40 results about "Fuzzy method" patented technology

The invention provides an intelligent energy-saving light fuzzy control method and system in a passenger car compartment. The method comprises the steps that real-time data of external light intensity and the number of passengers in the compartment are collected; carrying out fuzzification processing on the collected data, outputting a fuzzy set, and converting the fuzzy set into an output signal of a compartment light brightness value; and executing the output signal instruction to adjust the light brightness value. According to the invention, the fuzzy method library is utilized to control the adjustment strategy of the compartment light brightness, accurate control of the light in the compartment is realized, the comfort level of passengers is satisfied, the energy consumption is effectively reduced, the intelligent level of the passenger car is improved, and more convenient, comfortable and environment-friendly travel experience is provided for the passengers.

The invention provides a sewage treatment optimization control method and system, electronic equipment and a storage medium, and belongs to the field of intelligent garbage recognition. The method comprises the following steps: building a BSM1 model of a sewage treatment process by adopting Simulink; capturing sewage simulation data based on the BSM1 model, and training by using an Elman neural network to obtain a parameter prediction model of a sewage treatment process; optimizing the parameter prediction model by adopting a prefabricated IMOGWO algorithm; obtaining a predicted value of a target control parameter according to the optimized parameter prediction model; and controlling the predicted value based on a stepping fuzzy PID method so as to optimize and control the sewage treatment process. By means of the sewage treatment method and device, the problems that existing sewage treatment equipment is poor in sewage historical information sensitivity, low in budget solving precision, low in convergence speed, prone to falling into local optimum, poor in control precision and the like are solved, and therefore it is guaranteed that sewage discharge reaches the standard while energy consumption in the sewage discharge process is effectively reduced.

The invention discloses a least square improvement-based nearest projection point ambiguity resolution method. The method comprises the following steps of: constructing a relation model between ambiguity phase differences corresponding to various baselines of a double-long-baseline phase interferometer; grid division is carried out on the field angle of the double-long-baseline phase interferometer, and a phase difference fuzzy graph is constructed; expanding the relation model of the double-long-baseline phase interferometer to a multi-long-baseline interferometer, constructing a baseline vector, a theoretical fuzzy phase difference vector and a fuzzy number vector, and determining a hyperplane perpendicular to a phase line in the phase difference fuzzy graph; starting point fuzzy phase difference vectors of all phase lines and phase difference projection points of the phase lines on a hyperplane are determined based on the phase difference mode fuzzy graph; and performing least square fitting on an actually measured fuzzy phase difference vector corresponding to the actually measured multi-snapshot target signal, searching a fitted fuzzy phase difference vector with the minimum variance, determining the nearest phase difference projection point, and obtaining a corresponding fuzzy number vector to realize ambiguity resolution.

The invention discloses an improved FMEA method based on a double-layer hesitant triangular fuzzy semantic set and fuzzy exp-TODIM, and the method comprises the steps: determining n potential failure modes of an analysis object, and constructing a failure mode set; risk factors in the FMEA method are improved to be severity, occurrence degree, detection degree, repair degree and economic degree; establishing a double-layer hesitant triangular fuzzy semantic set; obtaining an expert weight through a consensus decision algorithm based on the social network trust degree and the fuzzy preference relationship consistency; defuzzifying the fuzzy failure mode evaluation matrix in two steps to respectively obtain a semi-fuzzy failure mode evaluation matrix and a clear failure mode evaluation matrix; using an MEREC method for the clear failure mode evaluation matrix to obtain a risk factor weight; and for the semi-fuzzy failure mode evaluation matrix, using a fuzzy exp-TODIM method based on a generalized mixed Hausdorff preference distance to sort the failure modes. According to the method, the risk severity of each failure mode of the IMS is determined through the reliability and risk evaluation analysis of the IMS, and the effectiveness and applicability of the improved FMEA method are verified.

The present invention discloses a fuzzy interval analysis method for assembly deviation of aerospace products based on Jacobian spinors, which includes: establishing an assembly connection relationship diagram of product assembly; combining the structural dimensions of the product and the position of the coordinate system to obtain the Jacobian matrix of each functional feature; characterizing the deviation of each functional feature of the product based on the spinor method, and expressing it in the form of an interval; using a fuzzy method to discretize the deviation interval into confidence intervals of deviation sources under different confidence levels, and jointly establishing a Jacobian matrix to predict the deviation interval of the assembly function requirements of the final product under different confidence levels; establishing a deviation contribution calculation model to calculate the contribution value of each deviation source to the deviation of the assembly function requirements. The method can predict the possible interval of the deviation of the assembly function requirements in the actual assembly process according to the calculation results, and at the same time reasonably select the deviation source combination under different confidence intervals according to the deviation of the assembly function requirements, so as to minimize the manufacturing cost while ensuring the assembly accuracy.

The invention provides a traffic special bottleneck monitoring method based on multi-source road data, and the method comprises the following steps: S1, collecting road data of a plurality of intelligent network connection data clients, and building a road information database of different road segments; s2, performing precision complementation and error ablation on the road information of the same road section of a plurality of intelligent network connection data clients, outputting multi-source road information, and calculating overall evaluation parameters of multi-dimensional deep road section ablation; s3, calculating a road data fuzzy matrix; s4, setting and calculating the critical entropy of the traffic event; calculating a fuzzy entropy in combination with the multi-source road information and the road data fuzzy matrix; and when the fuzzy entropy is greater than the critical entropy, constructing a special event list, and listing the special event list for continuous tracking. Through the multi-dimensional multi-source deep road data ablation algorithm, the deep road data fuzzy method and the road data fuzzy entropy fluctuation recognition algorithm, the accuracy of monitoring the special traffic events is improved from the way of processing the multi-source road data.

The invention discloses a module high and low temperature test system based on a semiconductor, and the system comprises a hardware module which is used for controlling the temperature, transmitting data, and receiving an instruction; a control algorithm unit; the control algorithm module comprises a PID control module which optimizes temperature control by adjusting proportional, integral and differential parameters and improves the stability and response speed of the system by using a self-adaptive PID or fuzzy PID method. High temperature measurement precision can be realized by using a high-sensitivity sensor, errors can be reduced, control accuracy can be improved, novel technologies such as an MEMS actuator and the like are adopted, the temperature can be rapidly adjusted, the rapid change environment requirement can be met, meanwhile, through fuzzy logic and a reinforcement learning algorithm, the system can automatically adjust a control strategy according to real-time data, and the system is suitable for large-scale popularization and application. The method adapts to different working environments and conditions, combines edge calculation and deep learning technologies, can predict temperature changes, and takes measures in advance.

The invention relates to the technical field of wireless power transmission, in particular to a fuzzy PID wireless power transmission control method, system and device based on load estimation, and the method comprises the steps: measuring an output voltage and an output current, and estimating the load information of a wireless power transmission line; an equivalent circuit model is constructed based on the load information, and the relation between the output active power of the full-bridge inverter and the load is established; monitoring load information in real time, identifying system interference and load change according to a preset change rate threshold value, and judging whether to execute fuzzy PID self-tuning control or not; when fuzzy PID self-tuning control is executed, fuzzy control rules are established by fuzzifying the input quantity error and the error change rate; and performing fuzzy reasoning according to a fuzzy control rule to obtain a control quantity, and generating a corrected PID control parameter through a defuzzification method. According to the invention, the problem of limitation of a traditional PID control method in a wireless power transmission system when facing nonlinearity, dynamic change and interference is effectively solved.

The invention discloses an anti-interference fuzzy prediction control method based on a linear matrix inequality. The method comprises the following steps: 1) establishing a system state equation of a cleaning robot with noise; 2) designing a fuzzy controller according to a T-S fuzzy method; 3) converting an anti-interference fuzzy prediction control problem into a solution minimization problem; and 4) solving a minimization problem based on a linear matrix inequality method. According to the invention, the model is reasonable and has certain robustness in switching control of various states; according to the method, the cleaning robot can adapt to various different working states, the system is kept stable, meanwhile, the robustness of the system can be kept under the condition that noise disturbance exists, and the working efficiency of the cleaning robot is improved.

The invention discloses a circular array interferometer ambiguity resolution method based on adaptive angle clustering, and the method comprises the steps: firstly constructing a two-dimensional uniform circular array interferometer model, and calculating the position of each antenna array element; secondly, two units are randomly selected from the uniform circular array to form base lines, the fuzzy phase difference and the maximum fuzzy number of each base line are calculated, two base lines are randomly selected to form double-base-line combinations, each double-base-line combination is traversed, the azimuth angle and the pitch angle are calculated, and an angle matrix is formed; then, a neighborhood radius parameter of a DBSCAN clustering algorithm is set according to the input frequency, clustering analysis is carried out on the angle matrix, and a cluster with the maximum density is selected; and finally, calculating the average value of the data in the maximum density cluster to obtain the azimuth angle and the pitch angle of the target. According to the method, the correct ambiguity resolution probability and the direction finding precision of the two-dimensional circular array interferometer can be effectively improved.

The present application relates to micro energy network multi-objective optimization scheduling model, including: for micro energy network, establish multi-objective optimization scheduling model;Improved weighted fuzzy method is constructed;Specifically, including: constructing membership function, each sub objective function is fuzzy;According to the actual operation of micro energy network, determine the weight coefficient of each sub objective function at different time;The multi-objective optimization scheduling model is converted into single objective optimization scheduling model;Solve through traditional nonlinear optimization theory.The present application, improved weighted fuzzy method, the membership function and the weight setting of multi-objective function are optimized, the comprehensive coordination between multi-objective is improved, and the robustness of the algorithm is also improved, and the optimization scheduling model achieves the purpose of optimizing the output of each device in the operation process of micro energy network.

The invention belongs to the technical field of radio signal monitoring, and provides a moving target ambiguity resolution method based on frequency shift correlation. The method specifically comprises the following steps: defining a detection parameter'frequency shift 'as a difference value between a fuzzy carrier frequency and a real spectrum center; at two calculation moments, determining a corresponding fuzzy speed in a fuzzy space by using a radiation source fuzzy positioning solution, calculating a fuzzy carrier frequency corresponding to the fuzzy speed, and obtaining a frequency shift [delta] fmoij as a detection parameter based on the fuzzy carrier frequency; calculating a Doppler frequency shift fdij corresponding to each radiation source position and the corresponding carrier frequency at two calculation moments; and respectively calculating each calculation moment, calculating frequency shift correlation values of the frequency shift delta fmoij and the Puller frequency shift fdij, adding the frequency shift correlation values of the two moments to find out a minimum frequency shift correlation value, and taking a time difference positioning solution corresponding to the minimum frequency shift correlation value as a real solution.

The invention discloses a dosage self-adaptive control method and device based on multi-modal recognition, and belongs to the technical field of mode recognition and flotation dosing, and the method comprises the steps: carrying out the real-time recognition of a feeding coal quality image through a trained coal quality recognition model, judging a multi-modal working condition according to a recognition result, and then combining with a preset rule, and calculating the corresponding initial dosage. Key characteristics such as the tailing ash content, the tailing white foam amount and the tailing rough running condition are collected in real time, interval division and weighted calculation are conducted through a triangular membership fuzzy method, and the agent compensation amount is dynamically optimized. And timely transmitting a dosing amount decision value calculated based on the initial dosing amount and the comprehensive medicament compensation amount to an intelligent dosing station to complete closed-loop operation of dosing control. According to the method, the feeding coal quality and the tailing condition are comprehensively considered, accurate calculation of the dosage and real-time feedback of the control decision under the complex working condition are achieved, and stable operation of the flotation technology is guaranteed.

The invention relates to a tubular reactor temperature control method under the perspective of a singular partial differential equation. The method comprises the following steps: establishing a tubular reactor temperature concentration reaction rate system model described by a singular partial differential equation system; simplifying the temperature concentration reaction rate system model of the tubular reactor into a singular partial differential equation system; carrying out approximate linearization on the singular partial differential equation system through a fuzzy method, and designing an integral sliding mode surface containing a singular matrix; designing a sliding mode controller; and respectively analyzing the sliding mode motion accessibility and the index tolerance of the singular partial differential equation system based on a Lyapunov method to obtain a sliding mode controller gain, and applying the sliding mode controller gain to the sliding mode controller to complete the control of the temperature of the tubular reactor. According to the method, the defect that a traditional bivariate model cannot explicitly represent dynamic coupling of the reaction rate can be thoroughly overcome, the inhibition capability on the temperature runaway phenomenon is improved from the source, and the safety accident risk is remarkably reduced.

The present invention discloses a method for solving velocity ambiguity by assuming phase compensation, which comprises: identifying and detecting dynamic targets, acquiring radar data, and determining the Doppler phase difference φ corresponding to the dynamic targets. cfar , all channel data sets S and assumed speed ambiguity period N; according to the assumed speed ambiguity period N and the phase compensation formula, perform Doppler phase compensation on the radar data to obtain compensated radar data; draw an angular power spectrum based on the compensated radar data, determine the target peak point according to the peak point in the angular power spectrum, and determine the representative point of the dynamic target according to the target peak point and the geometric center of the dynamic target, as well as the time complexity of the representative point; based on the time complexity corresponding to the representative point and the target speed estimation value V cfar , determine the true speed of the dynamic target V true By applying the method provided in this application, the accuracy and computing performance of speed estimation are improved.

The invention discloses a construction and control method of a land pollution abatement system, and belongs to the technical field of environmental pollution abatement, and the method comprises the steps: constructing a land pollution abatement model described by a singular partial differential equation; the model is converted into a control system with a movable sprayer as an original point through coordinate transformation; carrying out approximate linearization on a nonlinear term in the system by utilizing a T-S fuzzy method, and designing an interval observer and a controller capable of estimating upper and lower bounds of a system state based on the approximate linearization; the bounded tolerance of the system is analyzed based on the Lyapunov stability theory, the gain of an interval observer and the gain of a controller are obtained by solving a linear matrix inequality, and the gains are applied to the designed observer and the designed controller to complete closed-loop control. According to the method, unknown soil conditions and external interference can be effectively handled, the control robustness is ensured through interval estimation, the limitation that a traditional model only depends on a partial differential equation is avoided, and accurate and stable treatment on polluted land is achieved.

The present invention provides a fuzzy deduplication method and device based on a single server. The method comprises: obtaining the first part of the image features of a certain image from the client UC, and assisting AM i For the second part of the image features of a certain image; the first part of the image features and the second part of the image features are similarly judged, and if the first part of the image features are similar to the second part of the image features, the client UC and the assistant AM are notified respectively. i A similarity check is performed, and whether to remove duplicates is determined based on the check result. The method provided by the present invention, on the one hand, reduces the communication overhead of repeated data transmission; on the other hand, effectively resists collusion attacks and brute force attacks, protects the confidentiality of user data, and effectively solves the problem of difficulty in identifying similarity after encryption of similar data across users.

The invention discloses an automatic anterior tooth characteristic parameter extraction method and evaluation system based on computer vision, and the method comprises the steps: obtaining and visualizing a full oral cavity scanning image of a patient to be processed, intercepting a tooth part image corresponding to the full oral cavity scanning image, eliminating specular reflection by using a Gaussian blur method, and obtaining an anterior tooth part image; threshold values are set for the H channel, the S channel and the V channel respectively through a color segmentation method, teeth and gingiva in each tooth part image are separated and then subjected to morphological processing respectively, and tooth part contours and gingiva part contours are extracted through a contour extraction method; the segmentation precision is further refined through a Chan-Vese active contour model algorithm and an energy function in a tooth part contour, angular points are extracted through a Shii-Tomasi angular point detection method and then clustered, and other evaluation important feature points are extracted through curve fitting and an extreme value searching method. And finally, measuring and calculating tooth evaluation related objective indexes and automatically generating a corresponding tooth score, thereby completing automatic anterior tooth evaluation.

The invention provides a multi-vehicle collaborative operation-oriented traction type AGV hinge angle robust estimation method, and belongs to the technical field of intelligent transportation AGV state observation. Firstly, in order to improve the adaptive capacity of an observer when facing the uncertain parameters of the traction-type AGV, especially for the time-varying longitudinal speed of the traction-type AGV and the trailer mass, a T-S fuzzy model is constructed by adopting a T-S fuzzy method, so that all possible uncertain parameters can be covered; secondly, in order to save communication resources and reduce the calculation burden of an AGV controller, a DETM is provided between a sensor and an observer. Finally, on the basis, an H-infinity robust hinge angle observer is provided, the observer and DETM are designed in a collaborative mode in combination with a fuzzy Lyapunov functional method and an LMI technology, and therefore the robustness of the observer is remarkably improved. According to the method, the robustness problem in hinged angle estimation of the traction type AGV can be effectively solved, and the reliability and stability of multi-vehicle collaborative operation are further improved.

The invention relates to a construction method and system of an emergency drill three-dimensional evaluation model. The construction method comprises the following steps: determining an emergency drill scene, organization and task three-level index system; based on an analytic hierarchy process, determining a weight value of each index in an emergency drill scene, organization and task three-level index system; and based on the weight value of each index in the emergency drilling scene, organization and task three-level index system and a fuzzy comprehensive evaluation method, determining evaluation scores of drilling organization roles in different drilling tasks in different drilling scenes. The invention provides a method for dividing three levels of indexes including a drill scene, a drill organization role and a drill task in combination with a refinery enterprise scene, and provides a weight calculation method in a three-level index system in combination with an analytic hierarchy process and a fuzzy method. The problem that the evaluation result is easily influenced by evaluation personnel because the current weight is mostly manually empowered is solved.

The present invention discloses a method and device for adaptive control of dosing amount based on multimodal recognition, which belongs to the field of pattern recognition and flotation dosing technology. The method includes using a trained coal quality recognition model to perform real-time recognition of the feed coal quality image, and after determining the multimodal working condition according to the recognition result, combining it with the preset rules to calculate the corresponding initial dosing amount. By collecting key features such as tailings ash content, tailings white foam volume, and tailings coarseness in real time, the triangle membership fuzzy method is used to perform interval division and weighted calculation to dynamically optimize the reagent compensation amount. The dosing decision value calculated based on the initial dosing amount and the comprehensive reagent compensation amount is transmitted to the intelligent dosing station in a timely manner to complete the closed-loop operation of dosing control. The present invention comprehensively considers the feed coal quality and tailings conditions, realizes the accurate calculation of dosing amount and real-time feedback of control decision under complex working conditions, and ensures the stable operation of the flotation process.

This invention proposes a dynamic scene deblurring method and system based on 4D Gaussian representation and pseudo-ground value supervision. The method includes: obtaining a sharp image and a rendered depth map from a 4D Gaussian representation; predicting the motion velocity of dynamic pixels using a velocity MLP network based on the rendered depth map; constructing a fuzzy weight network and predicting the contribution weight of each sampling point on the sampling trajectory; fusing the pseudo-sharp image with the original blurred input using a dynamic region mask to obtain a hybrid pseudo-ground value image; synthesizing a physically blurred image through weighted integration; and constructing a dual-domain reconstruction loss and geometry-motion regularization constraints by combining hybrid pseudo-ground value supervision and gradient decoupling strategies to jointly optimize the scene representation, motion parameters, and fuzzy model, thereby obtaining a sharp dynamic scene representation. This invention achieves explicit modeling of the physical blurring process through 4D Gaussian representation and a fuzzy weight network, improving the realism and view consistency of motion blur synthesis.

The invention provides a time difference constraint-based multi-carrier frequency phase difference ambiguity resolution method, which belongs to the field of radar arrival phase difference positioning and comprises the following steps of: designing an A group of uniform carrier frequency sequences and a B group of uniform carrier frequency sequences; respectively recording phase difference observation and time difference observation between a receiving station i and a receiving station j of the distributed radar system under the A group of carrier frequency channels and the B group of carrier frequency channels; obtaining an actual distance difference between a target and a receiving station i and an actual distance difference between the target and a receiving station j according to time difference observation, and further obtaining an inter-station phase difference fuzzy number possible value set; respectively constructing a least square cost function related to phase difference observation and fuzzy number combination under the A group of carrier frequency channels and the B group of carrier frequency channels, and selecting the fuzzy number combination enabling the cost function to be minimum as a fuzzy number solving result; and fusing the fuzzy number solving results obtained in the A group of carrier frequency channels and the B group of carrier frequency channels to obtain a final ambiguity solving result. The method is high in solving precision, high in anti-noise performance and low in calculation complexity.

The present invention discloses a surface water quality evaluation method based on fuzzy algorithm, which belongs to the field of water conservancy and hydrology / water resources monitoring. The present invention takes into account the situation that some monitoring factors far exceed the standard concentration of Class V. By calculating the difference between the measured concentration of the monitoring factor and the standard concentration of Class III water, the evaluation index of the monitoring factor exceeding the standard is obtained by using an index evaluation method that is more accurate for single factor evaluation; the fuzzy comprehensive evaluation is used to calculate the fuzzy comprehensive evaluation matrix of the river channel, and the proportion of Class IV and V water bodies in the overall water body is extracted, which is used as the fuzzy method exceeding the standard evaluation index; the exceeding standard weight is introduced to select an evaluation method that is closer to reality for the water quality of different rivers, and finally a comprehensive exceeding standard evaluation index is obtained. Compared with the traditional fuzzy comprehensive water quality evaluation, the present invention sorts the comprehensive exceeding standard evaluation index of different rivers, which can intuitively reflect the order of pollution degree of the rivers in the monitoring basin, provide judgment and basis for environmental protection departments, and is more practical.

The invention provides a fuzzy risk assessment model for off-site construction, and relates to the technical field of off-site construction risk assessment. The method comprises the following steps: firstly, identifying potential risk factors related to off-site construction by adopting a Delphi method; then, an interval value intuitionistic fuzzy IVIF-DEMATEL method is used in combination with Choquet integration, the relation between adopted risk factors ARFs is analyzed, and the method comprises the steps of data collection, decision maker weight determination, matrix construction and the like; and finally, determining the individual weight of each decision maker by using an intuitionistic fuzzy TOPSIS method, carrying out aggregation evaluation to construct a matrix, calculating an ideal solution, a distance index and a proximity coefficient, and carrying out priority ranking on risk factors. According to the method, the defects of a traditional risk assessment model are effectively overcome, and the complexity and uncertainty of off-site construction risks are comprehensively considered. By integrating multiple methods, the key risk factors and the interrelation thereof can be identified more accurately, a scientific and comprehensive risk assessment basis is provided for decision makers, and making of a more effective risk coping strategy is facilitated.

The present invention discloses a multi-agent pursuit-evasion game method and device based on reinforcement learning, which relates to the field of artificial intelligence technology. The present invention realizes the generation of strategies for multi-agent pursuit-evasion games through self-play. Based on the game data of multi-agent pursuit-evasion, by using fuzzy learning and Q-learning for the exploration and exploitation of the environment, it can autonomously generate optimal game strategies. Moreover, the present invention reasonably partitions the state-action space by using a fuzzy method. The Nash equilibrium solution generated according to the rules has global optimality and robustness. The local Q-value table composed of the adjacent states of the current state avoids the curse of dimensionality problem caused by the continuous state space.

The present invention relates to the field of antenna technology, and the present invention discloses a method, device and storage medium for resolving angle ambiguity of an antenna array. The method for resolving angle ambiguity provided by the present invention is implemented based on two subarrays, namely a first subarray and a second subarray, and there is a preset interval between the two subarrays, the array element spacing of the first subarray is equal to the array element spacing of the second subarray; the distance between the adjacent first array elements and the second array elements is equal to the preset interval, and the two subarrays are arranged in a straight line or parallel, and the corresponding phase set is subsequently determined through the ambiguity angle set received by the two subarrays, the target phase is determined, and then the target angle corresponding to the target phase is determined, thereby improving the accuracy of angle resolution on the basis of improving the efficiency of angle resolution.

The present invention relates to an image defocusing and blurring method based on a fuzzy conditional residual network. The method comprises: step 1, preparing a training set of an image defocusing and blurring model; step 2, constructing a fuzzy conditional network; step 3, constructing a conditional residual restoration network using a conditional residual module; and step 4, adopting a two-stage training strategy for image defocusing and blurring model training. The present invention can realize image defocusing and blurring more quickly and obtain a clear full-focus image of higher quality.

The invention provides a fuzzy method for determining an optimal evacuation strategy of a storm, and relates to the technical field of natural disaster assessment, and the method comprises the steps: obtaining an initial intuitionistic fuzzy set through normalization processing based on an alternative scheme and an evaluation standard of a storm emergency decision; based on the initial intuitionistic fuzzy set, obtaining a standard intuitionistic fuzzy weight through calculation; summarizing the initial intuitionistic fuzzy sets to obtain a collective intuitionistic fuzzy decision matrix; performing weighting processing on the collective intuitionistic fuzzy decision matrix by using the standard intuitionistic fuzzy weight to obtain an intuitionistic fuzzy evaluation result of the alternative scheme; and based on the intuitionistic fuzzy evaluation results of the alternative schemes, sorting the alternative schemes to obtain a storm emergency decision result, and completing fuzziness for determining the optimal evacuation strategy of the storm. According to the method, the problem that a feasible emergency decision is difficult to provide for an unconventional sudden storm event is solved.

The present application discloses a deambiguation method, device and medium for uniform circular array spatial spectrum direction finding, which relates to the field of radar direction finding technology and is used to solve the problem that when the radius of the uniform circular array is greater than half a wavelength, the spatial spectrum produces ambiguous pseudo peaks, resulting in ambiguous DOA estimation. The method includes: rotating and adjusting the uniform circular array antenna based on a preset asymmetric adjustment rule to construct an asymmetric circular array antenna; obtaining the array signal received by the asymmetric circular array antenna and calculating the corresponding covariance matrix based on the array signal; performing a preset number of eigenvalue decompositions on the covariance matrix to obtain a preset number of eigenvalues ​​and corresponding eigenvectors, and estimating the corresponding number of information sources through a fuzzy clustering algorithm; determining the MUSIC spatial spectrum matrix based on the eigenvectors of the covariance matrix; normalizing the MUSIC spatial spectrum matrix, and performing spectrum peak search on the processed MUSIC spatial spectrum matrix based on the number of information sources to determine the direction of the signal wave.