33 results about "Indicator value" patented technology

The invention discloses a high and steep slope ecological restoration effect evaluation method and device, and the method comprises the steps: obtaining daily meteorological data, daily vegetation growth state data and daily soil moisture content data in a high and steep slope ecological restoration region, the vegetation growth state data comprises an unmanned aerial vehicle NDVI image shot by the unmanned aerial vehicle in the high and steep slope ecological restoration area; determining an initial restoration index value based on the daily vegetation growth state data and the daily soil moisture content data; determining a correction coefficient based on the daily meteorological data; and correcting the initial repair index value based on the correction coefficient to obtain a target repair index value. According to the invention, on one hand, the meteorological data is combined to evaluate the ecological restoration, and on the other hand, the unmanned aerial vehicle NDVI image shot by the unmanned aerial vehicle in the high and steep slope ecological restoration area is utilized to evaluate the ecological restoration, so that the evaluation accuracy of the high and steep slope ecological restoration effect can be improved.

The invention belongs to the field of agricultural technology and ecological monitoring, and particularly discloses a Hainan island wild tea tree growth model construction method and system.The method comprises the steps that firstly, a microenvironment competition factor is obtained by quantifying a local competition index based on diameter-level distribution in a fixed quadrat around a target tea tree; selecting a preset cubic function growth mechanism model to calculate a theoretical growth index value according to a vegetation vertical zone corresponding to the altitude of the tea tree; then fusing the local competition index, the theoretical growth index value, the altitude, the canopy density and the growth environment type to construct a feature vector so as to train a gradient lifting decision tree model, and establishing a multi-factor growth state prediction model; and finally, predicting the growth state of an unknown tea tree by using the model. According to the method, the ecological mechanism and machine learning are effectively fused, the growth prediction precision is remarkably improved, and a quantitative basis is provided for precise conservation.

The invention discloses a mine ecological restoration effect evaluation method based on a life cycle evaluation model, and relates to the technical field of ecological restoration effect evaluation, and the method comprises the steps: defining a mine restoration effect evaluation target, an evaluation range and a function unit, and carrying out the evaluation of the mine ecological restoration effect based on the evaluation range and the function unit; collecting resource consumption data, environmental emission data and ecological state data in the restoration process, and constructing a dynamic life cycle list database; and carrying out characterization calculation on data in the dynamic life cycle list database to obtain a preliminary environmental influence index value, establishing a recognition rule of a life cycle evaluation model based on sensitivity analysis of the soil microbial community in the mine restoration area to heavy metal stress, and recognizing the ecological toxicity potential of fresh water from the preliminary environmental influence index value. According to the method, the decision support report is generated visually, and multi-dimensional, dynamic and accurate evaluation of the mine restoration effect is realized.

The invention relates to a biodiversity hot spot area threat condition monitoring method and device and electronic equipment, and the method comprises the steps: obtaining reference period data and monitoring period data of a biodiversity hot spot area, and obtaining forest loss layer data based on the reference period data and the monitoring period data; calculating an ecological pressure index value based on the forest loss layer data, and performing normalization processing on the ecological pressure index value to obtain a standardized ecological pressure index value result; and based on the standardized ecological pressure index value result, performing weighting according to the weight to obtain an ecological threat index, performing threat level division according to the ecological threat index, and outputting a biodiversity hot spot area threat condition result, thereby solving the problems of poor biodiversity hot spot area threat condition monitoring timeliness and poor biodiversity hot spot area threat condition monitoring accuracy in related technologies. And the timeliness and the accuracy of monitoring the threat condition of the biodiversity hot spot region are improved.

The invention relates to the technical field of ecological assessment, and discloses a coastal wetland ecosystem condition assessment method and device, a medium and a product, different smooth regression functions are obtained through double generalized additive model processing, and the influence of an environmental single factor on vegetation and the cooperative influence of the environment and the vegetation on benthic organisms are accurately quantified. Furthermore, the index value is determined by taking historical data as a reference and combining a nonlinear rule of a smooth function, so that subjective weighting deviation is avoided. Furthermore, the weight is calculated based on the association between the real-time index value and the biological index, so that human subjective intervention is avoided, and the weight is ensured to reflect the actual contribution of the index to the ecological system. Meanwhile, the influence of single data deviation is reduced by using the multi-tree integration characteristic of the random forest model, so that the weight result is more stable. Furthermore, the complex ecosystem condition of the coastal wetland can be comprehensively evaluated in combination with the index value and the weight, the biodiversity is protected, and the stability of the ecosystem is maintained.

The invention relates to the technical field of city planning recommendation, and provides a coastal zone city ecological space protection strategy recommendation method and system, and the method comprises the steps: dividing a gradient zone ecological space; constructing an index system corresponding to the state-interaction-toughness framework, performing multi-dimensional quantification to obtain each evaluation index, acquiring region detection data for each gradient zone ecological space, and calculating an index value; and setting different fusion weights for the gradient zone ecological spaces according to the ecological characteristics, and for each gradient zone ecological space, fusing each evaluation index of the index system to obtain an ecological importance comprehensive evaluation index so as to generate an ecological space protection recommendation strategy. According to the method, the authenticity and the interpretation capability of importance identification of the ecological space are improved by constructing a multi-dimensional evaluation framework of states, interaction and toughness; differentiation index fusion weights are set, evaluation distortion caused by unified indexes and unified weights is avoided, and pertinence and space suitability of protection strategy recommendation are improved.

The present application relates to the technical field of intelligent diagnosis, in particular to a kind of estuary habitat degradation intelligent diagnosis method, comprising S1: obtaining the in-situ time series monitoring data of estuary key section;S2: extract tidal characteristic phase, carry out tidal phase normalization processing, generate standard ecological dataset;S3: standard ecological dataset and the biodiversity index obtained based on environmental DNA technology are spatiotemporal fusion;The response relationship between the ecological parameters in different tidal characteristic phase interval and biodiversity index is modeled, and the response lag feature and coupling strength of each ecological parameter are extracted;Multi-dimensional local dynamic baseline is constructed;S4: time lag compensation is carried out to each dimension index;Based on the index value after time lag compensation, the standardization deviation degree of each dimension index is calculated, and the comprehensive deviation index is obtained by weighted integration;S5: identify the dominant type leading to habitat degradation.The present application improves the accuracy and efficiency of ecological monitoring and management.

The embodiment of the invention provides an ecological safety risk comprehensive assessment early warning method and system and a computer readable medium, and can solve the technical problems of low ecological safety risk assessment precision and poor timeliness in related technologies. The method comprises the following steps: determining at least one ecological risk type and risk factor of a region to be pre-warned; obtaining an ecological risk type result based on the ecological risk index value and the importance scoring result corresponding to the ecological risk type; according to the sensitivity index, the restoring force index and the pressure index, obtaining an ecological risk comprehensive index; calculating a correlation result between the risk factor and the ecological risk type result to obtain a risk threshold value; and according to the ecological risk comprehensive index, based on a risk threshold, determining a target risk level corresponding to the ecological risk type. According to the method, the change early warning of the macroscopic ecological security pattern is realized, a microscopic high-risk unit can be positioned, and the refined management and control and adaptive decision of the ecological security pattern are systematically supported, so that the ecological security risk evaluation precision is improved.

The application discloses a soil salinization discrimination method based on combination optimization of geochemical parameters, and belongs to the field of soil salinization monitoring. The method comprises the following steps: collecting soil samples in a research area and measuring the content of multi-dimensional geochemical elements; removing outliers and performing standardization processing on the geochemical data; dividing the samples by using a clustering algorithm; screening characteristic elements which are significantly related to salinization and have low collinearity in each division to form an optimal parameter combination; establishing a partial least squares regression model based on the combination, constructing a salinization response function and calculating a discrimination index value; training and optimizing the index by using a machine learning model to obtain a discrimination model; and finally, realizing rapid discrimination of the degree of soil salinization by using the model. The application considers regional spatial heterogeneity and multi-element coupling characteristics, has the advantages of high discrimination accuracy and good stability, and is suitable for regional scale salinization investigation, grading evaluation and early warning.

A method and system for identifying the critical transformation risk of an ecosystem based on multi-source remote sensing vegetation indicators are disclosed. The method includes: S10: acquiring and preprocessing vegetation time-series data of the study area; S20: performing signal separation based on multiple time-series decomposition methods; S30: selecting the best separation result from the multiple time-series decomposition methods; S40: calculating statistical indicators for early warning of critical transformation; S50: performing linear trend analysis on the time series of early warning indicators for each pixel, and calculating the slope b of the indicator value changing over time using the least squares method; S60: directly summing the trend values ​​b of each indicator obtained in step S50 to obtain the pixel-scale consistency score CS; S70: constructing a multi-indicator covariance matrix; calculating the standard deviation MS of the Mahalanobis distance time series; S80: constructing a critical transformation risk index R, and judging the critical transformation risk of the ecosystem in the study area based on R.

The application discloses a mine ecological restoration effect evaluation method based on a life cycle assessment model, relates to the technical field of ecological restoration effect evaluation, and comprises the following steps: defining the target, evaluation range and functional unit of mine restoration effect evaluation; collecting resource consumption data, environmental emission data and ecological state data in the restoration process based on the evaluation range and functional unit, and constructing a dynamic life cycle inventory database; performing characteristic calculation on the data in the dynamic life cycle inventory database to obtain preliminary environmental impact index values; based on the sensitivity analysis of soil microbial communities in the mine restoration area to heavy metal stress, establishing identification rules of the life cycle assessment model, and identifying the freshwater ecological toxicity potential from the preliminary environmental impact index values; and generating a decision support report through visualization, so that multi-dimensional and dynamic accurate evaluation of the mine restoration effect is realized.

To appropriately evaluate an environmental load regarding an evaluation target product to be taken in a biological system or an ecosystem.SOLUTION: An information processing device holds information for inferring dynamic changes in states of a biological system or an ecosystem that takes an evaluation target product in, a life cycle model that indicates the evaluation target product and a used item other than the evaluation target product used in each state, environmental load information that indicates an environmental load of each of the evaluation target product and the used item, and index information that indicates an index value related to quality of life of the biological system or the ecosystem affected by the evaluation target product in each state, infers the dynamic changes in the states based on the life cycle model, calculates an environmental load and an index value for the entire period of the inferred dynamic changes by referring to the environmental load information and the index information, and corrects the calculated environmental load based on the calculated index value.SELECTED DRAWING: Figure 1

The application discloses a kind of fish fattening field suitable ecological flow and system of deducing method, including the following steps: constructing the index system of hydraulic habitat of fattening field for quantifying habitat patch spatial heterogeneity, the hydraulic habitat index value of different flow conditions is analyzed and calculated using two-dimensional hydrodynamic model in the study water area, the flow corresponding to the most suitable hydraulic habitat index value of the fish habitat studied is selected as the suitable ecological flow of fattening field.The present application not only considers the target organism but also considers other organisms in the river, and is more conducive to creating suitable flow conditions for multiple species coexistence, and has certain scientific significance and reference value for fish fattening field protection and ecological restoration.

The invention belongs to the technical field of aquaculture, and particularly relates to a screening method of microbial indicator species for river crab earth pond seedling water quality grades and application of the screening method. Physical and chemical index data of water bodies of different river crab breeding earth ponds in different development periods of river crabs are obtained, physical and chemical indexes with violent data changes serve as water quality indexes, and water quality grades are divided; high-throughput sequencing is carried out, and microorganism species and composition of different river crab breeding earth ponds in different water quality grade groups in water bodies of the river crabs in different development periods are obtained and are relatively rich; calculating an indicator value by adopting an indicator value analysis method, and carrying out statistical test by utilizing multiple replacement test to obtain primarily screened microbial indicator species; and carrying out correlation analysis on the primarily screened microbial indicator species and the obtained physicochemical index data, and screening out the final microbial indicator species for evaluating the water quality grade of the river crab earth pond breeding water body. The method has the advantages of being strict in logic, scientific in system and reliable in result, and valuable reference is provided for dividing the water quality grade of the river crab earth pond breeding water body.

The invention provides a deep learning-based slope vegetation protection effect evaluation method and device fusing multi-modal features and a storage medium, and relates to the field of slope protection evaluation, and the method comprises the steps: obtaining a structure index, a time sequence index and an image index of a target slope; constructing an initial structure vector, an index value sequence, an index position sequence and an index time interval sequence; performing three-color channel combination on the land cover image and the root system vertical distribution pattern image to obtain an initial image tensor; inputting the initial structure vector, the index value sequence, the index position sequence, the index time interval sequence and the initial image tensor into a slope index scoring model to obtain a stability score and an ecological function score; and obtaining a slope vegetation protection effect evaluation index based on the stability score and the ecological function score, wherein the higher the evaluation index value is, the better the slope vegetation protection effect is. By adopting the evaluation method provided by the invention, rapid and efficient slope vegetation protection effect evaluation can be realized.

The invention relates to a multi-variable evaluation method. The method comprises the following steps: 1) performing correlation analysis on a plurality of indexes of a to-be-evaluated object, and removing indexes without significant correlation to obtain retention indexes of the to-be-evaluated object; 2) if an index numerical value with a negative change trend exists in the retention indexes, performing reciprocal valuing on the index numerical value to obtain a positive same-trend numerical value of the to-be-evaluated object index; 3) converting a forward same-trend numerical value of the to-be-evaluated object index into an index conversion numerical value in a range of [0, 1]; 4) calculating the average of the sum of the deviations of the n index conversion values of the to-be-evaluated objects and the minimum values of the corresponding index conversion values in all the to-be-evaluated objects to obtain evaluation values for evaluating the to-be-evaluated objects; and 5) the evaluation value of the to-be-evaluated object is compared with 1, and the closer the evaluation value is to 1, the better the comprehensive performance of the to-be-evaluated object is.

The invention provides a spatial function partitioning method, device and equipment for ecological product value conversion, and relates to the technical field of spatial governance, and the method comprises the steps: extracting a drainage basin unit in a target region, and carrying out the spatial coupling correlation of the drainage basin unit and village boundary vector data corresponding to the target region, so as to form a basic spatial function unit; determining a multi-dimensional feature index value of the basic spatial function unit relative to each ecological product value conversion type, and performing spatial weighted stacking processing on the multi-dimensional feature index value by using a dynamically adjustable current index weight value to obtain a type evaluation index; and determining a target ecological product value conversion type to which the basic space function unit belongs according to the type evaluation index. According to the method, natural ecological integrity and planning implementation conductivity are considered in the aspect of applicable objects, comprehensive judgment of ecological product value conversion types is realized in the aspect of recognition means, and scientificity and comprehensiveness of partition type recognition are improved.

The present application provides a method and system for dynamic monitoring of the ecological quality of a marine protected area based on a GEE platform, comprising: S1: calling remote sensing data within a first preset time period and a preset sea area through the GEE platform, extracting ecological indicators from the remote sensing data to form an ecological monitoring indicator set, and constructing a time series of ecological indicators by pixel point unit; S2: constructing a fluctuation characteristic vector of the pixel point for the ecological indicator time series corresponding to each pixel point, and inputting the fluctuation characteristic vector of each pixel point into a clustering algorithm to divide the sensitivity level area of ​​the preset sea area; S3: constructing a regional indicator weight adjustment model, calculating the degree of influence of each ecological indicator in each sensitive level area on the ecological quality, and generating a regional adaptive weight table; S4: extracting the ecological indicator corresponding to each pixel point and generating a fusion index value of the pixel point according to a preset fusion method, and inputting the fusion index value into a fuzzy neural network model to map the pixel point to an ecological quality level.

The present invention discloses a non-destructive measurement method for the morphological indexes of Masson pine seedlings, comprising: collecting and correcting Masson pine images; reconstructing the collected images into 3D point clouds and pre-processing the point clouds; creating a dataset for semantic segmentation of the Masson pine point clouds, calculating class balance weights for different classes in the dataset; constructing a densely weighted semantic segmentation network model; assigning the class balance weights to the loss function of the model; training the densely weighted semantic segmentation network model using the dataset; obtaining the original skeleton points of the stem based on the points of the Masson pine stem in the Masson pine point cloud segmented by the densely weighted semantic segmentation network model, and refining and extracting the skeleton points of the stem; and extracting the morphological index values of the Masson pine to be measured based on the refined skeleton points of the stem. The present invention can accurately measure the morphological indexes of Masson pine seedlings, no longer relying on manual labor and specialized instrument measurement equipment, and reducing measurement costs and difficulty.

The invention discloses a fish school suitability index weight determination method and system, electronic equipment and a computer readable storage medium, and belongs to the technical field of water conservancy and hydropower development fish habitat protection. The method comprises the following steps: step 1, acquiring a hierarchical structure diagram of fish school suitability indexes; step 2, constructing a judgment matrix of each layer in the hierarchical structure diagram; 3, according to the judgment matrix of each layer, determining the initial weight of each element in each layer to the previous layer; and step 4, determining the weight of each index value in the fish school suitability index based on the initial weight of each element in each level to the previous level. Weighted values are accurately given to different indexes to reflect the relative importance degrees of the indexes, so that the accuracy and effectiveness of the fish school habitat evaluation result are ensured.

The invention relates to the technical field of nitrogen emission prediction, and discloses a DNDC-based machine learning feature extraction method and system, and the method comprises the steps: firstly extracting climate, soil and farmland management original features from agricultural ecosystem data; calculating an intermediate process variable related to the nitrogen cycle based on DNDC; training a machine learning reference model according to the original features to obtain a reference performance index value; combining each intermediate variable with the original features to construct an extended data set and train a model, and calculating an extended performance index value; by comparing the two performance indexes, screening intermediate variables which significantly improve the prediction effect to form an important variable set; and finally, combining the original features and the important variable set to train a machine learning model to obtain a high-precision nitrogen emission prediction model. According to the method, through fusion of a mechanism model and machine learning, dual improvement of prediction precision and interpretability is realized.

The present invention discloses a method and system for environmental monitoring and phenological correlation processing based on GEE. By obtaining environmental factors of the area to be studied, using Landsat 8 remote sensing data on the GEE platform for environmental monitoring according to the environmental factors to obtain spatio-temporal maps of the environmental factors, determining the temporal soil-adjusted vegetation phenology index from the maximum vegetation index and the minimum vegetation index, taking the temporal soil-adjusted vegetation phenology index as the phenological measurement value for phenological correlation analysis, analyzing the phenological correlation between the phenological measurement value and the index value corresponding to the surface environmental variables based on the support vector regression algorithm, using remote sensing data in GEE to monitor environmental changes and correlate them with phenological data, it is possible to identify the peaks and valleys of each parameter in the environmental factors, revealing a significant correlation between TSPI and environmental factors, improving the efficiency of diverse analysis and processing of environmental monitoring and phenological correlation, and enhancing the accuracy of phenological correlation assessment.

The invention discloses a rapid, low-loss and effective red tilapia cold stress evaluation system and evaluation method, and belongs to the technical field of aquaculture, the evaluation system comprises an index layer, a method layer and an application layer, the index layer comprises a behavior index, a body color index, a blood index and a tail fin pigment cell index; according to the method layer, a control group and a monitoring group are set, index values are measured respectively, the measured value of the control group serves as a standard value, and the differentiation degree of the monitoring group and the control group is judged through an evaluation model. The application layer is used for regulating and controlling a breeding strategy according to the differentiation degree of the monitoring group and the control group; according to the method, a four-dimensional quantitative evaluation system is constructed, and a grading early warning mechanism for the red tilapia breeding state is realized through a differentiation degree value algorithm; according to the method, the state of the tilapia can be pre-judged, so that a feeder can timely adjust a breeding strategy, and the death problem caused by cold stress or acute cold stress in the breeding process is reduced to the maximum extent.

The application discloses a kind of urban river network aquatic habitat quality driving factor identification methods, method includes: according to the rainfall data, air temperature data, elevation data set, land use data, soil data, runoff measured data, tidal data, riverbed data, water level measured data and river network connection node data are constructed hydrological model and hydrodynamic model;According to hydrological model and hydrodynamic model obtain hydrological hydrodynamic coupling model and hydrodynamic factor;According to the area of each grid unit of the region to be identified, the suitability index of hydrodynamic factor and the preset factor weight, the response index value is obtained by orthogonal test under several influence factors;According to the variance ratio statistics corresponding to the change value of response index value and influence factor, the influence factor with variance ratio statistics greater than the preset significance level is used as the aquatic habitat quality driving factor of the region to be identified. By implementing the application, the identification efficiency is improved while the cost is reduced.

A method of generating a health assessment of an asset based on one or more index values. The method includes receiving, by a first computer system, a first set of data including environmental data and a second set of data including operational data, calculating localized environmental data from the first set of data and the second set of data, generating one or more index values based on the localized environmental data, receiving, by the second computer system, the one or more indicator values and a third set of data including operational data of the asset, performing a health assessment of the asset using an analytical model based on the one or more indicator values and the third set of data to estimate a health of the asset, determining a future health or condition of the asset, and determining a health of the asset. And outputting a suggested action to maintain the asset.

The invention provides an uncertainty analysis method for surface ecological parameter measurement and calculation. The method comprises the following steps: acquiring an observation value of a target index for a target area; sampling is carried out from prior probability distribution of measurement and calculation factors contained in the target index measurement and calculation model, a plurality of candidate prior parameter combinations are obtained, the measurement and calculation factors comprise model input variables and error parameters, and the model input variables comprise prior surface ecological parameters; the multiple candidate prior parameter combinations are input into a target index measurement and calculation model, respective index measurement and calculation results of the multiple candidate prior parameter combinations are output, and the index measurement and calculation results comprise measurement and calculation values of the target index values; according to the measured value of the target index and the observed value of the target index, a target prior parameter combination is selected from the multiple candidate prior parameter combinations, and the target prior parameter combination comprises target prior surface ecological parameters; and according to the probability distribution determined based on the target prior surface ecological parameters, calculating the uncertainty for the surface ecological parameters.

The invention belongs to the technical field of water pollution biological monitoring, and discloses a water pollution early warning system and method based on non-intrusive corbicula fluminea behavior quantitative analysis, and the method comprises the following steps: carrying out image acquisition on multi-temporal behavior data of corbicula fluminea in a target pollution area; extracting a short-term sensitive index and a long-term stable index from the multi-temporal behavior data, and calculating index values of the short-term sensitive index and the long-term stable index; and determining the pollution level of the target pollution area by comparing the index value with an early warning threshold value. Specifically, the short-term sensitive index comprises the escape diffusion rate of the corbicula fluminea in a first preset time, and the long-term stable index comprises the diffusion area ratio and the digging rate of the corbicula fluminea in a second preset time; the early warning threshold value comprises a basic threshold value and a grading threshold value. In conclusion, water environment ecotoxicity assessment is realized based on quantitative analysis of corbicula fluminea behaviors, and effective technical support can be provided for health monitoring of a fresh water ecosystem.

The present invention discloses a collaborative method and system for water resources - ecological environment - economic society in a water network system. The marginal distributions of rainfall and evapotranspiration are fitted and a joint distribution is constructed. Massive scenarios are randomly sampled and input into a pre - constructed machine learning model to obtain the water resource quantity. Historical population and historical GDP data of the study area are collected to construct an economic and social volume prediction model and an economic and social volume prediction sample. A multi - objective optimization model is constructed to calculate the collaborative indicators of water resources - ecological environment - economic society. A system dynamics model is constructed and its model parameters are calibrated to calculate the values of the collaborative indicators of water resources - ecological environment - economic society. The collaborative indicators of water resources - ecological environment - economic society are dimensionally reduced and the corresponding indicator values are calculated, and a regulation plan is constructed to screen out the optimal optimization plan. The present invention improves the collaborative operation efficiency of the water conservancy model, realizes the comprehensive simulation of the water conservancy system, enhances the intelligent level of water network scheduling, and realizes the deep interactive integration of the physical water network and the digital water network.

The invention provides an estuary water ecology monitoring method based on diatom indication species identification and environmental response. The estuary water ecology monitoring method comprises the following steps: sampling a monitored estuary to obtain water ecology monitoring data including water environment factors and diatom population data; diatom indicator species are identified by adopting a biological indicator value method; acquiring time sequence data of the same diatom indicator species in the sedimentary column by adopting a sedimentary chronology method; obtaining a mutation point of the time sequence of the diatom indicator species through MK inspection; a random forest model between water environment factors and diatom indication species is trained; setting water environment scene data to be input into the random model, obtaining an abnormal scene in which the predicted data of the diatom indication species exceeds the mutation point, and obtaining a water environment factor threshold according to the abnormal scene. The problems that in the prior art, indication species cannot be recognized by quantifying the relation between diatom population and environmental factors, and mutation points of ecological abnormality are difficult to recognize by obtaining the historical evolution law of the indication species, so that the pertinence of a monitoring result is weak are solved.

The application discloses a kind of geogrids to enhance the performance of comprehensive evaluation method of macadam bed, including determining the performance of several evaluation indexes for evaluating geogrid to enhance the effect of macadam bed;Obtain the value of each evaluation index of several different geogrids to be evaluated;Each evaluation index value is preprocessed, and each evaluation index value after preprocessing is normalized;Based on each evaluation index value after normalization, the weight of each evaluation index is calculated using entropy weight method;The optimal evaluation sample comprising each evaluation index is constructed;Based on optimal evaluation sample, the comprehensive correlation degree of each geogrid to be evaluated is calculated using grey correlation method;The comprehensive correlation degree of each geogrid to be evaluated is substituted into the preset judging rule, and the comprehensive evaluation result is obtained.The application is used to solve the problem that the performance of geogrid to enhance the macadam bed cannot be effectively evaluated in the prior art, and the performance of geogrid to enhance the macadam bed is realized to carry out comprehensive evaluation of the purpose of progress.