115 results about "Fuzzy analytic hierarchy process" patented technology

The invention provides an urban gas pipeline micro-leakage early warning method and system, and relates to the technical field of data processing, and the method comprises the steps: employing a fuzzy analytic hierarchy process to calculate a dynamic risk index based on an evaluation matrix, and triggering the three-stage linkage alarm of an audible and visual alarm, a mobile terminal and an emergency platform when the index exceeds a threshold value; for three-level linkage alarm, a mobile robot is dispatched, a target area is navigated based on thermodynamic diagram positioning and reference coordinates, gas concentration is remeasured through a methane laser detector, a pipeline surface temperature field is scanned in combination with infrared thermal imaging, and a verification result and correction data are bound through a block chain evidence storage technology. And a tamper-resistant full-link evidence chain is formed. According to the invention, through cooperation of early warning and calculation, full-process automation of gas pipeline monitoring, early warning and emergency verification is realized, and the intelligent level of safety monitoring is improved.

The invention discloses a power operation behavior intelligent identification and evaluation method in a multi-machine cooperation mode. The method is realized through multiple steps: multi-source data collaborative acquisition and time-space consistency calibration are realized by combining Beidou / GPS dual-mode positioning with an inertial measurement unit to acquire data, and a unified time-space coordinate system is constructed through an improved synchronization algorithm and time-space calibration; edge end adaptive feature enhancement and fusion are carried out, image details are enhanced by means of a generative adversarial network and the like, and multiple types of features are extracted; the multi-machine collaborative decision and risk judgment realize accurate risk assessment through a three-level fusion mechanism and a dynamic weight distribution strategy; performing dynamic evaluation and closed-loop management and control, establishing a multi-dimensional index system, generating a real-time report in combination with an improved fuzzy analytic hierarchy process, and triggering intervention; and carrying out data security storage and model optimization, and ensuring security and optimizing the model by adopting hierarchical encryption and federal learning.

The invention discloses a sea condition perception and path prediction navigation method and system for a high-speed unmanned ship, and relates to the technical field of multi-source path decision optimization, and the method comprises the steps: collecting storm real-time perception data through a sensing device, carrying out the preprocessing, outputting a standardized sea condition state vector, and providing an experience reference for real-time path planning through ship-borne historical data; constructing a multi-target navigation prediction algorithm model to predict and generate a path candidate scheme set on the basis of the storm real-time sensing data and the ship-borne historical data, and performing evaluation through a conditional random field in combination with path candidate schemes generated by the storm real-time sensing data, the ship-borne historical data and target navigation prediction; and carrying out multi-dimensional safety risk scoring on an evaluation result through a fuzzy analytic hierarchy process by combining the wave height and direction influence, the hull stability and the obstacle avoidance complexity, and determining an optimal sailing path. According to the invention, fusion of multi-source sea condition perception and dynamic path optimization is realized, and the navigation stability, the adaptability and the risk control capability of the high-speed unmanned ship are improved.

The invention relates to the technical field of electric digital data processing, and particularly provides a method for judging seepage failure of an immersed roadbed under the action of repeated seepage, which comprises the following steps of: constructing a water-force-chemical coupling test mechanism, monitoring dynamic change of a permeability coefficient, a fine particle loss rate and three-dimensional reconstruction of a pore structure in real time through a sensor, and determining seepage failure of the immersed roadbed under the action of repeated seepage. A scanning technology is combined to quantify an evolution rule of a seepage path; key parameters such as seepage path fractal dimension, fine particle mobility and dynamic porosity change are extracted on the basis of an evolution rule, the weight of each index is determined by introducing fuzzy analytic hierarchy process, and a seepage failure comprehensive index is constructed; and establishing a time sequence prediction model, inputting a seepage failure comprehensive index and an environment variable, outputting a seepage failure probability, and dividing safety-critical-danger three-level early warning. According to the method, the limitation of a traditional static evaluation method is broken through, and the whole-process monitoring and prediction of seepage failure under the dynamic action of repeated seepage are realized; and the discrimination precision is obviously improved.

The invention relates to a science and technology project evaluation method and system, and relates to the technical field of multi-index decision and intelligent modeling. Comprising the steps of collecting multi-dimensional data of finance, intellectual property, teams, historical projects and the like of science and technology projects; constructing an evaluation index system; constructing a cognitive map by taking the indexes as nodes and combining statistical correlation and expert rules; a graph attention network (GAT) is utilized to train the graph, and structural causal weights among indexes are extracted; fusing the structure weight and the original fuzzy relation matrix to form a structure enhanced fuzzy relation matrix; and in combination with a weight vector determined by a fuzzy analytic hierarchy process (FAHP), performing fuzzy weighted comprehensive evaluation, and outputting a project grade and an interpretable result. According to the method, the accuracy, self-adaptability and interpretability of science and technology project evaluation are effectively improved, and the method is suitable for complex project evaluation tasks in a multi-source heterogeneous data environment.

The invention specifically relates to a risk assessment method based on the combination of a fuzzy analytic hierarchy process and TOPSIS, and relates to the technical field of tunnel engineering construction safety. Constructing an index system; performing fuzzy hierarchy analysis; and TOPSIS evaluation is carried out. According to the invention, various means of drilling coring, image acquisition, water pressure monitoring and settlement measurement are adopted, so that geological, hydrological and construction process data are comprehensively obtained; in the geological deviation coefficient calculation, the rock mass integrity and the fracture development degree are depicted by using the proportion of the rock core length to the footage and the fracture projection area; hydrological deviation coefficients are subjected to shallow hole and deep hole water pressure fluctuation analysis, influence degrees and quantitative face values are combined, and a time-space evolution rule of water pressure abnormity is captured in a multi-dimensional mode; complex risk factors are converted into measurable indexes, deep analysis of tunnel construction risks is achieved, scientific and comprehensive data support is provided for risk assessment, and the accuracy and reliability of assessment results are remarkably improved.

The invention belongs to the technical field of energy system optimization, and particularly provides a multi-objective collaborative optimization method and system for an integrated energy system. Comprising the steps of generating a multi-dimensional uncertainty time sequence scene of the integrated energy system; establishing a high-fidelity dynamic behavior model library; defining decision variables, and constructing a multi-target two-stage stochastic programming optimization model by taking the economy, environmental protection and toughness of the comprehensive energy system as a three-dimensional optimization target; solving the multi-objective two-stage stochastic programming optimization model by adopting a self-adaptive multi-objective evolution algorithm assisted by an agent model; and according to a solving result, realizing a mixed multi-attribute decision based on a fuzzy analytic hierarchy process and a multi-criterion compromise solution sorting method. According to the method, the park-level IES global optimal, high-robustness and high-efficiency planning design is realized from uncertainty modeling, equipment characteristic description and large-scale solution to multi-attribute decision full-chain innovation.

The invention discloses a construction personnel unsafe behavior detection method based on an improved YOLO, and relates to the technical field of behavior detection, and the method comprises the steps: carrying out the improvement and training of the YOLO through the marked video data, obtaining an improved YOLO model, obtaining the video data of the operation motion of a to-be-recognized construction personnel, inputting the video data into the improved YOLO model, and combining with a multi-target tracking algorithm, and carrying out the recognition of the operation motion of the to-be-recognized construction personnel. Performing quantitative analysis on the behavior types and the behavior track characteristics of the construction personnel by applying a quantitative theory, and performing evaluation in combination with a safety evaluation model constructed based on a fuzzy analytic hierarchy process to obtain a comprehensive safety score of the construction personnel. And generating an unsafe behavior detection report according to the comprehensive safety score and the behavior safety level of the construction personnel. Through the YOLO behavior detection method, the accuracy and efficiency of unsafe behavior detection of the construction personnel are greatly improved.

The invention provides a rural smart energy system toughness evaluation method and system based on comprehensive empowerment, and the method comprises the steps: constructing an index system for rural smart energy system toughness evaluation, including static toughness indexes and dynamic toughness indexes of a power grid, a gas grid, a water grid and a heat supply network, and obtaining the original value of each index; adopting a CRITIC method to determine the objective weight of each level index; determining the subjective weight of each level index by adopting a fuzzy analytic hierarchy process; comprehensive weights of the indexes are obtained based on the objective weights and the subjective weights of the indexes of all levels, the toughness evaluation values of all the indexes are calculated through step-by-step weighted aggregation based on the comprehensive weights of the indexes and the normalized original values of all the indexes, and multi-energy coupling system toughness quantitative evaluation is carried out. According to the method, subjective and objective combined index empowerment is utilized, a'static-dynamic 'two-dimensional evaluation framework is established, and the problems that a traditional method neglects the dynamic characteristics of multi-energy coupling and static toughness evaluation is insufficient are solved.

The invention discloses a power distribution network self-healing strategy generation method and system which are used for solving the technical problem that when an existing power distribution network self-healing strategy generation method faces a fault, simple label matching is carried out only according to a fault type and a line basic structure, and the rapid power restoration quality of a power distribution network is poor. The method comprises the following steps: acquiring surface temperature distribution data of power distribution network equipment and abrupt change high-frequency transient signals of power distribution line nodes; constructing a dynamic topological graph of the power distribution network, and constructing a dynamic three-dimensional matrix according to the dynamic topological graph of the power distribution network, the surface temperature distribution data of the power distribution network equipment and the abrupt change high-frequency transient signals of the power distribution line nodes; generating a plurality of priority self-healing strategies according to a preset basic strategy library, the power distribution network optimization function and the power distribution network constraint conditions; and based on a fuzzy analytic hierarchy process, screening each priority self-healing strategy by adopting a power distribution network optimization function according to the dynamic three-dimensional matrix, and determining a target power distribution network self-healing strategy.

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 discloses an industrial control system security protection capability assessment method and system. The method comprises the following steps: acquiring key chip models, operating systems, monitoring software version information and service port information of n selected industrial control systems; the method comprises the following steps: acquiring a vulnerability list under a decision-making layer index and a corresponding threat value, constructing a fuzzy consistency judgment matrix from a target layer to a decision-making layer and from the decision-making layer to a scheme layer, performing fuzzy consistency verification on the constructed judgment matrix, calculating the weight of the decision-making layer index for the matrix passing the consistency verification, forming a weight matrix, and determining the vulnerability list according to the weight matrix. The evaluation results of the safety protection capability of the selected n industrial control systems are calculated through a fuzzy analytic hierarchy process, an analytic hierarchy model including hardware, software, protocols and other multi-dimensional indexes is constructed, vulnerability database retrieval and field test data are combined, a quantitative evaluation system is established through the fuzzy analytic hierarchy process, and the safety protection capability of the industrial control systems is evaluated. The method has the advantages of improving evaluation index systematicness, realizing multi-dimensional safety factor quantitative analysis and improving evaluation result objectivity.

The invention relates to the field of deep coal bed gas development and reservoir reconstruction engineering, in particular to a compressibility evaluation method for a deep coal bed gas reservoir containing dirt band. The invention discloses a method for evaluating compressibility of a deep coal bed gas reservoir containing dirt band. The method comprises the following steps: obtaining a normalized coal rock brittleness index, a normalized coal body structure index, a normalized fracture toughness index, a normalized ground stress heterogeneity index, a normalized dirt band and coal rock layer stress difference index, a normalized fracture surface density index and a normalized mechanical specific energy index; converting the data into dimensionless numerical values, and unifying the value range to an interval of [0, 1]; and performing hierarchical weight assignment by using a triangular fuzzy analytic hierarchy process to form a deep coal rock compressibility index, and establishing an evaluation standard according to the deep coal rock compressibility index. According to the method, a theoretical basis is provided for optimal decision-making of the on-site deep composite coal rock reservoir fracturing transformation horizon.

The invention discloses a comprehensive assessment method for weak links of a power system involving multi-dimensional indexes in extreme weather. The method comprises the following steps: firstly, establishing a multi-dimensional index system containing safety and optimized operation, wherein the system covers the line outage probability, the load loss probability, the electric energy insufficiency expectation, the line heavy load rate and the network loss rate; secondly, constructing a line fault model and a cascading fault model under extreme storm weather, describing fault probability change in combination with a Gaussian function and Weibull distribution, and simulating line segment failure by adopting Poisson distribution; a system state after a fault is calculated through a direct-current optimal power flow model, and a large amount of simulation data is obtained in combination with a non-sequential Monte Carlo method. Furthermore, a fuzzy analytic hierarchy process and a CRITIC method are adopted to calculate subjective and objective weights respectively, subjective and objective comprehensive evaluation is realized through weight fusion, and weak links of the system are identified. The method gives consideration to evaluation scientificity and calculation efficiency, and is suitable for real-time risk evaluation and weak link identification of a large-scale power system in extreme weather.

The invention discloses a single-phase earth fault comprehensive discrimination method based on multiple fault criteria and weight dynamic calculation, and the method comprises the steps: collecting phase voltage and zero sequence voltage characteristic quantities before and after a power distribution network fault, and discriminating the type of a single-phase earth fault according to the change rule of the characteristic quantities; the method comprises the following diagnosis steps: a, adopting a new zero-sequence current method, calculating the zero-sequence current break variable of each feeder switch based on a zero-sequence current reference value, and achieving the positioning of a fault feeder and a section; b, a new phase current method is adopted, a phase current fault characteristic quantity is defined based on the sum of three-phase current difference values before and after a fault, and positioning of a fault feeder line and a section is achieved; constructing an evaluation model by adopting a fuzzy analytic hierarchy process according to the fault category judged by the parallel diagnosis, and dynamically determining a weight coefficient; and performing weighted fusion on the confidence coefficient according to the weight coefficient to obtain the comprehensive fault probability of each feeder line, selecting the feeder line with the maximum comprehensive fault probability as a fault feeder line, and judging a fault interval.

The invention relates to the technical field of train wireless network communication, in particular to an information security risk assessment method for a train wireless network control system, which comprises the following steps of: establishing an attack tree model according to a risk assessment object, assessing the occurrence possibility of a security event by using a triangular fuzzy number, analyzing attack paths, and calculating the interval probability of each attack path, the method comprises the following steps: obtaining a point probability according to an attack path interval probability, calculating an attack occurrence possibility, evaluating a security event influence by using a fuzzy analytic hierarchy process, calculating a security event risk value by quantifying the occurrence possibility and an influence value of the security event, and determining a risk level and a security level of a system according to a system risk evaluation value. And formulating corresponding protection requirements. According to the method, the information security risk of the train wireless network control system is effectively evaluated and managed, a basis is provided for formulating an effective security protection strategy, and the overall security capability of the train wireless network is improved.

The application discloses a kind of underwater vehicle degradation characterization method, belong to underwater vehicle technical field, steps are as follows: the full life cycle data collected by sensor carried on underwater vehicle is collected, data is preprocessed;Feature extraction is carried out to the data after pre-processing;Design a kind of layered cooperation particle swarm optimization algorithm based on fuzzy analytic hierarchy process, the selected feature is obtained by screening the extracted feature, and the final optimal feature combination is obtained;Dynamic correlation mahalanobis distance is used to weight and fuse the selected feature, and the fusion feature is obtained;Using the UMAP dimension reduction method with degradation perception, the degradation process is divided into three stages of early, middle and late according to the full life cycle data, an independent UMAP submodel is trained in each stage, and then the degradation index is fused by transfer learning.This application breaks through the limitation of single signal, realizes multi-component coupling degradation recognition, strengthens early degradation capture, reduces the rate of missed judgment and fault risk, has environmental dynamic adaptability, and adapts to complex deep-sea working conditions.

The application relates to an energy storage power station consistency evaluation method, system, equipment and medium based on an improved MK algorithm, and comprises the following steps: based on a pre-established energy storage power station consistency evaluation index system, obtaining original observation data of each index, and forming a standardized data matrix and a fuzzy judgment matrix; based on the standardized data matrix and the fuzzy judgment matrix, a combination weight vector is obtained through a combination weight assignment method of fuzzy analytic hierarchy process-gray correlation degree-game theory; based on the improved MK algorithm, clustering analysis is performed on a data set of an energy storage power station to be evaluated, and the consistency of the energy storage power station is evaluated in combination with the combination weight vector, so that a consistency evaluation result is obtained. The application can be widely applied to the technical field of energy storage power station safety risk evaluation.

The invention discloses an acquisition terminal test case priority ranking method based on a fuzzy analytic hierarchy process, which comprises the following steps of: applying the fuzzy analytic hierarchy process to the field of acquisition terminal test, and quantizing fuzzy evaluation opinions of experts by triangular fuzzy through constructing a'target-criterion-scheme 'hierarchical structure; fusing a multi-expert judgment matrix by adopting a weighted geometric averaging method, and optimizing a criterion weight and performing defuzzification in combination with consistency check; and comprehensive priority scores of the test cases are calculated through weighted summation, a sorting sequence from high to low is generated, and meanwhile, dynamic adjustment during demand change is supported. According to the method, the fuzzy demand quantification accuracy can be improved by 60%, the expert dispute rate is reduced to 8% or below, the regression test error detection efficiency is improved by 40%, and the method adapts to the multi-scene test demand of the acquisition terminal.

The invention discloses a power distribution network typical scene division method based on a fuzzy C-means clustering theory, and aims to explore a novel local power system development mode adapted to rural energy revolution and dual-carbon objectives, comprising the following steps: 1, systematically constructing a multi-dimensional division system of a rural power distribution network typical scene, a comprehensive index system is constructed from four aspects of a new energy development level, a power grid construction level, a load level and an energy storage construction level; 2, establishing a combined weighting method model of an entropy weight method and a fuzzy analytic hierarchy process; 3, a fuzzy C-means clustering algorithm is put forward as a power grid scene division method; and 4, defining an evaluation standard for a division result through the clustering algorithm. According to the method, the power distribution network scene is divided, so that an important reference is provided for planning, construction and operation of the power distribution network, and the method has important significance in promoting energy revolution and realizing a dual-carbon target.

The invention discloses an equipment health assessment method, system and equipment in dynamic operation and maintenance of a power distribution network based on point cloud three-dimensional visualization and a storage medium, and relates to the technical field of power distribution network monitoring and assessment, and the method comprises the steps: obtaining the original point cloud data of a power distribution network scene and the operation state data of target equipment in the power distribution network; processing the original point cloud data to construct a three-dimensional point cloud model of the power distribution network scene, and performing semantic segmentation on the equipment point cloud; based on the historical operation state data of the target equipment, performing time sequence prediction on the degradation index of the operation health state of the target equipment by adopting a GPR (Gaussian Process Regression) model to obtain a probabilistic prediction result containing a prediction mean value and a prediction variance; evaluating the current comprehensive health state of the target equipment by adopting a fuzzy analytic hierarchy process (FAHP) model to obtain a comprehensive health evaluation score; dynamically adjusting the fusion weight of the probabilistic prediction result and the comprehensive health assessment score by using the prediction variance, and calculating to obtain a hybrid prediction health index HPHI; and respectively mapping the HPHI and the prediction variance into visual attributes, and rendering the target equipment in the three-dimensional scene. According to the method, the dynamic visual accurate quantitative evaluation of the health state of the target equipment and the reliable prediction of the future trend in the dynamic operation and maintenance of the power distribution network are realized.

The present application relates to a method for analyzing and evaluating photovoltaic power generation efficiency. The method includes obtaining historical operation data, corresponding historical meteorological data, and historical power grid data of a photovoltaic power station; performing causal inference analysis on the historical operation data, historical meteorological data, and historical power grid data to obtain influencing factors affecting the power generation efficiency of the photovoltaic power station; combining the fuzzy analytic hierarchy process to comprehensively evaluate and assign weights to the influencing factors to obtain weighted influencing factors; constructing a dynamic DEA model based on time series analysis according to the weighted influencing factors, and performing efficiency evaluation based on the dynamic DEA model to obtain an efficiency evaluation result, where the efficiency evaluation result includes an efficiency change trend and true efficiency values at different time points. By combining causal inference, fuzzy analytic hierarchy process, and dynamic DEA model, this method can comprehensively and dynamically evaluate photovoltaic power generation efficiency, provide a scientific basis for operation and maintenance management, optimize resource allocation and improve power generation efficiency, and ensure the long-term stable operation of the power station in a complex environment.

The embodiment of the invention provides an interface element importance degree evaluation method and device based on fuzzy hierarchy analysis, and the method comprises the steps: collecting index data corresponding to interface elements at a current preset hierarchy through receiving an index structure corresponding to a fuzzy complementary judgment matrix, and constructing the fuzzy complementary judgment matrix based on the total element number and the index data; based on the total element number and matrix elements in a fuzzy complementary judgment matrix corresponding to the current preset level, determining factor weights of the interface elements in the fuzzy complementary judgment matrix, and based on the interface elements, determining a feature matrix corresponding to the fuzzy complementary judgment matrix; and determining the compatibility between the current fuzzy complementary judgment matrix and the feature matrix based on a compatibility calculation rule, and marking the current layout data as important layout data under the condition that the compatibility is not greater than a preset compatibility threshold value. According to the method, the defect of insufficient evaluation precision of the importance degree of the interface elements in the traditional technology is effectively overcome, and the accuracy of the importance degree of the interface elements is remarkably improved.

The application discloses a kind of multi-source sensing and space-time matching inland waterway navigability test and evaluation method, belong to waterway engineering and ship test evaluation technical field.Pass through the layout shore base monitoring unit and integrated shipboard perception unit, unified space-time datum is constructed;Based on unified space-time datum, space-time matching fusion is carried out to ship dynamic response data and waterway environment data, forms ship response-environment excitation coupling data set, constructs three-layer navigability performance evaluation system, uses improved fuzzy analytic hierarchy process to determine index weight in combination with three scale method and optimal transfer matrix, uses cloud model to complete index quantization and comprehensive evaluation value calculation, finally determines waterway navigability effect grade according to comprehensive expectation value.The application realizes the quantitative evaluation of multi-source data accurate fusion and subjective and objective fusion, forms standardization test and evaluation process, truly reflects the coupling navigability characteristics of waterway and ship, provides technical support for inland waterway engineering acceptance, navigation safety management and waterway optimization design.

The application discloses an offshore renewable energy development evaluation method and system, which comprises the following steps: obtaining offshore renewable energy development data; using a fuzzy analytic hierarchy process to evaluate the offshore renewable energy development data to obtain a preliminary evaluation result; determining index weights for evaluating the offshore renewable energy development data based on the preliminary evaluation result; performing index value assignment and data standardization processing on the index weights to obtain a comprehensive evaluation result according to the processing result. The application can effectively evaluate offshore renewable energy development.

The invention relates to the technical field of environment evaluation, in particular to an abandoned mine geological environment comprehensive evaluation method, a medium and equipment. The method comprises the following steps: constructing an abandoned mine geological environment comprehensive evaluation index system; determining the optimal subjective weight of the evaluation index based on a fuzzy analytic hierarchy process and an IRMO algorithm; determining objective weights of evaluation indexes based on an entropy weight method; based on the game theory, determining the comprehensive weight of the evaluation index; and dividing evaluation grades, calculating the membership degree of the evaluation object to each evaluation grade based on a fuzzy comprehensive evaluation method, and determining the evaluation grade of the evaluation object according to a maximum membership degree principle. Subjective and objective coordination of evaluation index weights, geological conditions, mine resource damage and loss degrees and geological environment problems are considered; the IRMO algorithm is introduced, the subjective weight obtaining method of the fuzzy analytic hierarchy process is optimized, the influence of the expert level on the judgment matrix in the existing analysis method is weakened, the credibility of the weight is improved, and the final evaluation result is more reliable.

The application relates to the technical field of data security, and discloses a financial data security risk assessment method and device; the method comprises the following steps: determining an initial risk index set, wherein the initial risk index set comprises a plurality of risk indexes influencing financial data security; performing screening on the initial risk index set based on an approximation ideal solution sorting method to determine a target risk index set; determining an initial weight set of the target risk index set based on a fuzzy analytic hierarchy process; correcting the initial weight set of the target risk index set by using an entropy weight of the target risk index set to obtain a target weight set of the target risk index set; and calculating a fuzzy comprehensive evaluation result of the financial data security risk based on a fuzzy membership matrix of an evaluation factor set, the target weight set of the target risk index set and an assignment matrix of a comment set. The application can objectively and accurately evaluate the financial data security risk.

The invention discloses a construction risk evaluation method for a tunnel crossing a strong outburst coal seam group. According to the evaluation method, 15 risk factors including geology, construction technologies and operators are included into a comprehensive evaluation framework; a fuzzy analytic hierarchy process is adopted to obtain global comprehensive weights of 15 risk factors, the weights serve as parameters to be input into a back propagation neural network, dynamic risk prediction is achieved, and an intelligent risk assessment model capable of being updated in real time is constructed. The problems of subjectivity and dependency relationship among indexes in expert judgment are effectively solved, and the risk of the complex system is dynamically simulated and predicted by the aid of powerful nonlinear mapping and learning capabilities of the system. The method significantly improves the tunnel construction risk identification precision and early warning capability in a complex geological environment, and can be widely applied to high-risk underground engineering safety management.

The present invention discloses a method and system for dynamic optimization of a wind farm based on real-time data adaptive regulation, which relates to the technical field of wind farm optimization. The method includes: acquiring wind farm environmental data and wind turbine status data, mapping them to a state space model, and aligning them within the same time step; constructing a wind farm dynamic optimization objective, calculating the uncertainty degree, dynamic importance degree, and target collaborative contribution rate, constructing a fuzzy analytic hierarchy process matrix, solving to obtain the weight of the wind farm dynamic optimization objective, and constructing a dynamic optimization objective function; constructing wind farm constraints, solving the dynamic optimization objective function to generate an optimal control parameter set, inputting it into a safety barrier function for verification, and after passing the verification, performing wind farm dynamic optimization. By constructing a wind farm dynamic optimization objective, power coordination optimization within the entire field is achieved, and wake damage is reduced; by introducing a safety barrier function and a fault tolerance control mechanism, the overall optimization efficiency and reliability of the wind farm are improved.

The invention discloses a dynamic task efficiency evaluation method for a man-machine cooperation system, and the method comprises the steps: carrying out the multi-state modeling of a cooperation system which comprises a movable platform and an operation unit, and constructing a state transition relation; respectively establishing dynamic efficiency models of the platform and the operation unit; constructing a time-varying availability matrix and a reliability matrix based on the model and the state relationship; constructing a multi-dimensional capability index system, fusing the objective weight of the entropy weight method and the subjective weight of the fuzzy analytic hierarchy process to obtain a comprehensive weight, and further constructing a time-varying capability matrix; and performing synthesis operation on the three matrixes, and outputting a dynamic efficiency evaluation result of the whole task process. According to the method, the defects of insufficient description of a dynamic process and human factors, strong weight subjectivity and the like of a traditional method are overcome, and accurate and reasonable dynamic evaluation of the task efficiency of the complex man-machine cooperation system is realized.