808 results about "Analytical hierarchy process method" patented technology

The invention discloses an information security adaptive protection method and system based on artificial intelligence, and relates to the field of security protection, and the method comprises the steps: dynamically collecting multi-dimensional asset data through distributed nodes, carrying out the edge calculation preprocessing, and extracting features through a deep learning model; carrying out threat identification by fusing LSTM time sequence analysis, an isolated forest and a multi-modal AI detection engine of a knowledge graph; outputting a risk level based on an improved analytic hierarchy process and a fuzzy evaluation model; the AI strategy engine combines the risk level and the business scene to generate an optimal protection strategy, and continuous optimization is carried out through reinforcement learning; a standardized instruction is linked with safety equipment to execute protection, and interception effect closed-loop optimization is fed back in real time; a whole process log is stored through a block chain, and an attack evidence chain is generated through an AI traceability model. The method has the advantages that the information security protection capability is comprehensively improved through hierarchical data acquisition, multi-modal threat detection, scientific situation evaluation, dynamic generation of an optimization protection strategy and combination of block chain evidence storage and AI traceability.

The invention discloses an ecological restoration effect evaluation and simulation system after polluted soil restoration, and relates to the technical field of soil restoration, and the system comprises a soil feature generation module which generates an ecological feature data set; the ecological restoration evaluation module is used for establishing a multi-dimensional evaluation model by using an analytic hierarchy process and a fuzzy comprehensive evaluation method based on the ecological characteristic data set, and generating an ecological restoration effect index; the dynamic simulation prediction module is used for constructing an ecological restoration dynamic simulation model and simulating the evolution trend of a soil ecological system under different environment conditions; and the restoration strategy optimization module is used for generating a targeted ecological restoration optimization scheme by combining a preset restoration strategy library according to the ecological restoration effect index and the dynamic simulation prediction result. According to the method, a closed-loop system integrating multi-source data acquisition and processing, multi-dimensional evaluation, dynamic simulation prediction and stepped strategy optimization is constructed, and accurate evaluation of the ecological restoration effect after contaminated soil restoration and scientific optimization of the restoration strategy are achieved.

The invention discloses a primary equipment state monitoring method and system in a new energy power system, and the method comprises the following steps: deploying a multi-mode sensor array on primary equipment, and synchronously collecting a voltage signal, a current signal, a temperature signal, a vibration signal and an environment parameter; inputting the collected data into an edge computing node for preprocessing to obtain a multi-modal signal sequence; variational mode decomposition is carried out to form a multi-dimensional feature vector; inputting a long-short-term memory neural network model containing an attention mechanism, performing training and reasoning by using an AdamW optimizer and a cosine annealing learning rate strategy, and outputting the health degree of equipment; determining the weight of each monitoring index based on an analytic hierarchy process, and dividing the equipment into a plurality of state grades; the fault probability is obtained through fuzzy Petri net reasoning, and a corresponding early warning mechanism is triggered according to a preset threshold value. According to the invention, through multi-dimensional data fusion and intelligent analysis, the accuracy and real-time performance of state monitoring are significantly improved.

The invention belongs to the technical field of display design evaluation, and particularly relates to an exhibition display layout design effect analysis and evaluation method, which comprises the following steps of: constructing a dynamic spatial topology network by collecting audience moving tracks, exhibit information and spatial structure data in real time; the problem of insufficient attention on space utilization influenced by dynamic factors such as human traffic fluctuation is solved. And dynamic changes in the space are converted into quantifiable network nodes and connection relationships, so that the space utilization state is changed from static design to dynamic monitoring, accurate capture of the real-time use condition of the exhibition space is realized, a comprehensive and real-time data basis is provided for subsequent analysis, and the real-time monitoring of the exhibition space is realized. Meanwhile, the dynamic space topology network is analyzed by means of spatial-temporal feature fusion to determine the edge weight and the exhibition area correlation degree, the spatial efficiency index and the dynamic line rationality index are generated in combination with an analytic hierarchy process and multi-dimensional analysis, and the defect that a space utilization rate core evaluation index is not established in the prior art is overcome.

The invention discloses a road line selection design scheme decision-making method based on multi-source fusion. The method comprises the following steps: collecting multi-source data of a road planning area, performing standardized preprocessing, identifying ground features through an improved target detection model, and extracting features; fusing multi-dimensional data to construct a constraint function aiming at cost, ecology and compliance, and determining a weight by using an analytic hierarchy process; and performing staged optimization on three-dimensional line selection based on deep reinforcement learning to generate candidate schemes, and determining an optimal scheme through comprehensive score and curvature comparison selection. The method solves the problems that traditional line selection depends on manpower, is low in efficiency and is one-sided in decision, improves the scientificity, economy and driving safety of a scheme, and is suitable for a road line selection design scene.

The invention provides an emergency resource intelligent scheduling optimization method and system based on large model analysis, and relates to the technical field of emergency resource scheduling. The method comprises the steps of collecting emergency event data and environment data; extracting emergency event features and environment features, constructing a prediction model based on a long short-term memory network, and obtaining a required emergency resource list; constructing an emergency resource evaluation model based on an analytic hierarchy process, and obtaining priority scores of the required emergency resources; constructing a multi-objective optimization model, and solving the multi-objective optimization model by using a particle swarm algorithm to generate a scheduling scheme; and constructing a decision function, and solving by using a genetic algorithm to obtain a scheduling decision. According to the method, through accurate prediction, scientific evaluation, multi-objective optimization and decision in combination with priority, the accuracy and efficiency of emergency resource scheduling and the resource utilization efficiency can be remarkably improved, powerful support is provided for emergency management work, and the method has important practical significance and application value.

The invention discloses a method and a system for evaluating the reliability of a contact network system under an icing galloping condition. The method comprises the following steps: collecting icing galloping data of the overhead line system in real time, and carrying out load conversion and statistics on parts of the overhead line system in icing galloping by adopting a rain flow counting method; the reliability of parts under the icing galloping condition is calculated through the Miner cumulative damage theory, and weight distribution of the overhead line system is conducted through an analytic hierarchy process; based on the reliability and the weight distribution result of each part under the icing galloping condition, evaluating the reliability of the overhead line system of the data acquisition anchor section until the evaluation task is finished; the method and the system provided by the invention are suitable for evaluating the operation reliability of the contact network system in the icing galloping section, can provide support for operation and maintenance of the contact network system after icing galloping occurs, and have wide application prospects.

The invention specifically relates to an intelligent water affair dynamic supervision method and platform based on digital twinning, and relates to the technical field of intelligent water affair supervision. Risk early warning and situation deduction; emergency decision making and dispatching command; and post-treatment evaluation and knowledge precipitation. According to the method, a comprehensive and scientific risk quantification system is constructed through a combined weighting mechanism of multi-source data fusion, an analytic hierarchy process and an entropy weight method, and dynamic and accurate description of risks of each section of pipeline and each node of a pipe network is achieved in combination with a real-time working condition correction coefficient and a second-level updating mechanism; and grading accurate early warning triggered by a dynamic threshold value is matched with risk situation deduction of a simulation model, so that the influence range and the development trend of risks such as pipe explosion and water quality pollution can be pre-judged in advance.

The invention discloses a self-adaptive evaluation method and system for the running state of a contact network. The method comprises the following steps: constructing a contact network operation state evaluation index system, and obtaining time sequence detection data of each evaluation index; dynamically calculating the length of an adaptive window at the current evaluation moment, and extracting a nearest data subset matched with the length of the adaptive window from the time sequence detection data; using an improved CRITIC method to calculate and obtain a first objective weight vector; updating the gain coefficient vector, and calculating a second objective weight vector; combining the second objective weight vector with a subjective weight vector determined by an analytic hierarchy process by adopting a combined weight method to generate a final combined weight vector, and evaluating the running state of the overhead line system at the current evaluation moment until the evaluation task is finished; according to the method and the system, the accuracy and the timeliness of state evaluation of the overhead line system are effectively improved.

The invention relates to a multi-master election method and device based on an OpenHarmony soft bus, and the method comprises the steps: constructing six efficiency indexes according to the networking characteristics of the soft bus; operating system kernel state extraction: increasing a subsystem in an operating system layer, expanding system capability, obtaining index data of each device in a network in real time, storing the index data in a distributed database, and extracting required data from the distributed database by a multi-main election component to calculate and lift the device; performing analytic hierarchy process index weight construction and election formula derivation: establishing an efficiency index score system through an analytic hierarchy process, and calculating the weight of each index at the level to which the index belongs; and after the weights are determined, performing corresponding fuzzy judgment on each index by using a fuzzy comprehensive judgment method from the bottom-layer index, and finally obtaining a judgment score. According to the invention, the problem that the traditional open-source soft bus solves the problem that the single-center networking survivability of the traditional soft bus is insufficient is solved.

The invention discloses a low-carbon transformation method, system and device for a building air conditioning system. The objective of the invention is to solve the problems of static model, single target, one-sided evaluation and non-standardized process in the existing reconstruction technology. According to the method, building multi-dimensional data are collected; constructing a building energy consumption prediction physical simulation model coupled with a user behavior prediction model based on machine learning to dynamically reflect a real operation condition; a multi-dimensional objective function is defined, and a Pareto optimal transformation scheme set is generated; constructing an evaluation model based on an analytic hierarchy process and a fuzzy comprehensive evaluation method, and calculating a comprehensive evaluation value of each scheme; and selecting an optimal scheme according to the comprehensive evaluation value, and generating a detailed implementation report. The method can scientifically and efficiently determine the global optimal transformation strategy considering energy conservation, carbon reduction, comfort and economy, and significantly improves the scientificity and comprehensive benefits of building transformation decision.

The invention discloses a rail transit multi-network integration method based on a digital trunking technology, relates to the technical field of communication, and aims to solve the problem that a traditional narrowband trunking system cannot meet the requirements of voice and data comprehensive bearing and vehicle-ground large-bandwidth service real-time transmission. The method comprises the following steps: constructing a time division duplex long-term evolution broadband digital trunking unified bearing platform; an intermediate media access control layer fusion architecture is deployed, and seamless mobility management of the heterogeneous network is realized through unified authentication and multi-link aggregation; an intelligent vertical switching algorithm based on prediction and multi-criterion decision is introduced, a bidirectional long-short-term memory network model is utilized to predict a network state trend, and an improved entropy weight method and an analytic hierarchy process are combined to dynamically select an optimal access network according to service requirements. According to the invention, the network operation efficiency and the user experience can be obviously improved, and high reliability and high service quality of the rail transit communication system are ensured.

The invention discloses an intelligent archive information security protection method and system, and belongs to the technical field of information security protection. The method is used for solving the technical problem that the reliability and interpretability of an algorithm for archive information security protection in an existing scheme cannot be actively supervised and optimized. Initial weight distribution of sensitive levels is realized through an analytic hierarchy process, the Bayesian network quantifies the influence degree of real-time risk factors, weights are dynamically adjusted in combination with time attenuation factors, finally, a multi-dimensional archive information security risk assessment model capable of being dynamically optimized is constructed, an explicit logic basis is provided through rule reasoning, and an archive information security risk assessment model is established. A machine learning model quantifies a risk probability and explains key features, multi-source information is fused through a D-S evidence theory, finally, a decision path is tracked through a visual tree diagram, and multi-dimensional improvement of risk identification accuracy-decision transparency-system adaptability is realized through adaptive parameter adjustment and closed-loop optimization of an abnormal response strategy.

The invention discloses a privacy protection effect evaluation method and system, and the method comprises the steps: carrying out the hierarchical analysis of a privacy protection effect evaluation index system, defining the definition and calculation boundaries of four first-level dimensions, i.e., data features, compliance, availability and safety, and subordinate second-level indexes, carrying out the adaptation of a calculation algorithm for different types of indexes, and carrying out the weighted integration of the second-level indexes through employing an analytic hierarchy process, thereby achieving the evaluation of the privacy protection effect. Multi-dimensional quantitative evaluation is realized; an index association rule base and a matrix are constructed through static analysis and dynamic mining, and linkage analysis is achieved; determining an index fluctuation reference according to scene characteristics and historical data, converting user demands into a variation amplitude of a fluctuation reference unit, and realizing index dynamic linkage updating based on an incidence matrix; and finally, the optimization rule is verified through simulation testing and historical data backtracking, and a dynamically adaptive and self-iterative optimization relation rule system is formed, so that the limitation of traditional evaluation is broken through, a scientific basis is provided for privacy protection strategy optimization, and the privacy governance efficiency is improved.

The invention provides a rainstorm lightning disaster risk early warning method and system based on an analytic hierarchy process, and the method comprises the steps: obtaining historical thunderstorm frequency data and thunderstorm movement path data of a target region, and analyzing and determining the sensitivity levels of different regions in thunderstorm activities; the lightning stroke risk assessment model is decomposed into a target layer, a criterion layer and a scheme layer by using an analytic hierarchy process; according to historical data including lightning stroke historical data, thunderstorm historical data and disaster damage historical data, performing pairwise comparison on each factor of the criterion layer, and constructing a judgment matrix; acquiring spatial position information and characteristics of different types of disaster-bearing bodies, performing overlay analysis according to spatial positions of the disaster-bearing bodies and the lightning drop point probability distribution map, calculating lightning stroke probability values of areas where the disaster-bearing bodies are located, and generating a disaster-bearing body risk level distribution map.

The invention discloses a self-adaptive brushless motor control method and system, and relates to the field of intelligent control, and the method comprises the steps: collecting the original data of the operation state of a motor through a sensor group, and carrying out the preprocessing; time-varying parameter identification is completed through combination of an extended Kalman filtering algorithm and a radial basis function neural network, an evaluation index system is constructed based on an analytic hierarchy process to obtain a comprehensive evaluation value, and a related trend is predicted through a long and short-term memory neural network; constructing a multi-modal control strategy library, determining an adaptive strategy, optimizing core parameters by using an improved particle swarm optimization algorithm, generating a control instruction, and outputting a corresponding current through a power driving module; and monitoring motor parameters in real time, comparing with a control target value, calculating deviation, correcting an identification result, adjusting a strategy threshold value, and updating and optimizing an objective function. The method has the advantages that by accurately sensing the state of the motor, dynamically adapting the control strategy and optimizing parameters in real time, it is ensured that the motor stably and efficiently operates under the complex working condition, and the characteristics of energy conservation and long service life are achieved.

The invention provides a mining area vegetation reconstruction method based on vegetation classification and division. The method relates to the technical field of ecological environment restoration, and comprises the following steps: S1, acquiring mining area environment data by adopting a mode of combining remote sensing images, unmanned aerial vehicle aerial photography and ground sampling, performing spatial interpolation, normalization and filtering preprocessing on the environment data, and outputting a mining area ecological factor database; s2, on the basis of the ecological factor data, constructing a multi-index evaluation model by combining an analytic hierarchy process with clustering analysis to perform vegetation type division on the mining area, and generating partition templates with different ecological functions; and S3, constructing a plant phenological growth prediction model based on years of phenological observation data and weather forecast information. According to the mining area vegetation reconstruction method based on vegetation classification and division, precise planting and spatial layout are completed, the vegetation survival rate, biomass production and community diversity are remarkably improved, and the strict requirements of mining area ecological reconstruction for diversity and adaptability are met.

The invention discloses a land value evaluation method and system based on multi-source heterogeneous data fusion, and relates to the technical field of land economic evaluation. The invention discloses a land value evaluation method and system based on multi-source heterogeneous data fusion. The method comprises four steps of multi-source data acquisition and preprocessing, standardized evaluation index quantification, index weighted fusion and value calculation, and value distribution diagram generation and output. Firstly, four types of data of background status, planning, market feedback and social perception are acquired and preprocessed; secondly, constructing a hierarchical index system to quantify indexes; determining a weight through an analytic hierarchy process and calculating a land value index according to a preset formula; and finally generating a value distribution diagram in a thermodynamic diagram form. The method realizes standardization, high efficiency and visualization of land value evaluation, can be applied to the fields of city updating, land market monitoring, government planning decision making and the like, and provides scientific support for related decision making.

The invention relates to a heterogeneous AI computing virtualization architecture and slice enhancement method and system, and the method comprises the steps: evaluating the demands of an AI task for GPU resources through an analytic hierarchy process, and dividing the GPU resources into ultrafine-grained slice units according to an optimization model; predicting a resource demand through an ARIMA model, allocating slice resources through a minimum error sum of squares algorithm, and generating a resource allocation scheme; the method comprises the following steps: dividing a GPU into a plurality of independent hardware isolation units based on a resource allocation scheme and GPU hardware topology, and generating a hardware unit configuration table; establishing an isolation mechanism based on the identity information and the ACL, and establishing a software isolation environment; the method comprises the following steps: dividing network partitions, configuring a firewall rule to control network access authority, monitoring network traffic in real time, processing abnormal traffic, and generating a network partition mapping table; gPU resources are abstracted into a logic resource pool, a resource scheduling platform based on an intelligent scheduling algorithm is constructed, and resource scheduling of heterogeneous slices is carried out.

The invention relates to the technical field of crop genetic breeding, in particular to a plateau rape adaptive germplasm breeding method based on multi-character collaborative screening, which comprises the following steps of: constructing a multi-character evaluation system covering more than 20 indexes of four categories of agriculture, physiology, quality and stress resistance, and determining character weights by applying principal component analysis, grey relational analysis and analytic hierarchy process; and acquiring data by combining unmanned aerial vehicle multispectral imaging, a ground phenotype platform and a molecular marker technology, and substituting the data into the comprehensive evaluation model for germplasm screening. According to the method, the limitation of traditional single-character breeding is broken through, multi-dimensional collaborative evaluation is achieved, and the plateau rape germplasm breeding efficiency and accuracy are remarkably improved.

The invention discloses an anti-quantum key management method for a vehicle-mounted domain centralized electronic and electrical architecture. Firstly, the invention provides a self-adaptive security policy generation method based on an analytic hierarchy process. Key factors influencing vehicle-mounted service safety are sorted through a system, a three-layer AHP hierarchical structure model with the purpose of selecting an optimal encryption mechanism is constructed, and therefore vehicle-mounted service safety modeling is achieved. According to the method, the most suitable security policy can be automatically matched according to the characteristics of different services, the self-adaptive security policy generation of the service granularity is realized, and the optimization of the system resource use efficiency is realized while the communication security is ensured. Secondly, the invention provides a fine-grained anti-quantum key management scheme based on the Chinese remainder theorem, and the fine-grained anti-quantum key management scheme is specially designed for adapting to a one-to-many communication scene widely existing in a vehicle-mounted network. The method supports efficient distribution and dynamic updating of group keys of service granularity, and has good quantum attack resistance.

The invention belongs to the technical field of welding workstations, and discloses a welding workstation robot welding path and positioner action collaborative optimization method, which comprises the following steps: constructing a weld importance-real-time working condition dynamic priority system through an analytic hierarchy process, and collecting thermal stress and deformation data in real time in combination with multiple sensors; the high-priority weld joint cooperation level with the heat deformation exceeding the threshold value is automatically adjusted up; meanwhile, establishing a'priority-equipment resource 'matching matrix to identify conflicts in advance; according to the design, working condition changes in the welding process can be dynamically adapted, the deformation problem caused by fixed priorities in a multi-welding-seam intersection area is avoided, manual interruption and adjustment are not needed, it is ensured that the robot and the positioner act collaboratively without resource preemption, it is ensured that the welding process is continuous and stable, and the welding quality consistency of multi-welding-seam workpieces is improved; a variable load coupling dynamic model is established based on a Lagrange equation, a load compensation item is embedded, and a coefficient is corrected online in real time.

The invention provides a subway tunnel water disaster risk evaluation method under extreme rainfall based on multi-source data, and belongs to the technical field of urban rail transit disaster prevention. The method comprises the following steps: establishing a grading evaluation system on the basis of field rainstorm monitoring data, hydrogeological parameters, field geological exploration, rock-soil physical and mechanical parameters, monitoring data of a tunnel lining structure and material strength parameters of a tunnel site area in combination with a plurality of developed tests, dividing corresponding grades and determining an influence index-; and S4, respectively carrying out weight calculation on the influence index-by adopting an analytic hierarchy process and an entropy weight method, then calculating a dynamic weight of the influence index-, correcting an abnormal dynamic weight, generating a comprehensive score, dividing risk grades, matching graded prevention and control measures, and optimizing and adjusting the prevention and control measures in real time through a parameter risk grade dynamic judgment and construction method matching mechanism. According to the method, minute-level accurate interpretation of a disaster evolution mechanism and dynamic optimization adaptation of a prevention and control scheme are realized.

The invention discloses a visual analysis method and equipment for the trafficability of a grain transport vehicle tractor track and a storage medium. According to the method, images are collected through a vehicle-mounted binocular vision system, and multi-dimensional geometric attributes of the terrain and obstacles are automatically extracted through semantic segmentation, three-dimensional reconstruction and voxel modeling. And on the basis of the extracted multi-dimensional attributes, constructing a hierarchical evaluation system containing terrain and obstacle criteria. A local weight of each attribute index is determined by adopting an analytic hierarchy process, and a fuzzy membership degree vector of each index on different passage evaluation grades is constructed according to dynamic judgment parameters adaptively set with the current grain transport vehicle model number and the terrain, so that a membership degree matrix is formed. And finally, through hierarchical fuzzy comprehensive evaluation, calculating to obtain a comprehensive trafficability score. The accuracy, reliability and automation level of tractor track trafficability evaluation are improved.

The invention discloses a medical equipment state monitoring and early warning method and system based on a full life cycle, and relates to the technical field of medical equipment state monitoring and early warning. Comprising a full-life-cycle data acquisition module, a multi-dimensional data preprocessing module, a full-life-cycle state evaluation module, a hierarchical early warning decision module, a full-life-cycle management module and an edge-cloud collaborative storage module. The full-life-cycle data acquisition module is used for acquiring multi-dimensional data of the medical equipment in the whole stage from purchase acceptance, operation and use, operation and maintenance to scrap evaluation, and outputting original data in the whole stage. Differentiation quantitative indexes are set for different life cycle stages, an evaluation model is constructed by adopting an analytic hierarchy process and dynamic weight adjustment, and an early warning threshold value and a four-level hierarchical response mechanism are dynamically adjusted in combination with a gradient lifting tree algorithm. The problems that a traditional evaluation mode is poor in adaptability, early warning misinformation lags behind, response pertinence is insufficient, and clinical safety guarantee is weak are solved.

The invention discloses a dynamic verifiable fuzzy multi-keyword cloud ciphertext search method based on a block chain, and relates to the technical field of cloud native security. According to the method, full-process automatic analysis from vulnerability collection to attack graph generation to vulnerability evaluation is realized by combining vulnerability data of CNNVD, Docker container information and various vulnerability analysis algorithms. The core part in the design is attack graph generation and vulnerability analysis, and the part aims to comprehensively discover vulnerabilities existing in the system as much as possible and evaluate potential safety influences of the vulnerabilities. Through fusion evaluation of the analytic hierarchy process and the improved BP algorithm, the accuracy of vulnerability evaluation can be ensured, and the purpose of providing deeper analysis for the overall security condition of the system through the prediction capability of the neural network can be achieved. According to the multi-angle evaluation mode, the comprehensiveness and scientificity of vulnerability evaluation can be improved, so that a security team is helped to manage security risks in the system more effectively.

The invention belongs to the technical field of Internet data security, and discloses a multi-dimensional Internet data security fusion processing system, which is characterized in that an acquisition module depends on a three-dimensional decision model, combines reinforcement learning dynamic allocation tasks, only acquires threat associated key data in a low-computing-power and high-threat scene, and starts full-amount lightweight acquisition in a high-computing-power and low-threat scene; the data preprocessing module adds scene labels for data, filters logic and unifies formats according to scene design, and eliminates data isomerism. The identification module builds a basic threat library and a scene adaptation layer, adapts a new scene through transfer learning, calculates a risk value in combination with a four-dimensional quantitative model such as propagation probability, generates an attack link map, and effectively eliminates a monitoring blind area caused by edge computing power limitation; the decision-making module constructs a five-dimensional trust evaluation model of cooperation duration, compliance records and the like, calculates weights by using an analytic hierarchy process, establishes a compliance and trust linkage engine, synchronizes industry specifications in real time and adapts to scene adjustment rules.

The invention belongs to the technical field of enterprise information technology resource management, and provides a tool performance evaluation method and device, and the method comprises the steps: carrying out the data preprocessing of a pre-constructed tool performance evaluation index pool matrix, and outputting a standardized matrix; n is the number of tools, and p is the number of selected indexes; performing PCA dimension reduction operation on the standardized matrix to obtain a principal component score matrix and a load matrix; d is the dimension after dimension reduction; performing k-means clustering on the principal component score matrix and the load matrix, outputting cluster division, and generating a clustering label for each cluster; and on the basis of an AHP analytic hierarchy process, tools in each cluster are sorted respectively. According to the method, the tools are grouped based on the clustering result through a clustering independent ranking mechanism, so that the intra-group homogeneity and inter-group difference of the tools are obvious, misjudgment of heterogeneous tools, monopoly sorting of dominant clusters and mismatching of resources are avoided, and the global ranking stability is improved.

The invention provides an aviation support system efficiency evaluation method and system based on a combined weighting and cloud gravity center theory. The method comprises the following steps: determining an aviation guarantee efficiency evaluation object, and establishing an aviation guarantee efficiency evaluation index system; the method comprises the following steps: based on an aviation guarantee efficiency evaluation index system, acquiring data of quantitative indexes through simulation deduction, rating the qualitative indexes by experts, converting the qualitative indexes into quantitative data through an evaluation grade scale table, standardizing the index data, and calculating weights of the indexes by adopting a combined weighting method combining an analytic hierarchy process and an entropy weight method; the method comprises the following steps: determining digital characteristics of an index cloud based on aviation guarantee efficiency evaluation index data, calculating a comprehensive cloud gravity center, determining a cloud gravity center position in an ideal state based on standardized index data, and calculating a weighted deviation degree; and calculating an efficiency evaluation value of the aviation guarantee system based on the comprehensive weight and the weighted deviation degree of the aviation guarantee efficiency evaluation index, and forming a final evaluation conclusion.

The invention relates to the technical field of tire health degree evaluation, in particular to a road transport vehicle in-use tire health degree evaluation method, which comprises the following steps of S1, acquiring tire data, S2, constructing a three-level evaluation framework based on a hierarchy analysis method, S3, constructing a first-level index judgment matrix and a second-level index judgment matrix, and S4, constructing a first-level index judgment matrix and a second-level index judgment matrix. The method comprises the following steps: S1, calculating a first-level index and a second-level index, calculating a weight vector of each single index in the first-level index and the second-level index, and carrying out normalization, row summation and further normalization processing on a first-level index judgment matrix and a second-level index judgment matrix, S4, correcting a weight vector coefficient by adopting an entropy weight method, and calculating a combined weight by adopting a multiplication combination method, and S5, carrying out fuzzy comprehensive evaluation by adopting a fuzzy comprehensive evaluation method. And S6, according to the actually measured tire data, evaluating the tire health degree. According to the method, the tire health degree is comprehensively evaluated based on the multi-dimensional indexes, the analytic hierarchy process and the entropy weight method are combined for weighting, the accident rate is reduced, and the operation and maintenance cost is saved.