457 results about "Analytic hierarchy process" patented technology

The invention discloses a load flow calculation and simulation control method and system for a digital twin power grid, and relates to the technical field of digital twin simulation control, and the method comprises the following steps: constructing a digital twin power grid model, and carrying out the dynamic topology optimization processing of the digital twin power grid model based on remote signaling credibility weighting; according to the optimized digital twin power grid model, identifying the power grid operation risk based on an integrated learning model; according to the risk identification result, generating a transfer path control strategy based on an analytic hierarchy process and a fuzzy comprehensive evaluation method; mapping the transfer path control strategy into a control action instruction set, and simulating execution and establishing a feedback correction mechanism on the digital twin power grid model; by generating the optimal path control strategy and performing control strategy analog simulation and self-adaptive feedback correction based on the digital twin power grid model, the problem of lack of intelligent path control strategy selection and simulation verification based on state dynamic identification in the prior art is solved.

The invention relates to the technical field of process optimization control, and discloses a silk-covered enameled winding process optimization control method and system based on intelligent analysis. The method comprises the steps that multi-area production parameters are collected in real time and preprocessed; constructing parameter and product quality mapping through principal component dimensionality reduction, grey correlation and support vector regression; training an Actor-Critic structure by using a depth deterministic strategy gradient network to obtain an adjustment strategy; a non-dominated sorting genetic algorithm is combined with analytic hierarchy process to carry out multi-objective optimization, and a control scheme for balancing mass, efficiency and energy consumption is realized. According to the application, on the basis of considering the complex coupling relationship among the process parameters, multi-objective dynamic balance optimization of product quality, production efficiency and energy consumption is realized, the process parameters can be adaptively adjusted according to the production state and the task demand, and the stability and the optimization degree of the silk-covered enameled winding production process are improved.

A fuzzy cloud-based risk assessment method for reservoir operation schemes, including: collecting basic data of target reservoirs; constructing optimal operation model of conventional reservoirs to obtain model calculation results; acquiring change process of operation characteristics during whole operating period according to model calculation results, and constructing multi-level reservoir multi-dimensional risk assessment index system; dividing different risk level intervals according to multi-level reservoir multi-dimensional risk assessment index system; obtaining large number of sample data xij of reservoir risk index under corresponding working conditions by multiple parallel calculations to conduct risk assessment; calculating cloud digital features of different indexes by inverse cloud generator; and weighting indexes in index layer and criterion layer by Analytic Hierarchy Process to obtain multi-dimensional risk assessment results. In order to promote sustainable development and utilization of water resources and enhance level of reservoir risk management, scientific evaluation of reservoir risk is conducted by comprehensively considering various uncertainties.

The invention relates to the technical field of risk analysis, in particular to a safety engineering comprehensive management system which comprises a geological parameter dynamic monitoring module, a risk threshold early warning module, a stability weight evaluation module and a risk comprehensive management and control module. According to the method, lithology data are extracted through a drilling profile to calculate the layer thickness sudden change rate and the strength attenuation rate, a lithology abnormal area is positioned through a variable coefficient method, lithology sudden change marks are analyzed through spatial clustering, a dynamic trend is captured through sliding window mean value comparison, and gradient amplitude and slope direction dispersion are calculated through a digital elevation model. Fusing the abnormal point density to generate a terrain instability index; establishing a multi-dimensional quantitative evaluation framework; carrying out fuzzy comprehensive evaluation and cross validation on the instability index and an engineering parameter trend; generating a dynamic priority sequence, carrying out stake number interval matching to construct a risk measure table, carrying out analytic hierarchy process dynamic resource allocation support drainage scheme, and carrying out real-time monitoring and prediction closed-loop iteration. And adaptively adjusting the control strategy.

The invention discloses a project performance evaluation and risk early warning method for multi-source heterogeneous scientific research data, and relates to the technical field of scientific research project management, and the method comprises the steps: collecting the multi-source heterogeneous scientific research data, cleaning, converting, filling missing values, and storing in a unified format; extracting performance and risk features, and fusing to obtain a fused feature set; combining an analytic hierarchy process, an entropy weight method and the like to construct a dynamic weight performance evaluation model; constructing a multi-modal risk early warning model by adopting multiple algorithms and optimizing a threshold value; collecting data in real time to update a feature set, and dynamically adjusting the model; and visually outputting a result, generating an improvement suggestion, and forming closed-loop feedback. According to the method, the multi-source data processing efficiency and evaluation accuracy are improved, the risk early warning timeliness and adaptability are enhanced, a management closed loop is formed, and the problems of difficult data integration, evaluation lagging, insufficient early warning and the like of a traditional method are solved.

The invention discloses a multi-dimensional collaborative AI training processor benchmark evaluation device and method. According to end-to-end performance evaluation, TTA and throughput indexes are obtained through a standardized training process; the operator support degree evaluation adopts a dynamic parameter generation technology to evaluate the speed-up ratio and the floating point performance utilization rate of calculation-intensive and memory-access-intensive operators; the energy consumption evaluation calculates a power consumption delay product based on steady-state power consumption monitoring. And finally, integrating multi-dimensional indexes through an analytic hierarchy process model and a fuzzy theory, realizing level mapping by adopting a four-section membership function, and finishing multi-level aggregation evaluation in combination with matrix operation. According to the method, three dimensions of performance, operator support degree and energy efficiency are creatively integrated, the problems of single evaluation index and high environment dependence of the heterogeneous AI processor are solved through automatic container deployment, dynamic parameter generation and steady-state power consumption monitoring technologies, and a comprehensive and quantifiable evaluation basis is provided for processor model selection.

The invention relates to a smart city planning monitoring system, which comprises a multi-source data acquisition module, a database construction and management module, a planning analysis and monitoring module, a communication cooperation module and an interactive decision support module, the database construction and management module is used for constructing and managing a database of urban planning and monitoring data, the planning analysis and monitoring module is used for planning scheme evaluation and progress tracking, the communication cooperation module is used for data communication and module cooperation, and the interactive decision support module is used for data interaction, monitoring visualization and decision support. According to the smart city planning monitoring system, a city planning multi-source data fusion algorithm based on kernel density analysis is put forward to fuse multi-source data, and a smart city planning monitoring algorithm based on analytic hierarchy process and fuzzy comprehensive evaluation is put forward to monitor and evaluate smart city planning.

The invention relates to a safety production equipment risk monitoring method and system, and belongs to the technical field of risk monitoring, and the method comprises the steps: obtaining historical operation data and real-time operation data of to-be-monitored safety production equipment; setting a dynamic threshold according to the historical operation data, predicting the range of the dynamic threshold according to preset target process operation data and the historical operation data through a bidirectional long-short-term memory network, and updating the range of the dynamic threshold in combination with the real-time operation data to obtain an updated dynamic threshold; the comprehensive risk index is calculated according to the updated dynamic threshold value and the real-time operation data through the analytic hierarchy process, the risk of the safety production equipment to be monitored is evaluated according to the comprehensive risk index, an evaluation result is obtained, dynamic monitoring and evaluation of the risk of the safety production equipment are achieved, and the safety production equipment risk evaluation efficiency is improved. The actual operation state of the equipment can be reflected more accurately, potential risks can be found in time, corresponding measures can be taken, and the operation safety and reliability of the equipment are improved.

The invention relates to the technical field of aircraft optimization, and discloses an expressway low-altitude aircraft optimization arrangement method, which comprises the following steps: constructing an evaluation index system, determining the comprehensive weight of each evaluation index by using an analytic hierarchy process and an entropy weight method, and identifying the importance of the evaluation indexes; constructing a low-altitude aircraft optimization arrangement model, and solving by utilizing a simulated annealing algorithm to obtain static optimal quantity configuration of the low-altitude aircrafts of the service site; dynamically adjusting the static optimal number configuration of the low-altitude aircrafts of the service site by using a social emotion resonance avoidance algorithm; and according to the final number configuration of the low-altitude aircrafts of the service site, combining the social emotion data to optimize the flight path of the low-altitude aircrafts. According to the method, various complex factors are comprehensively considered, efficient arrangement and path optimization of the low-altitude aircraft are achieved, investment of the low-altitude aircraft is more global and economical, and important technical support is provided for application of the low-altitude aircraft industry.

The invention provides a rock damage evaluation method and device, and the method comprises the following steps: carrying out a compression test on a rock sample until the rock sample is damaged; treating the damaged rock sample to obtain a multi-scale damage fractal dimension of the damaged rock sample; based on the multi-scale damage fractal dimension, calculating a weight coefficient of each scale fractal dimension to the damage of the rock sample through an analytic hierarchy process; constructing a multi-scale rock damage evolution fractal model based on the weight coefficient; and evaluating the damage degree of the rock to be measured based on the rock damage evolution fractal model. The defect that the rock damage degree is determined from a single scale is overcome, rock damage can be more comprehensively and accurately quantified, long-term rock damage and stability evolution are effectively predicted, and reference is provided for comprehensively and accurately representing the rock damage degree and long-term evolution.

The invention provides a computer big data storage control system, and relates to the technical field of computers, and the system comprises a data evaluation module which is used for comprehensively calculating the real-time popularity of data, and the real-time popularity is obtained through the comprehensive calculation of the data access frequency and the access duration; performing quantitative evaluation on the real-time popularity of the data in combination with a multi-dimensional factor to obtain a value evaluation value of the data; analyzing the system resource information of the storage device on the computer to obtain a resource analysis result; and the intelligent contract execution module is used for carrying out comprehensive analysis and judgment on the real-time popularity, the value evaluation value and the system resource analysis result of the data so as to trigger adjustment of a storage strategy. According to the method, the real-time popularity model is constructed, the analytic hierarchy process is combined to achieve multi-dimensional value evaluation, the intelligent contract dynamically adjusts the storage strategy according to the evaluation result and the resource state, the data value and the storage medium are accurately matched, the problems that a traditional system is extensive in evaluation and rigid in strategy are solved, and efficient and accurate scheduling of storage resources is achieved.

The invention discloses an alpine grassland no-tillage restoration suitability evaluation method based on a 3S technology, and particularly relates to the technical field of data processing. Through the combination of multi-temporal satellite images and global positioning system data, the spatial dynamic change of the frozen soil layer of the alpine grassland and the long-term influence of the spatial dynamic change on vegetation growth are accurately obtained, and a frozen soil layer depth and distribution dynamic monitoring model is constructed based on multi-source remote sensing data and historical weather and soil temperature and humidity data. Analyzing the influence of freezing and thawing alternation on plant root growth; establishing a vegetation recovery potential index and a soil moisture supply index by combining the vegetation coverage and the dynamic change of the frozen soil layer, and generating a suitability partition map through a GIS spatial analysis and analytic hierarchy process; through field sampling and long-term vegetation growth monitoring data verification and model optimization, the accuracy of no-tillage restoration suitability evaluation is remarkably improved, and scientific and accurate decision support is provided for ecological restoration of alpine grassland.

The invention discloses a data and knowledge dual-drive wheel set multi-parameter comprehensive state evaluation method and system, and belongs to the technical field of railway vehicle maintenance. The method comprises the following steps: firstly, constructing a mapping relation between geometric parameters and dynamic performance indexes through sampling and dynamic simulation, and carrying out global sensitivity analysis to screen key dynamic performance indexes; secondly, determining subjective and objective weights of the indexes in combination with an analytic hierarchy process and an entropy weight method, and introducing a dynamic optimization model based on a Bellman equation to generate a final combined weight; then, constructing a multi-dimensional state space division model by applying adaptive kernel density estimation and fuzzy C-means clustering, and determining the probability density and membership function of each index under different health levels; and finally, performing simulation prediction on the target wheel set, inputting a predicted value into the state space model, fusing a dynamic combination weight and a D-S evidence theory, calculating a comprehensive health index, and outputting a grading result, so that the health state of the wheel set can be accurately and efficiently evaluated.

The invention relates to the technical field of fire control management, and discloses an intelligent fire control door management method and system based on the Internet of Things, and the method comprises the following steps: S1, collecting multi-environment data of a fire control door; s2, performing standardization processing to obtain multi-environment data in a unified format, and establishing a feature matrix; s3, determining the importance degree of each item of data in the feature matrix to obtain a comprehensive weight; s4, constructing a membership function, and outputting a fire risk level; s5, determining the fire stage of the current environment; s6, selecting a final risk response strategy through a fuzzy game method; and S7, controlling the action of a fire exit door according to the selected final risk response strategy. According to the method, the information entropy and the analytic hierarchy process algorithm are combined to determine the importance degree of the multi-environment data and calculate the comprehensive weight of the fire risk, so that the assessment is more objective and comprehensive, overlarge deviation of a single model is avoided, and the problems of bias and poor applicability of assessment are solved.

The invention belongs to the technical field of virtual power plants, and particularly relates to a virtual power plant resource aggregation method for a dynamic peak regulation demand of a power grid, which comprises the following steps of: acquiring multi-source data, preprocessing the multi-source data, and then verifying the data quality; aiming at different resource types including temperature control load, energy storage and charging piles, respectively constructing refined models, setting constraint conditions of the refined models, and solving a resource operation feasible region by applying multi-dimensional space mapping and linear programming; establishing a target function and a constraint condition by taking the lowest cost and the minimum energy abandoning as targets; solving a target function by using a dung beetle optimization algorithm, and screening an optimal resource aggregation scheme by using an entropy weight method; and based on the optimal resource aggregation scheme, dividing peak, valley and normal periods, constructing a four-dimensional peak regulation index, determining a weight by using an analytic hierarchy process, and screening an optimal resource combination in each period to execute scheduling. The method can guarantee the accuracy and high efficiency of the peak regulation demand response of the power grid, and assists in improving the stability of the power system and the renewable energy consumption level.

The invention provides a multi-source information fusion mining overlying strata high separation layer water disaster prediction evaluation method, which comprises the following steps of: constructing a coal mining, overlying strata structure index, strata space occurrence and cretaceous system aquifer prediction index system according to related data of hydrogeology, engineering geology and coal mining in a research area; through the separation water disaster multi-source information fusion prediction evaluation model of the subjective-objective weight combination of the analytic hierarchy process, the entropy weight method and the CRTIC method, accurate prediction evaluation of the separation water disaster is realized, the error of the traditional separation water disaster prediction result is reduced, the water disaster threat of the stope face is greatly reduced, a guarantee is provided for safe mining of a coal mine, and the economic benefit of the coal mine is improved. And coal mine water disaster prevention and control measures and safety production are effectively guided.

The invention discloses a multi-scale convolution self-adaptive partial discharge fault type identification method based on characteristic parameters and moment characteristics, and relates to the field of discharge fault identification, and the method comprises the steps: obtaining a partial discharge phase three-dimensional statistical graph, and extracting a distribution relation to generate a statistical parameter graph; extracting statistical parameters based on the statistical parameter atlas, introducing preposed partial discharge occurrence judgment parameters to obtain statistical characteristic parameters, training a neural network, and constructing a statistical characteristic parameter model according to a training result; processing the statistical parameter atlas by using a multi-scale convolution technology to construct a moment characteristic model, and respectively deploying the statistical characteristic parameter model and the moment characteristic model to a partial discharge online monitoring and diagnosis platform; and obtaining a partial discharge fault type identification result based on the deployment result, analyzing the partial discharge fault type identification result by using an analytic hierarchy process, and evaluating the health state of the equipment. According to the method, the partial discharge fault type identification rate is improved, the anti-interference capability is improved, and the partial discharge type can be effectively and accurately identified.

The invention relates to an intelligent operation and maintenance method for power transmission network equipment based on digital twin dynamic coupling, and belongs to the technical field of intelligent detection of power systems. The method comprises the following steps: dynamically splitting a power grid panoramic frame into an equipment physical entity layer and a static background environment layer, and generating a panoramic display picture through cloud and edge parallel rendering and a terminal HMD picture synthesis technology; establishing real-time bidirectional mapping between the physical entity and the virtual twinborn body of the power grid equipment, and synchronizing sensor data to the digital twinborn model; adopting an improved permutation entropy algorithm to extract equipment operation characteristic quantity, and dynamically distributing rendering pipeline resources in combination with a Bayesian network diagnosis model and an analytic hierarchy process evaluation system; and constructing an equipment state quality index, and quantitatively evaluating the health degree of the current equipment and predicting the future degradation trend by dynamically comparing the characteristic parameters with an expected value and combining health factor correction and a time sequence nonlinear prediction model. According to the invention, full-life-cycle efficient management and control of the operation state of the power grid equipment can be realized.

The invention relates to the technical field of urban flood prediction and risk assessment, and discloses an urban flood prediction and risk assessment method based on multivariate data fusion, and the method comprises the steps: collecting data through a plurality of data sources; preprocessing the collected data, and performing dimensionality reduction and fusion on the preprocessed data; a flood prediction model based on the random forest is constructed, and the flood occurrence probability is predicted; constructing a risk assessment index system; determining the weight of each index by using an analytic hierarchy process and a random forest method, and constructing a comprehensive risk assessment model; dynamic assessment and visual display of flood risks are realized by combining real-time monitoring data with a geographic information system technology; the multi-source uncertainty is quantized and processed by adopting a Bayesian method and a Monte Carlo simulation technology. According to the method, multiple data sources can be integrated, the flood risk is comprehensively evaluated, the multi-source uncertainty is effectively processed, and the reliability and stability of the evaluation result are improved.

The invention provides a tunnel health monitoring method based on distributed optical fiber sensing, and relates to the technical field of tunnel engineering health monitoring, and the method comprises the steps: carrying out the risk assessment of a tunnel through employing an analytic hierarchy process, setting a differential optical fiber laying scheme according to an assessment result, and laying distributed optical fiber sensors on the inner surface of a tunnel lining; the method comprises the following steps: acquiring original strain data through Brillouin optical time domain analysis, and preprocessing by using a moving average filtering algorithm; building a finite element model based on actual physical data of the tunnel, inverting strain data into full-field node displacement, and obtaining a complete strain tensor of a finite element unit; performing unit-level strain state evaluation, time sequence trend risk evaluation and spatial clustering risk evaluation to obtain a comprehensive risk value; and setting a dynamic evaluation threshold interval, and completing tunnel accurate region health evaluation. Accurate monitoring and risk assessment of the tunnel health state are achieved, and the method can be widely applied to the field of safety monitoring of highway and railway tunnels.

The invention belongs to the technical field of unmanned aerial vehicle power inspection, and discloses a multi-module cooperative control method for an unmanned aerial vehicle power inspection system based on a visual language model. The precise mapping of the natural language instruction and the inspection task is realized; a user does not need to depend on professional coordinate input, and target equipment and key parts can be positioned only through daily inspection verbal skills; meanwhile, a priority evaluation model and a task snapshot mechanism constructed by an analytic hierarchy process support rapid insertion and progress recovery of temporary high-priority tasks, so that the emergency troubleshooting requirement of sudden equipment exceptions can be met, orderly promotion of conventional inspection can be guaranteed, and intelligence and flexibility of substation inspection are improved; the cooperative bus built based on the time-sensitive network realizes efficient data synchronization of a plurality of modules such as a fusion model, navigation, visual acquisition and the like.

The invention discloses a regulation and control quota distribution method and system fusing subjective and objective multi-dimensional features. The method comprises the following steps: acquiring electrical load data, historical response behavior data and subjective response intention information of a user; firstly, a Ward system is used for clustering, users are clustered according to active power, then a primary clustering center is used as an initial clustering center of secondary clustering, FCM clustering is carried out, and a typical load curve of the users is described based on a secondary clustering method; load prediction is carried out based on an NARX neural network, a predicted load curve is compared with a typical load curve, and adjustable potential is calculated; constructing a DR feature data set; and the DR feature data set is fused with an entropy weight method and an analytic hierarchy process to obtain a combined weight, a fuzzy relation matrix is constructed, a user comprehensive score is quantified, and a comprehensive response potential score of the user is formed.

The invention particularly relates to a meteorological equipment health degree assessment method based on regression and fuzzy comprehensive analysis. The method comprises the following steps: constructing a meteorological equipment health degree assessment index system; the method comprises the steps of collecting multi-source data of meteorological equipment, and completing data preprocessing through missing value filling and abnormal value correction; performing feature extraction on the multi-level indexes by adopting regression analysis, screening out core parameters strongly related to the health degree, and quantifying priorities; combining an analytic hierarchy process, integrating expert experience and feature importance results, constructing a hierarchical judgment matrix, and calculating the dynamic weight of each hierarchy index; and based on a fuzzy comprehensive evaluation method, establishing a multi-dimensional comment set and a membership function for the quantitative index and the qualitative index, fusing the weight matrix and the membership data, and outputting a quantitative score of the health state of the meteorological equipment. According to the method, the accuracy of health assessment of the meteorological equipment in severe environments such as extremely cold environments can be realized, and reliable technical support is provided for intelligent operation and maintenance of the meteorological equipment.

The invention relates to the technical field of cigarette supervision, in particular to a cigarette retail store supervision route planning method, which solves the problems of data missing and heterogeneity through data cleaning and standardization processing, and provides high-quality basic data for subsequent analysis. Due to the application of the analytic hierarchy process, scientific quantification of multi-dimensional indexes is realized, and the reliability of an evaluation result is improved; the improved ant colony algorithm is combined with pheromone concentration parameter adjustment, so that the routing inspection path planning efficiency and pertinence are optimized; key problems can be quickly positioned by introducing an anomaly detection algorithm, and the timeliness and accuracy of supervision are enhanced; a clustering analysis algorithm reveals a potential rule of a regional problem by grouping abnormal stores and calculating spatial distribution density; the thermodynamic diagram visualization technology presents the distribution of supervision key areas in a visual mode, and provides clear information support for decision makers; dynamic supervision and trend analysis are achieved through interactive function design, and scientificity and flexibility of supervision decision making are further improved.

The invention relates to the technical field of underground space development, and provides a coastal bedrock type city underground space development geological suitability evaluation method comprising the following steps: analyzing key geological problems of land area and sea area underground space development, and extracting related geological factors; basic geological data are collected and classified, a geological suitability evaluation index system is constructed, and geological evaluation units are divided; subjective and objective weights are determined based on an analytic hierarchy process and an entropy weight method, and an optimal comprehensive weight is obtained through game theory combination weighting; modeling based on a grey correlation analysis method, and calculating and grading suitability scores of the evaluation units; and integrating evaluation results, and generating an underground space development geological suitability partition map of land-sea overall planning. According to the scheme, the underground space development pattern is optimized, comprehensive utilization of land and ocean resources is promoted, and safe, efficient and sustainable development and utilization of the coastal city underground space are powerfully supported.

The invention provides an unmanned ship cluster confrontation game method and system based on situation information. The survival ability and combat efficiency of an unmanned ship cluster in a complex confrontation environment are improved. The method comprises the following steps: firstly, collecting threat data of the enemy unmanned surface vehicle and quantitatively evaluating the threat degree, collecting performance data of the our unmanned surface vehicle and quantitatively evaluating the adaptability, and fusing the threat data and the performance data by using an analytic hierarchy process to obtain a comprehensive situation evaluation result; then, sub-task targets are determined according to the comprehensive situation assessment and the overall task target, and tasks are reasonably allocated to the unmanned surface vehicles by adopting an improved Hungary algorithm; and finally, performing local path planning on each unmanned ship by adopting an improved A * algorithm in combination with a local environment, and performing global path planning based on multi-agent collaborative consideration of cluster collaborative requirements and enemy threat distribution. According to the method, comprehensive situation assessment, reasonable task planning and scientific path planning are realized, and the unmanned ship cluster confrontation capability is improved.

A sponge facility layout optimization method based on adaptability evaluation comprises the following steps: constructing a layered index system, integrating soil substrate characteristics, natural conditions and region positioning factors, and dynamically distributing index weights by using an analytic hierarchy process; quantifying the effect variation of the sponge facility improvement measures on each subitem index and grading; based on the three-dimensional mapping relation between the index current situation level and the measure effect direction, generating an adaptability scoring matrix through an expert scoring mechanism; an adaptive priority coefficient is calculated in combination with weight weighting, and quantifiable decision parameters are generated after linear standardization processing. According to the method, spatial heterogeneity response, cost-benefit collaborative optimization and multi-objective decision are creatively fused, the dependence of a traditional evaluation method on fixed indexes is broken through, and scientific grading recommendation of facility improvement measures is realized; and quantifiable and extensible technical support is provided for differentiated layout of sponge facilities in an urban complex environment and optimal configuration under resource constraints.

The invention provides an urban rail transit station development intensity multi-objective optimization method in a TOD mode, and relates to the technical field of urban planning and intelligent transportation, and the method comprises the steps: analyzing the spatial relation between various types of land and urban function nodes according to the data after standardization processing, and carrying out the location value evaluation; constructing a development intensity evaluation model according to the location value evaluation, calculating the initial average plot ratio of each type of land, and deducing an initial development intensity parameter in combination with the current situation data; establishing a development intensity optimization target system according to a TOD planning principle, performing iterative optimization on the initial development intensity parameters by adopting a multi-target genetic algorithm, and outputting an optimal solution set; and carrying out comparative analysis on the optimal solution set and a current planning index, and obtaining a plot ratio index in combination with a regional development planning requirement. According to the method, a technical framework of subjective and objective collaborative optimization can be constructed by fusing GIS spatial analysis, an analytic hierarchy process and a non-dominated sorting genetic algorithm.

The invention discloses a power distribution network self-healing method for improving power supply reliability, and the method comprises the following steps: S1, collecting fault information and an operation state, constructing a fault description matrix P, and carrying out the fault positioning based on the fault description matrix P; s2, after fault positioning, judging the position of the node relative to a fault position by taking whether fault current is detected at the node as a criterion, and recording the distance x between the node and a fault branch; s3, after a fault branch and a fault node are determined, fault recovery of a non-fault area is carried out based on the distance x between the node and the fault point; s4, constructing multiple objective functions and constraint conditions, determining the weight of each objective function by adopting an analytic hierarchy process to obtain a total objective function F, and optimizing the objective functions based on an ant colony algorithm to obtain an optimal power distribution network reconstruction scheme; the power failure time can be shortened, the power supply reliability is improved, and the power grid operation reliability is improved.

The invention provides a method and a system for processing content measurement data of multi-index components in folium cortex eucommiae, and relates to the technical field of traditional Chinese medicine quality control and data analysis crossing. The method comprises the following steps: aligning standardized content data of a current batch with data of a corresponding batch in a predicted content data set; obtaining an actual detection value and predicted value pairing sequence of each index; the deviation ratio of each data pair in the actual detection value and predicted value pairing sequence of each index is calculated, and a deviation ratio analysis result is formed; and based on the deviation ratio analysis result, in combination with a pre-stored legal standard threshold and historical batch data, performing comprehensive evaluation through principal component analysis and analytic hierarchy process to obtain a multi-dimensional quality comprehensive evaluation value including specification conformity, component proportional relation and process stability. According to the method, an integrated data processing system is constructed, so that the intelligence and precision level of multi-index quality evaluation of the folium cortex eucommiae is improved.