of the regional ecosystem. Therefore, in the effect evaluation, the change in vegetation coverage is the most important indicator, and its weight ω1 should also be the largest; the temperature and humidity comfort index reflects the comprehensive improvement of the regional climate environment after the implementation of the project. Although the main goal of the desert highway sand control project is to prevent wind and fix sand, improving regional climate conditions plays an important role in improving the actual benefits of the project, so its weight ω2 is second only to the change in vegetation coverage; the wind intensity index is a comprehensive indicator of wind speed and precipitation days in desert areas, reflecting the indirect impact of regional wind erosion on sand control effects. Although it is an important reference for engineering design and effect evaluation, as a background parameter of environmental conditions, its influence is more indirect, so the weight ω3 is lower than the vegetation coverage rate and temperature and humidity comfort index; the significance of soil moisture index is to evaluate the extent to which the project improves soil moisture conditions. However, although soil moisture is important, its impact is usually limited to local areas and changes slowly, and its intuitive reflection on the overall sand control effect is weak, so the weight ω4 is the lowest.

[0146] When ΔM increases, it means that the vegetation coverage rate after the project is implemented has increased. Vegetation can reduce wind erosion, fix sand, and reduce the harm of wind and sand invasion. Therefore, the ECT is larger. The temperature and humidity comfort index is a measure of the suitability of the temperature and humidity of the local area to the ecological environment and human body. When the index increases, it means that the temperature fluctuation in the area is reduced, the humidity is moderate, and the environment is more livable. Therefore, when When Q increases, ECT also increases; wind It reflects the wind speed in the area, which is directly related to the degree of wind erosion and desertification. The greater the wind speed, the stronger the wind and sand activity, and the more serious the desertification. wind When |S increases, ECT decreases accordingly; w -S ref | increases, which means that the degree of soil moisture deviation from the reference humidity increases, which is not conducive to the growth of vegetation and ecological restoration effects, and ECT will decrease accordingly; that is, ΔM, Positively correlated with ECT, Q wind 、|S w -S ref |Negatively correlated with ECT.

[0147] The environmental impact index is calculated based on the following formula:

[0148]

[0149] Where ENV is the environmental impact index, is the temperature stability index, is the humidity fluctuation index, ΔP adj is the adjusted precipitation change rate, X is the particle uniformity index, and X ideal is the ideal particle uniformity index, X ideal =1, is the preset scaling factor, and This is because the stability of temperature and humidity is the core indicator for measuring the overall stability and improvement of the environment, and is the key goal of desert control and ecological restoration. It comprehensively reflects the pros and cons of environmental stability, so its weight is Set to maximum; although precipitation change is an important environmental factor, it is usually the result of large-scale climate conditions rather than the direct result of sand control projects. Therefore, its importance is slightly lower than the stability of temperature and humidity. In addition, precipitation changes may have a large degree of randomness and may not fully reflect the direct environmental impact of the project in some cases. Therefore, the adjusted precipitation change rate ΔP adj Weight Second to The particle uniformity index reflects the uniformity of soil particle size distribution. Ideal particle uniformity means that the soil structure is more stable, which is conducive to soil moisture storage, wind erosion resistance and plant growth. However, compared with the stability of temperature and humidity and the change of precipitation, the significance of particle uniformity is more inclined to the local microscopic characteristics of the soil and has less impact on the overall environmental stability. Therefore, its weight lowest.

[0150] ΔP adj The calculation formula is:

[0151]

[0152] Where ΔP is the precipitation change rate, ΔP opt is the ideal precipitation change rate, [ΔP max , ΔP min ] is the reference value range of precipitation change rate;

[0153] The calculation formula of ΔP is:

[0154]

[0155] Where P total,after is the total annual precipitation after the project is implemented, P total,before It is the total annual precipitation before the project implementation.

[0156] ENV is a comprehensive evaluation index that reflects the overall impact of a project on the environment. The larger the value, the more significant the positive impact on the environment. Reflects the degree of fluctuation of regional temperature. The higher the value, the more stable the temperature, the smaller the temperature difference between day and night or the seasonal change, and the more livable the climate. When the humidity increases, ENV also increases; humidity fluctuation index Reflects the degree of fluctuation of regional humidity. The higher the value, the more stable the humidity is. It is not easy to cause drought or over-humidity due to precipitation or evaporation. When it increases, ENV also increases; ΔP adj Reflects the change in precipitation. After adjustment, it is used to reflect whether the environment is developing in a more suitable direction. If the precipitation change is closer to the ideal level, then ΔP adj tends to a larger value, that is, when ΔP adj As it increases, ENV also increases; when |XX ideal |When it increases, it means that the particle distribution deviates from the ideal state, which may lead to instability of sand or deterioration of soil structure, and ENV will decrease; that is, ΔP adj Positively correlated with ENV, |XX ideal |Negatively correlated with ENV.

[0157] Step 2 uses scientific calculation methods to transform complex and diverse data into multiple evaluation indicators with clear meanings, including engineering cost index, effect evaluation index and environmental impact index. These indicators have been dimensionless, eliminating the influence between different data dimensions, making them comparable and universal. At the same time, by constructing detailed indicators such as wind intensity index and particle uniformity index that reflect regional characteristics, the uniqueness of the desert highway sand control project is fully reflected, providing high-precision model input for subsequent evaluation.

[0158] In the prior art, a single dimension or a simple weighting method is usually used to evaluate the project benefits, which is easy to cause deviations in the evaluation results, especially in the comprehensive processing of multi-dimensional data. This scheme systematically constructs a multi-dimensional indicator system, which not only covers key dimensions such as project cost, ecological effect and environmental impact, but also improves the scientific nature of the evaluation by introducing dimensionless processing and interactive indicators. In addition, the establishment of wind intensity index and particle uniformity index makes up for the shortcomings of the prior art in insufficient analysis of environmental variables unique to desert areas, thereby more comprehensively reflecting the project benefits. The implementation of step 2 lays a scientific evaluation foundation for the overall scheme. By constructing a multi-dimensional, scientific and quantitative indicator system, the comprehensive benefit performance of desert highway sand control projects in economic, ecological and environmental dimensions can be fully reflected, thereby improving the accuracy and applicability of the evaluation model. At the same time, the dimensionless and dynamic adjustment characteristics of each indicator provide standardized and dynamic data input for the subsequent comprehensive evaluation based on the variable weight matter-element extension model, so that the overall scheme can more accurately capture the benefit change characteristics of the project at different time stages, and provide strong support for scientific decision-making and optimization and improvement.

[0159] Step 3: From the three dimensions of project cost, effect evaluation and environmental impact, a multi-dimensional evaluation index system for the benefits of desert highway sand control projects is constructed, and the time factor is introduced. The project benefits are evaluated based on the variable weight matter-element extension model, and the project benefits are divided into three levels, namely high efficiency, medium efficiency and low efficiency. According to the evaluation results, a quantitative evaluation is conducted on the project to be evaluated;

[0160] In this embodiment, an evaluation system is constructed and evaluated based on the variable weight matter-element extension model, and the specific logic is as follows:

[0161] The engineering cost dimension, effect evaluation dimension and environmental impact dimension are used as the main evaluation indicators of the desert highway sand control project benefits; among them, the engineering cost dimension corresponds to the engineering cost index COST, the effect evaluation dimension corresponds to the effect evaluation index ECT, and the environmental impact dimension corresponds to the environmental impact index ENV;

[0162] The project benefits are divided into three levels: high efficiency, medium efficiency, and low efficiency. The expression is as follows:

[0163] E k =(c k ,[a k ,b k ])

[0164] Where k is the index of the level, k∈{1,2,3}, E1, E2 and E3 represent high efficiency, medium efficiency and low efficiency respectively, c k is the reference center value of level k, usually determined by historical data or expert knowledge, [a k ,b k] is the classical domain range of level k, that is, the interval range of benefit value, which is determined based on historical data and expert knowledge;

[0165] The correlation between each dimension and the classical domain is calculated according to the following formula:

[0166]

[0167] K is the value of the association degree, which indicates the compatibility of the attribute value x with the classical domain. The attribute value x is the representative indicator of each dimension, including the engineering cost index COST, the effect evaluation index ECT and the environmental impact index ENV. K∈[0,1]. The closer K is to 1, the closer x is to the classical domain. [a,b] is the classical domain range of the level, and [c,d] is the node domain range, that is, the global upper and lower limits of the attribute value.

[0168] Introducing the time factor, the comprehensive benefit index is adjusted through dynamic weights:

[0169] The time factor f(t) is expressed as follows:

[0170]

[0171] Where f(t) represents the time factor, which is used to represent the progress ratio of the entire project implementation cycle at time t, and its value range is [0,1]; T induration is the project implementation time, t represents the cumulative time from the start of the project to time t, and 0≤t≤T induration ;

[0172]

[0173] Among them, Z total is the comprehensive benefit index, K j is the value of the association degree of the jth dimension, is the weight, j is the index of the dimension;

[0174]

[0175] This is a dynamic adjustment formula for weights, which is used to reflect the relative importance of different dimensions at different stages of a project. is the initial weight of the j-th dimension, β j is the weight change rate of the jth dimension, j is the index of the dimension;

[0176]

[0177] The comprehensive benefit index is compared with the preset threshold and divided into multiple levels according to the comparison results:

[0178] When Z totalWhen ≥0.8, it means that the project benefit evaluation is highly efficient, the project performs well in the three dimensions of economic cost, actual effect and environmental impact, and the comprehensive benefit index reaches the high efficiency standard;

[0179] When 0.5≤Z total When <0.8, it means that the project benefit evaluation is medium, and the project has certain effects in the three dimensions of economic cost, actual effect and environmental impact, but there is still room for improvement in some aspects;

[0180] When Z total When <0.5, it means that the project benefit evaluation is inefficient, and the project performs poorly in the three dimensions of economic cost, actual effect and environmental impact, and fails to achieve the expected goals.

[0181] Step 3 fully reflects the diversity and complexity of the benefits of desert highway sand control projects by constructing a multidimensional evaluation index system based on three dimensions: project cost, effect evaluation, and environmental impact. At the same time, the variable weight matter-element extension model is introduced to conduct quantitative analysis of benefit evaluation, so that the evaluation system has dynamic adjustment capabilities and can accurately reflect the changes in the importance of each dimension during the project implementation process. In addition, the evaluation results are divided into three levels: high efficiency, medium efficiency, and low efficiency, which is convenient for intuitively presenting the project benefit evaluation results and providing clear guidance for management and decision-making.

[0182] In the prior art, the evaluation of engineering benefits usually relies on a static and single-dimensional evaluation system, lacks a comprehensive consideration of the multi-dimensional impact of complex engineering, and is difficult to dynamically adjust weights to adapt to changes in time and environment. This solution not only realizes the comprehensive evaluation of multi-dimensional indicators by introducing a variable-weight matter-element extension model, but also optimizes the flexibility and adaptability of the evaluation through a dynamic weight adjustment mechanism, so that the evaluation results can more accurately reflect the comprehensive benefit performance of the project at different stages. Compared with the prior art, this method has significant improvements in scientificity and applicability. Step 3 is the core link of this solution. It effectively integrates the multi-dimensional indicators collected and calculated in the first two steps and establishes a comprehensive evaluation system with dynamic weight adjustment. Through the use of the variable-weight matter-element extension model, the objectivity and scientificity of the benefit evaluation are ensured, providing data basis and direction guidance for subsequent improvements and optimizations. At the same time, the hierarchical division of the benefit evaluation results facilitates project managers to quickly understand and apply them, making the entire solution more practical and decision-making support.

[0183] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0184] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0185] 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, and 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.

[0186] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for evaluating the benefits of desert highway sand control projects based on variable weight matter-element extension model, characterized in that: The specific steps include: Step 1: Collect meteorological data and soil data in the sand control project area before and after the implementation of the sand control project. The meteorological data includes temperature, humidity, wind speed and precipitation, and the soil data includes soil moisture and particle composition. Add data interaction items and hierarchical processing to the temperature and humidity data, calculate the temperature and humidity comfort index, and collect the project implementation effect, project investment and project implementation time as sand control project data; Step 2: Calculate the particle uniformity index based on the particle composition of the soil, calculate the wind intensity index based on the wind speed and the number of days with precipitation, and calculate the engineering cost index, effect evaluation index and environmental impact index of the project to be evaluated by combining the dimensionless temperature and humidity comfort index, meteorological data, soil data and sand control engineering data; Step 3: Construct a multi-dimensional evaluation index system for the benefits of desert highway sand control projects from the three dimensions of project cost, effect evaluation and environmental impact, introduce the time factor, evaluate the project benefits based on the variable weight matter-element extension model, and divide the benefits of sand control projects into three levels, namely high efficiency, medium efficiency and low efficiency. According to the evaluation results, conduct a quantitative evaluation of the sand control projects to be evaluated.

2. The method for evaluating the benefits of desert highway sand control projects based on a variable-weight matter-element extension model according to claim 1 is characterized by: Collecting meteorological data and soil data in the sand control project area before and after the implementation of the project refers to the meteorological data and soil data one year before the sand control project and one year after the implementation of the project. The soil data refers to the wind-blown sand data in the sand control project area; Collect ambient temperature data of the project area from the meteorological station, record the average daily temperature and calculate the annual average temperature and standard deviation of the project area: Where, T avg is the annual average temperature, T std is the standard deviation of temperature, T i is the average daily temperature of the i-th day, n is the statistical day, and i is the index of the day; Sub-index 1: Temperature stability index is calculated according to the following formula: In the formula, is the temperature stability index, T std is the standard deviation of temperature; The relative humidity is collected by humidity sensors, the daily average humidity is recorded and the annual average humidity of the project area is calculated. Relative humidity greater than 60% is defined as wet: In the formula, H avg is the average annual humidity, H std is the standard deviation of humidity, H i is the average daily relative humidity on the i-th day, n is the statistical day, and i is the index of the day; Sub-index 2: Humidity fluctuation index is calculated according to the following formula: In the formula, is the humidity fluctuation index, H std is the standard deviation of humidity; According to the temperature and humidity interaction term, the temperature and humidity comfort index is calculated based on the following formula: In the formula, is the temperature and humidity comfort index, T avg is the annual average temperature, H avg is the annual average humidity, 22℃ and 50% are the comfortable temperature and humidity conditions for human body respectively; Record the wind speed with an anemometer and calculate the average annual wind speed: Where V avg is the annual average wind speed, V i is the average daily wind speed on the i-th day, n is the statistical day, and i is the index of the day; Collect precipitation data through rain gauges to count the total annual precipitation and number of days with precipitation: P days =count(P i >0) Where P total is the total annual precipitation, P i is the precipitation on the i-th day, n is the statistical day, i is the index of the day, P days is the number of days with precipitation; The wind intensity index is calculated based on the following formula: Q wind =V avg *P days In the formula, Q wind is the wind intensity index, V avg is the annual average wind speed, P days is the number of days with precipitation; The specific logic for collecting soil moisture is as follows: Use a soil moisture sensor to measure shallow, middle and deep soil moisture, and take the average as the soil moisture: In the formula, S w is soil moisture, S w,shallow is the shallow soil moisture, S w,middle is the soil moisture in the middle layer, S w,deep is deep soil moisture; Collect a certain amount of soil in the sand control project area as samples, use soil sampling equipment to collect the respective proportions of sand, silt and clay, and meet the following requirements: S s +S p +S c =100% Among them, S s is the proportion of sandy soil, S p is the proportion of silt, S c is the proportion of clay; The changes in vegetation coverage before and after the project implementation were analyzed through drone aerial photography, and the changes in vegetation coverage were used as the project implementation effect: ΔM=M after -M before In the formula, ΔM is the change in vegetation coverage, M after is the vegetation coverage rate after the project is implemented, and is the vegetation coverage rate before the project is implemented; The total investment amount of the sand control project is obtained from the historical project financial data as the project investment, denoted as C input ; The project implementation time is calculated based on the start and end time of the project completion record, denoted as T induration .

3. The method for evaluating the benefits of desert highway sand control projects based on a variable-weight matter-element extension model according to claim 1 is characterized by: The particle uniformity index is calculated based on the formula: Where X is the particle uniformity index, S s is the proportion of sandy soil, S p is the proportion of silt, S c is the proportion of clay, μ s , μ p and μ c The ideal average value of sand, silt and clay is based on the international soil classification standard, σ s , σ p and σ c are the standard deviations of the ideal ranges for sand, silt, and clay, respectively; The calculation of the engineering cost index is based on the following formula: Among them, COST is the engineering cost index, T induration is the project implementation time, C input For project investment, C unit is the unit area cost, in units of 10,000 yuan / hectare, which is used to reflect the investment intensity of the project in different areas and is obtained according to the project plan. α is the time-related cost coefficient, which indicates the additional cost per unit time. ln is the natural logarithm, which is used to adjust the nonlinear relationship and smooth the data behavior. The calculation formula for the effect evaluation index is: In the formula, ECT is the effect evaluation index, ΔM is the change in vegetation coverage, Q wind is the wind intensity index, is the temperature and humidity comfort index, S w is soil moisture, S ref is the reference value of soil moisture, ω1, ω2, ω3 and ω4 are preset proportional coefficients, and ω1>ω2>ω3>ω4>0; The environmental impact index is calculated based on the following formula: Where ENV is the environmental impact index, is the temperature stability index, is the humidity fluctuation index, ΔP adj is the adjusted precipitation change rate, X is the particle uniformity index, and X ideal is the ideal particle uniformity index, X ideal =1, is the preset scaling factor, and ΔP adj The calculation formula is: Where ΔP is the precipitation change rate, ΔP opt is the ideal precipitation change rate, [ΔP max , ΔP min ] is the reference value range of precipitation change rate; The calculation formula of ΔP is: Where P total,after is the total annual precipitation after the project is implemented, P total,before It is the total annual precipitation before the project implementation.

4. The method for evaluating the benefits of desert highway sand control projects based on a variable-weight matter-element extension model according to claim 1 is characterized by: The evaluation system is constructed and evaluated based on the variable weight matter-element extension model. The specific logic is as follows: The engineering cost dimension, effect evaluation dimension and environmental impact dimension are used as the main evaluation indicators of the desert highway sand control project benefits; among them, the engineering cost dimension corresponds to the engineering cost index COST, the effect evaluation dimension corresponds to the effect evaluation index ECT, and the environmental impact dimension corresponds to the environmental impact index ENV; The project benefits are divided into three levels: high efficiency, medium efficiency, and low efficiency. The expression is as follows: E k =(c k ,[a k ,b k ]) Where k is the index of the level, k∈{1,2,3}, E1, E2 and E3 represent high efficiency, medium efficiency and low efficiency respectively, c k is the reference center value of level k, usually determined by historical data or expert knowledge, [a k ,b k ] is the classical domain range of level k, that is, the interval range of benefit value, which is determined based on historical data and expert knowledge; The correlation between each dimension and the classical domain is calculated according to the following formula: K is the value of the association degree, which indicates the compatibility of the attribute value x with the classical domain. The attribute value x is the representative indicator of each dimension, including the engineering cost index COST, the effect evaluation index ECT and the environmental impact index ENV. K∈[0,1]. The closer K is to 1, the closer x is to the classical domain. [a,b] is the classical domain range of the level, and [c,d] is the node domain range, that is, the global upper and lower limits of the attribute value.

5. The method for evaluating the benefits of desert highway sand control projects based on a variable-weight matter-element extension model according to claim 4 is characterized by: Introducing the time factor, the comprehensive benefit index is adjusted through dynamic weights: The time factor f(t) is expressed as follows: Where f(t) represents the time factor, which is used to represent the progress ratio of the entire project implementation cycle at time t, and its value range is [0,1]; T induration is the project implementation time, t represents the cumulative time from the start of the project to time t, and 0≤t≤T induration ; Among them, Z total is the comprehensive benefit index, K j is the value of the association degree of the jth dimension, is the weight, is the initial weight of the j-th dimension, β j is the weight change rate of the jth dimension, j is the index of the dimension; The comprehensive benefit index is compared with the preset threshold and divided into multiple levels according to the comparison results: When Z total When ≥0.8, it means that the project benefit evaluation is highly efficient, the project performs well in the three dimensions of economic cost, actual effect and environmental impact, and the comprehensive benefit index reaches the high efficiency standard; When 0.5≤Z total When <0.8, it means that the project benefit evaluation is medium, and the project has certain effects in the three dimensions of economic cost, actual effect and environmental impact, but there is still room for improvement in some aspects; When Z total When <0.5, it means that the project benefit evaluation is inefficient, and the project performs poorly in the three dimensions of economic cost, actual effect and environmental impact, and fails to achieve the expected goals.

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