278 results about "Fuzzy number" patented technology

The invention provides a dynamic security risk assessment method of a rail transit line. The dynamic security risk assessment method comprises the steps of firstly, determining a dynamic index system for dynamic security risk assessment of the rail transit line, secondly, calculating various dynamic index values according to data acquired by the devices of the station in real time, and finally, performing dynamic assessment on the operation security risks of the rail transit line by use of a new method of interval type-2 fuzzy numbers in combination with TOPSIS; as a result, the real-time security statuses of the operation of the rail transit line can be controlled more accurately, and technical support is provided for the related administrative staff to make decisions; the dynamic security risk assessment method has very important practical significance for improving the quality of decision-making.

The invention belongs to the technical field of radio monitoring technologies, and provides a parallel baseline based method for realizing two-dimensional wideband direction finding for a phase interferometer. The method comprises the steps of: figuring out a possible fuzzy number combination of a phase difference between two groups of parallel baselines by utilizing a linear relationship among fuzzy numbers of the phase difference between the two groups of parallel baselines in a uniform round array, thereby estimating the direction cosine of a possible incident signal; subsequently, calculating the corresponding phase differences among all the longest baselines; correlating actually measured phase difference vectors of all the longest baselines of the uniform round array; finding out a phase difference vector corresponding to the maximum correlation coefficient for estimation of a theoretical phase difference vector; and acquiring non-fuzzy phase difference vectors of all the longest baselines by resolving the phase ambiguity of all the longest baselines. According to the method provided by the invention, the deficiencies of other ambiguity resolving methods can be overcome; theestimation of the direction cosine approaches a CRLB (Cremer-Rao Lower Bound), so that the direction estimation of the incident signal achieves a very high direction finding precision; in addition, the calculation quantity in the invention is less.

The invention relates to a high-speed platform high-speed air moving target detection method based on STAP (Spacetime Adaptive Processing), belonging to the technical field of aerial maneuvering target detection. The detection method comprises the following steps of: (1) performing Keystone conversion correction target distance walking on spacetime two-dimensional data received by a high-speed platform phased array radar; (2) estimating a clutter covariance matrix of data subjected to cluster walking correction according to data of a reference unit; (3) multiplying an inverse matrix of the clutter covariance matrix with data subjected to Keystone conversion to realize clutter suppression; (4) switching the suppressed data to a distance frequency domain to prepare for target distance walking compensation; (5) configuring a fuzzy number set according to an aerial moving target speed range and a radar system parameter; (6) configuring a filter group according to the fuzzy number set; and(7) making data obtained in the step (4) pass through the filter group to realize target distance walking correction, and performing spacetime two-dimensional beam foaming on a correction result to realize target accumulation. In the method, a plurality of targets with different fuzzy numbers are detected simultaneously by performing parallel processing; and the method has the advantages of high operation speed, convenience for engineering realization, and the like.

To solve the selecting problem of a heterogeneous wireless network, the invention provides a network selection method based on an interval triangular fuzzy number, considering the uncertainty and irregularity of different parameter variations of various networks. The method constructs an optimization model combining subjective and objective weights to obtain an optimal weight, the subjective weight is obtained by a fuzzy analytic hierarchy process, and the objective weight is obtained by an entropy method. When a decision matrix is constructed, considering the uncertainty of network parameters, the interval triangular fuzzy number is used for processing data, and the sorting of the networks is achieved finally based on an improved gray correlation analysis method. The method in the invention can effectively reduce the switching times of terminals relative to other methods, and has better performance in terms of network parameters (time delay, time-delay jitter and throughput capacity).

The invention provides a comprehensive risk priority number calculating method for architecture. Three risk factors (the appearance frequency, the severity degree and the discovery index) in FMEA are evaluated in the mode that fuzzy numbers are utilized in software architecture in a leveled mode; the appearance frequency and the discovery index are determined through component complexity and expertise, and the weights of different risk factors are distinguished through the conception of information entropy; through the conceptions of a positive ideal solution and a negative ideal solution in a TOPSIS method, a more reasonable and accurate risk priority number rank is obtained; in this way, a comprehensive software-failing mode risk factor evaluation technology for the architecture is achieved. By means of the comprehensive risk priority number calculating method, at the initial software design stage, developers are helped to find out potential design defects in a system, and therefore the subsequent software development quality is guaranteed.

The invention discloses a method and device for evaluating the operating state of a power transformer, belonging to the field of transformers, comprising: step 1: selecting an evaluation index for the operating state of the transformer, and constructing an evaluation model for the operating state of the transformer; step 2: dividing the operating state level of the transformer, and formulating the corresponding The scale interval of each operating state level; Step 3: Based on the analysis of the segmented triangular fuzzy number coupling set pair analysis, obtain the state deterioration connection degree of each evaluation index in the index layer; Step 4: Combined with expert experience, comprehensively apply fuzzy analytic hierarchy process and Similarity cluster analysis, assigning subjective constant weights to each evaluation index; Step 5: Determine the objective variable weights of each evaluation index based on the improved CRITIC weighting method, and combine the objective variable weights with the corresponding subjective constant weights; Step 6: According to the corresponding subjective and objective variable weights of the evaluation indicators, obtain the relationship degree of state deterioration between the project layer and the transformer as a whole. The invention can reasonably and accurately judge the running state of the transformer.

The invention discloses a network selection method based on intuitionistic fuzzy set multi-attribute decision-making. The method comprises the following steps: determining an intuitionistic fuzzy set decision-making matrix; converting each attribute value in the intuitionistic fuzzy set decision-making matrix into a trapezoidal fuzzy number to obtain a trapezoidal fuzzy number decision-making matrix, and simultaneously obtaining a membership function of each trapezoidal fuzzy number; by use of a distance formula of an intuitionistic fuzzy set, converting the distance relation of the intuitionistic fuzzy set into an area relation of the membership function of a corresponding trapezoidal fuzzy number set, and according to the trapezoidal fuzzy number decision-making matrix, obtaining a total deviation between each network to be selected and all other networks to be selected under each attribute; based on a deviation maximum idea, establishing a weight model of attributes, and according to a total deviation value, obtaining a weight value of each attribute; and by use of an intuitionistic fuzzy set weighed averaging operator (IFWA), calculating integrated attribute values of the networks to be selected, and selecting an optimum network from the networks to be selected. According to the invention, the problem of network selection in a heterogeneous network environment can be effectively solved.

The invention relates to a spatial ultrahigh-speed maneuvered target detection method based on RMDCFT (Radon-Modified Discrete Chirp-Fourier Transform). According to the method, firstly, modification is carried out based on the conventional Radon-Fourier transform method by using prior information of spatial target motion parameters, searching is carried out in a known target motion parameter range, and thus, target echo signals are extracted along the motion trajectory of a target; meanwhile, modification is also carried out based on the conventional MDCFT method, transform processing is carried out on the extracted target echo signals, and thus, the estimation on the frequency modulation rate of the target can be obtained; secondary phase of echoes is compensated based on the estimation, coherent accumulation is carried out on the target echo signals, and target detection is realized. The method has no need of predicting or estimating the fuzzy number of speed of the target and is applicable to the circumstances of limited CPI (Coherent Processing Time) and low signal-to-noise ratio; simulation results are compared with processing results of MTD, Radon-Fourier transform, FRFT (Fractional Fourier Transform) and RFRFT (Radon-FRFT) detection methods, experimental results show that the method provided by the invention can be used for effectively detecting the target when the CPI is limited and the signal-to-noise ratio is relatively low, and thus, the effectiveness of the method provided by the invention is proved.

The invention discloses a high-speed maneuvering target detection method based on discrete linear frequency modulation Fourier transform. The method comprises the steps that 1 a radar echo is received, and demodulation and pulse pressure processing are carried out on the radar echo; 2 in the fast time domain, Fast Fourier transform and Keystone transform are carried out on the echo signal in order; 3 the search range, interval and number of the speed fuzzy number, the linear frequency modulation slope and the secondary frequency modulation slope are initialized, and a fuzzy speed compensation function is built; 4 Keystone transformed data are multiplied by the fuzzy speed compensation function, and then fast inverse Fourier transform is carried out in the fast time domain; 5 improved discrete linear frequency modulation Fourier transform is carried out on the data processed in the step 4; and 6 the steps of 4 and 5 are repeated until the search of the speed fuzzy number is completed, and a detection unit diagram is constructed for constant false-alarm detection. The method provided by the invention has the advantages of better detection performance and smaller calculation amount, and can be used for remote early warning of a ground-based radar.

The invention relates to a fault tree diagnosis method for a typical fault of a reciprocating compressor coupled to a triangular fuzzy number. The method comprises the steps of (1) classifying variousfault types with each key component as a research object according to an operating mechanism of the reciprocating compressor, and establishing a fault tree of the reciprocating compressor typical fault, (2) establishing a minimum cut set of top-level events according to the logic relationship of upper and lower events of the fault tree, (3) determining the probability of occurrence of fault treetop-level events and each node layer event by combining the triangular fuzzy number, and (4) judging the location of a key component of a compressor fault according to measured data of characteristicparameters and according to the logic relationship and outputting a fault mode. According to the method, the probability that a triangular fuzzy function expresses a fault event is integrated into a fault tree diagnosis method, a multi-factor feature causing the fault is reflected, and probability assignment is allowed to have a certain degree of error. The method has the advantages of convenientapplication, high diagnostic accuracy and high reliability.

The invention discloses a shift-change double-base forward-looking synthetic aperture radar distance migration correction method. Based on a shift-change double-base forward-looking synthetic aperture radar distance migration rule, variable substitution is introduced for realizing azimuth-variant distance migration correction; and combined with iteration assessment and comparison of the correction quality, the influences of motion errors are removed, the shift-change double-base forward-looking synthetic aperture radar distance migration correction is finally realized under the condition that the motion errors exist, and precise doppler fuzzy number estimation can be obtained. The method can be applied to other high-squint synthetic aperture radar modes and is wide in application value.

Provided is a transformer repair risk decision-making method characterized by constructing an initial repair decision matrix by using a method combining fuzzy evaluation with accurate evaluation, forming a decision scheme stationing set according to the number of test times of a orthogonal table; computing the mahalanobis distance between each repair scheme and positive-negative ideal solution; setting a repair decision influence factor so as to construct a positive-negative prospect value matrix; and computing the comprehensive prospect value of each repair scheme and selecting an optimal scheme. The method uses a quantitative and qualitative combined way, prevents information loss caused by a fuzzy number precision process, introduces a gray cumulative prospect theory and is improved in validity.

The invention provides a decision-making method for the state overhaul of transformers. The method comprises the following steps: (1) reading data relative to each transformer, wherein the data comprises routine experimental data, on-line monitoring data and manual inspection data; (2) utilizing the analytic hierarchy process of a triangular fuzzy number to perform a fuzzy analytic hierarchy process for the relative data, thereby acquiring the optimal overhaul decision-making scheme for the transformers. The invention also provides a decision-making system for the state overhaul of the transformers, owing to the decision-making method, the flexible decision of the plurality of transformers can be scientifically analyzed and solved, various influence factors can be integrated to serve as a decision-making index, quantification calculation is well carried out, the indefinability and the fuzziness of the decision-making factors are reasonable processed, the decision to overhaul the state of the transformers is scientific and reasonable, the practical demand for the decision to overhaul the transformers is met, and the execution of the overhaul work of the state of the transformers is facilitated.

The invention discloses an evaluation method of geological environment bearing capacity of a coastal zone. The evaluation method comprises the steps of establishing a coastal zone geological environment bearing capacity evaluation index system, obtaining index weights by using an unstructured triangular fuzzy number weight determination method and the evaluation indexes; and obtaining the geological environment bearing capacity according to the evaluation indexes and the index weights and outputting the geological environment bearing capacity. The unstructured triangular fuzzy number weight determination method in the evaluation method fully considers the importance of each index from the overall aspect during determination of the index weights, then an evaluation judgment matrix is established from three attitudes, i.e., pessimistic, neutral and optimistic attitudes in accordance with dyadic mood operators, the two methods are effectively merged, not only can the logics recognized by experts be satisfied, but also the judgment of decision makers to the importance of micro indexes under three different attitudes, i.e., pessimistic, neutral and optimistic attitudes is comprehensively considered, and the misjudgment of the original evaluation result based on a single attitude can be effectively avoided.

The invention discloses a nonlinear agricultural non-point source pollution control method. The method comprises the steps that data are collected, a watershed hydrologic model is established, verification is conducted, an interactive algorithm is adopted in a nonlinear non-point source pollution control model, a submodel is split, an upper bound submodel and a lower bound submodel are subjected to linearized solution, 11 risk situations are defined by changing the risk level rho, a linear equation is solved to acquire the agricultural optimal planting area (please see the specifications for the formula) under the 11 risk situations and the optimal dumping right (please see the specifications for the formula) obtained through transaction in each agricultural area, and the comprehensive degree of satisfaction (please see the specifications for the formula) of environment pollution under the 11 risk situations is further acquired. According to the method, the indefinite information characteristics of random numbers, interval numbers, fuzzy numbers and the like are comprehensively considered, the production plan can be helped to be adjusted for a researched river basin, and emission is made to meet the environment requirement.

The invention discloses a wind power, demand response and compressed air energy storage included power dispatching method. The method comprises that an objective function, including the system operation cost and the system wind abandoning cost, of a day-ahead dispatching fuzzy model of a power system is established; constraint conditions, including system constraint, routine set constraint, demandresponse resource constraint and compressed-air energy-storage power station constraint, of the day-ahead dispatching fuzzy model of the power system are established, output of wind turbines, load predicted output and demand response amount in the constraints are all represented by fuzzy numbers, and system positive and negative standby capacity constraints in system constraints are represented in the form of fuzzy opportunity constraints; the system positive and negative standby capacity constraints in system constraints are made equivalent clearly to obtain a clear equivalency model of day-ahead scheduling of the power system; and optimization software is used to solve a converted scheduling model, and an optimal scheduling scheme of the power system is obtained. It is shown that the method can be used to improve the operational economic performance and wind power absorption rate of the power system.

The invention relates to a method for correcting the depth trace of self-adapting well drilling, in particular to a new method for correcting the well depth trace of the well drilling, which belongs to the technical field of measurement well drilling. The method comprises the following steps: firstly, obtaining correction coefficients (K1, K2, K3, ... Kn) according to the variations of coded disc counts and the variations of a drilling tool corresponding to each layer of wire ropes of a winch; secondly, training the correction coefficients with observed well depth, and dividing the variance of observed values and measured values into three regions, wherein each region corresponds to zero, big and small fuzzy numbers, and each fuzzy number corresponds to weighting coefficients k1, k2 and k3; and thirdly, counting the variations of the correction coefficients simultaneously to obtain the variation trend Va of the correction coefficients. The trained correction coefficients can make the variations of the correction coefficients automatically trend to influences on the correction coefficients by various factors; and the depth of the well drilling measured by the method trends to the precision gradually, the measuring errors are attenuated quickly, and the errors generated by initial depth correction and error corrections of the correction coefficients caused by introducing error observed values are eliminated effectively.

The invention provides a fault diagnosis method based on an evidence theory, and relates to the field of fault diagnosis. According to the method, a triangular fuzzy model is established for each fault, basic probability distribution functions are generated according to the intersection points between a to-be-tested sample and the fault models, and the basic probability distribution functions generated under each feature are fused through the combination of the evidence theory and rules, and finally, the fusing results of a plurality of moments are re-fused to achieve fault diagnosis. According to the method, the evidence theory is combined with the triangular fuzzy number to achieve the fault diagnosis, and the method has the advantage of being simple in calculation; according to the basic probability distribution function generating method, the fuzzy information can be well processed; the multi-time fusion fault diagnosis provided by the invention improves the robustness of fault diagnosis; and the fault diagnosis method provided by the invention can achieve the fault diagnosis of a motor rotor.

The present design is directed to a cognitive system including a receiver configured to receive a set of actors and associated actor information and receive assets and their associated asset information, a creation apparatus configured to create data dictionary entries for a taxonomy based on the set of actors and the assets and create a cognitive model using the data dictionary entries for a time period, and a computing apparatus configured to compute trust of the cognitive model as a fuzzy number and activate the cognitive model if trust of the cognitive model is above a cognitive model trust threshold. When the cognitive model is activated, the cognitive modeling system is configured to schedule a collection of tasks to run that perform regular extraction of actions from an original data source and perform at least one anomaly analysis associated with the cognitive model.