563 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 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 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 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 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 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 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 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.

The invention relates to the field of power system clean low-carbon evaluation, and discloses an RAM-based power system clean low-carbon evaluation method and system. The method comprises the following steps: collecting multi-source heterogeneous data in real time and carrying out exception cleaning and structured processing to construct a standardized data set; dynamically adjusting the weight based on an entropy weight method and expert experience, calculating an efficiency value by using an RAM model, and optimizing a constraint condition; recognizing input redundancy and output insufficiency by decomposing slack variables, and generating a high-value improvement list in combination with principal component analysis and analytic hierarchy process; and finally, matching the optimization strategy library to form a decision report and realizing closed-loop updating of the index library. The system can dynamically evaluate the clean low-carbon level of the electric power system, accurately identify energy efficiency improvement key points, realize evaluation-optimization-feedback full-process automatic management, and significantly improve the accuracy of an evaluation result and the effectiveness of decision support.

The invention provides a raw electrode roasting process parameter collaborative optimization control method based on reinforcement learning, and belongs to the technical field of raw electrode roasting. The method comprises the following steps: collecting multi-source state data in a raw electrode roasting process, and carrying out feature extraction; and a reinforcement learning model based on the depth deterministic strategy gradient is constructed, and the operation efficiency of the roasting process is evaluated. And constructing a dynamic association network of the multi-source data. A multi-objective optimization model is established, a non-dominated sorting genetic algorithm is adopted for solving, a parameter optimization solution set is obtained, and optimal control parameters of the current working condition are selected through an analytic hierarchy process. And converting the optimal control parameter into an execution instruction through the industrial controller. According to the method, through combination of multi-source data fusion and dynamic association network construction, reinforcement learning and multi-objective optimization, a roasting complex process is accurately adapted, collaborative optimization of quality, energy consumption and equipment life is realized, control accuracy and reliability are improved, and stable and efficient production is guaranteed.

The invention relates to an e-commerce live broadcast intelligent item selection method and system. The method comprises the following steps: S1, constructing a multi-dimensional commodity selection criterion system, and collecting original data of a to-be-recommended commodity under each criterion; step S2, subjective weight calculation; s3, objective weight calculation; and S4, carrying out weight fusion and scheme evaluation. According to the method, weight quantification verification is performed through the analytic hierarchy process and the entropy weight method, and the fusion coefficient is dynamically adjusted in combination with the business scene, so that the problems of subjective experience contradiction, poor cold start adaptability and low decision transparency of traditional product selection are solved, and an experience quantification-data verification-weight fusion decision chain is formed; and finally, the product selection scientificity is improved, the scene adaptability is enhanced, and the decision transparency is improved.

The invention discloses a production area rice quality evaluation method based on multi-dimensional index fusion, and the method comprises the steps: determining a subjective weight through employing an analytic hierarchy process, calculating an objective weight through combining with a CRITIC method, and obtaining a comprehensive weight through multiplication integration normalization; establishing an index grading standard based on a sample data quantile, calculating the membership degree of each index by using a reduced half trapezoidal distribution function, and constructing a fuzzy relation matrix; and finally, synthesizing the comprehensive weight and the fuzzy relation matrix, and judging the rice quality grade according to a maximum membership degree principle. Compared with an existing evaluation criterion, the evaluation method comprehensively considers the subjective weight and the objective weight of each index, the rice quality can be evaluated more accurately, and therefore the rice grade is scientifically judged.

The present invention relates to the technical field of soil and water conservation. Disclosed is a vegetation configuration adjustment method applicable to a hilly and gully area. The method comprises: on the basis of a digital elevation model and remote sensing image data of a target watershed, dividing the target watershed into a plurality of afforestation areas, wherein each afforestation area corresponds to one site type; conducting surveying and sampling on existing vegetation in the target watershed, and determining ecological service functions of the afforestation areas, wherein the ecological service functions comprise biodiversity, a water resource conservation function and a soil improvement function; on the basis of a soil loss amount of each area in the target watershed, determining the priority degree of water and soil loss control in each area; and for areas where ecological service functions of the existing vegetation in the target watershed do not match site types, using an analytic hierarchy process to adjust vegetation in the afforestation area in view of the priority degree of current water and soil loss control in the watershed. The present invention improves the efficiency of vegetation configuration.

The invention relates to the field of artificial intelligence, and discloses a hospital project configuration type selection scheme automatic generation method based on big data analysis. The method comprises the steps of multi-source data collection and standardization preprocessing, construction of a dynamic weight evaluation model fusing an analytic hierarchy process and a gradient boosting tree, multi-target Pareto optimization by adopting an improved genetic algorithm, introduction of a Monte Carlo simulation risk pre-judgment and linkage of a resource substitution library adjustment scheme, and output of a structured document and an interactive decision board. The system supports real-time data flow access, elastic space grid planning, post capability matrix matching, dynamic cost modeling and compliance automatic verification. Through a data driving and closed-loop feedback mechanism, automatic generation of a scheme, risk pre-control and continuous evolution of a model are realized, the resource allocation accuracy, the approval passing rate and the implementation efficiency are remarkably improved, and the hyperbranched rate and the modification cost are reduced.

The invention discloses a supply chain supply and demand dynamic matching method based on a multi-agent game, and relates to the technical field of supply chain management, and the method comprises the following steps: constructing a multi-agent system, dividing agents, carrying an edge module, interacting with an MQTT protocol through a block chain, and encrypting sensitive data; sensing supply and demand information in real time, acquiring parameters according to dynamic frequency, and synchronizing the parameters to a sharing middle station after filtering and cleaning; generating a game strategy, constructing a model by taking Nash equilibrium as a target, and iteratively generating an initial strategy; dynamic matching is executed, requirements are distributed according to priorities, deviation is monitored, and negotiation and adjustment are carried out; evaluating a matching effect in multiple dimensions, and calculating a comprehensive score by using an analytic hierarchy process; and iteratively optimizing a strategy, adjusting parameters according to an evaluation result, and updating a strategy library to adapt to dynamic change. The method breaks the supply chain information island, balances the interests of all participants to achieve overall optimization, improves the supply and demand matching precision and dynamic adaptation capability, and enhances the efficiency and stability of the supply chain.

The invention discloses a digital twinborn irrigation district-oriented water resource efficient utilization and rice population quality comprehensive evaluation method and system, and relates to the technical field of irrigation district water resource efficient utilization and agricultural technology evaluation. Comprising the following steps: constructing a five-dimensional multi-level comprehensive evaluation index system, and determining a level framework; weighting the second-level indexes based on an analytic hierarchy process and calculating scores of the first-level indexes; a comprehensive integration model is established, the five first-level index scores serve as input, the nonlinear relation between the indexes is automatically learned, and an irrigation area comprehensive performance index is output; an evaluation system and a CatBoost model are integrated to a digital twinborn irrigation area platform, and multi-source data automatic access, model online reasoning and evaluation result space visualization are achieved. According to the method, the problems that an existing evaluation method is split in system, difficult in index quantification, depends on subjective authority assignment and cannot achieve dynamic spatialization display are solved, and intelligent and engineering decision support is provided for collaborative optimization of irrigation area water resources and crop production.

The invention provides a shipyard power distribution network health degree assessment method and system, and relates to the technical field of health state assessment and management of power systems. The method comprises the following steps: constructing a shipyard power distribution network health degree evaluation system by adopting an analytic hierarchy process, performing grading and scoring according to corresponding national standards, and determining subjective weights of indexes; calculating objective weights of the indexes by adopting an entropy weight method; calculating a comprehensive weight based on the subjective weight and the objective weight; and based on the comprehensive weight and the fuzzy relation matrix, performing shipyard power distribution network health degree evaluation by adopting a double-layer judgment criterion. Quantitative evaluation and hierarchical management of the health degree of the shipyard power distribution network are realized, a double-layer judgment criterion is introduced in evaluation grade judgment, the accuracy and rationality of an evaluation result are ensured, the stability of the power distribution network can be effectively improved, the unplanned shutdown risk is reduced, the power resource configuration is optimized, and the production safety and the product quality are guaranteed.

The invention belongs to the technical field of database management technologies, and particularly relates to a dynamic allocation method and system for multi-level storage resources of a database, and the method comprises the following steps: S1, data feature and storage state collection: collecting multi-dimensional feature parameters of target data and state parameters of each storage level in real time; s2, multi-dimensional data value evaluation: constructing a data value evaluation model based on an analytic hierarchy process, determining each index weight in combination with expert scoring and an entropy weight method, and calculating a comprehensive value coefficient of target data; s3, a storage hierarchy matching decision is made, a value adaptation interval of each storage hierarchy is preset, and the optimal storage hierarchy of the target data is decided according to the comprehensive value coefficient of the target data and the real-time state parameters of each storage hierarchy; according to the method, reliable acquisition of data features, accurate evaluation of multi-dimensional data values, intelligent matching of storage resources and advanced pre-migration of data can be realized, and finally, the goal of'sharing high-performance storage by high-value data and controlling storage cost by low-value data 'is achieved.

The invention discloses a power distribution network risk assessment method for massive distributed resource access, and the method comprises the following steps: dividing a risk domain according to the related information of a power distribution network, carrying out the stratified sampling of the risk domain, carrying out the Monte Carlo simulation, obtaining a sample matrix of risk indexes, inputting a random forest model, and calculating the importance score of the risk indexes, screening key risk indexes based on the importance threshold; taking the importance score as an objective weight, calculating a subjective weight by using an analytic hierarchy process, calculating a difference degree according to the subjective and objective weights, and fusing the subjective and objective weights to obtain a comprehensive weight; and obtaining a key risk index characteristic value in a to-be-evaluated scene, calculating the membership degree of the key risk index after adjusting the boundary parameter of the membership degree function according to the related information of the to-be-evaluated scene, calculating the comprehensive risk index according to the comprehensive weight and the membership degree of the key risk index, and judging the risk level. The method can fully consider the topological characteristics of the power distribution network, is suitable for the dynamic access of distributed resources, and achieves the precise risk assessment.

The invention provides a low-power-consumption scheduling method and system for an edge heterogeneous computing unit, and the method comprises the steps: constructing a resource sensing model of heterogeneous hardware, and collecting the performance parameters of a processing unit in real time; establishing a task priority evaluation model, and calculating a task priority by adopting an analytic hierarchy process based on the resource perception model and the task priority evaluation model; designing a collaborative optimization model; based on the collaborative optimization model and by adopting an improved particle swarm optimization algorithm, solving an optimal allocation scheme of tasks in the heterogeneous hardware, and dynamically adjusting the working frequency of the heterogeneous hardware; monitoring states of task execution and heterogeneous hardware in real time, judging whether resource overload or task timeout risks occur in the states or not, and if yes, triggering scheduling scheme updating. According to the method, local optimum is effectively avoided, the solution efficiency and the solution quality are remarkably improved, and the frequency-to-voltage linkage dynamic power consumption regulation and control closed loop is realized by triggering scheduling scheme updating.

The invention discloses an ecological assessment method and system based on an analytic hierarchy process and an entropy weight method, and belongs to the technical field of ecological environment assessment, and the method comprises the steps: data collection and preprocessing: collecting evaluation index data related to ecological environment influence, and carrying out cleaning and processing; determining objective weights by an entropy weight method; calculating the objective weights of the indexes according to the data variation degree; determining a subjective weight by an analytic hierarchy process: constructing a judgment matrix in combination with expert opinions, calculating the subjective weight of each index, and performing consistency check; an analytic hierarchy process and an entropy weight method are combined, optimized and weighted; the objective weight and the subjective weight are combined and optimized, and a comprehensive weight is determined; tOPSIS comprehensive evaluation: the original indexes are subjected to forward processing and standardization processing, the distance between each evaluation object and the optimal solution and the distance between each evaluation object and the worst solution are calculated, and a normalized score is obtained. According to the invention, the accuracy and reliability of an ecological assessment result can be improved, and a more scientific and comprehensive solution is provided for ecological assessment.

The invention relates to the technical field of edge computing resource management, in particular to an edge server load evaluation method based on analytic hierarchy process and performance loss. According to the method, firstly, edge servers are divided into a common type, a computing type, a memory type and an I / O type according to heterogeneous types; aiming at each type of edge server, constructing a judgment matrix by adopting an analytic hierarchy process and solving a feature vector so as to calculate load weight coefficients of CPU (Central Processing Unit), memory and disk I / O (Input / Output) resources; calculating a real-time load based on the weight coefficient, wherein the real-time load is the weighted sum of the resource utilization rates; the performance loss is further calculated according to the nonlinear relation between the real-time load and the total load ratio; and finally, restraining the real-time load through the load threshold value, and evaluating the performance state of the server in combination with the performance loss. According to the method, the accuracy and reliability of load evaluation of the heterogeneous edge server are effectively improved, the resource utilization rate is optimized, overload of the server is avoided, and the system stability is enhanced.

The invention provides a soft rock damming safety evaluation method and system based on fuzzy analytic hierarchy process, and belongs to the technical field of water conservancy and hydropower engineering safety evaluation, and the method comprises the steps: constructing a target layer-criterion layer-index layer three-level evaluation model framework; determining indexes in the index layer according to the evaluation items of the item layer; calculating the weight of each index by adopting an analytic hierarchy process; establishing a fuzzy relation matrix; performing synthesis operation on the weight of each index and the fuzzy relation matrix by using a fuzzy synthesis operator to obtain an evaluation vector; and judging the safety level of damming according to the evaluation vector. According to the method, the confidence interval based on credibility distribution is constructed, a traditional single evaluation result is replaced, uncertainty in the evaluation process is fully reflected, a more comprehensive and scientific information basis is provided for decision makers, and therefore the decision makers are assisted to make more reasonable and reliable engineering decisions.

The invention provides a fire-fighting unmanned aerial vehicle dispatching method and system based on multi-vehicle multi-nest intelligent matching, and belongs to the technical field of unmanned aerial vehicle dispatching. According to the method, a multi-dimensional state sensing system is constructed to obtain and preprocess fire-fighting unmanned aerial vehicle cluster and multi-nest operation information, and a global state data set is obtained; based on the data set, a nest matching priority evaluation model is established through an analytic hierarchy process, and accurate matching of the unmanned aerial vehicle and the nest is realized through a dynamic matching mechanism; multi-task pre-allocation and dynamic reallocation are completed by adopting a cluster collaborative scheduling optimization algorithm fusing multiple constraints, and a cross-nest switching track is generated in combination with an improved RRT track planning algorithm; a temporary landing preparation strategy is generated through the remaining voyage, the required electric quantity and risk judgment, and unmanned aerial vehicle parking supply, data uploading and position adjustment are achieved by means of a high-precision landing guide technology and a data synchronization protocol. And the requirements of high real-time performance and accuracy of multi-machine and multi-nest collaborative scheduling in a fire-fighting scene are met.

The invention discloses an SOP locating and sizing optimal configuration system and method based on sensitivity analysis. Comprising a source network data acquisition unit, a sensitivity analysis and calculation unit, an SOP locating and sizing optimization unit, a configuration scheme evaluation unit, a data storage unit and a visual monitoring platform. Synchronously acquiring and processing power distribution network data; selecting candidate branches according to sensitivity analysis; establishing a planning model, embedding multiple types of constraint conditions, obtaining an SOP optimal capacity through a particle swarm optimization algorithm, and determining an SOP configuration scheme; a multi-dimensional evaluation index system is constructed, after simulation verification, an analytic hierarchy process is adopted for weighted scoring, a comprehensive score is output, and an evaluation report is generated and sent to a data storage unit and a visual monitoring platform; through cooperative application of sensitivity analysis and an intelligent optimization algorithm, the SOP locating and sizing problem is efficiently solved, the operation economy, reliability and stability of the power distribution network can be remarkably improved, and powerful support is provided for scientific configuration of the SOP.

The invention relates to a big language model security detection system, device and equipment based on double-model adversarial evaluation, and the method comprises the steps: carrying out the variation of sensitive vocabularies through a dynamic load variation technology based on user configuration and an attack strategy template, generating diversified attack loads, and carrying out the recognition of a big language model according to the generated attack loads. Attack testing is carried out through a double-model adversarial evaluation architecture, model response content and a security judgment result are obtained, a risk score is calculated through a multi-dimensional quantitative scoring method according to the security judgment result, and a comprehensive security risk evaluation report is generated. According to the method, diversified hidden attacks are generated through a plug-in strategy library and a dynamic load variation technology; a double-model adversarial architecture is adopted, attack and detection roles are separated, an unbiased test closed loop is realized, multi-dimensional indexes are fused based on an information entropy-analytic hierarchy process, a risk assessment value is calculated, a report is generated, and scientific and accurate quantitative assessment of the security of the large language model is realized.