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Acid-pickling plates and strips speed control system by microwave heating based on self-adaptive fuzzy PID algorithm 认领 引用 被引量：9
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作者 杨彪 彭金辉 +3 位作者 郭胜惠 张世敏 李玮 何涛 《Journal of Central South University》 SCIE EI CAS 2012年第8期2179-2186,共8页
Double self-adaptive fuzzy PID algorithm-based control strategy was proposed to construct quasi-cascade control system to control the speed of the acid-pickling process of titanium plates and strips. It is very useful... Double self-adaptive fuzzy PID algorithm-based control strategy was proposed to construct quasi-cascade control system to control the speed of the acid-pickling process of titanium plates and strips. It is very useful in overcoming non-linear dynamic behavior, uncertain and time-varying parameters, un-modeled dynamics, and couples between the automatic turbulence control (ATC) and the automatic acid temperature control (AATC) with varying parameters during the operation process. The quasi-cascade control system of inner and outer loop self-adaptive fuzzy PID controller was built, which could effectively control the pickling speed of plates and strips. The simulated results and real application indicate that the plates and strips acid pickling speed control system has good performances of adaptively tracking the parameter variations and anti-disturbances, which ensures the match of acid pickling temperature and turbulence of flowing with acid pickling speed, improving the surface quality of plates and strips acid pickling, and energy efficiency. 展开更多
关键词 self-adaptive fuzzy PID algorithm microwave heating acid pickling plates and strips mixed-acid media
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Intuitionistic fuzzy C-means clustering algorithms 认领 引用 被引量：30
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作者 Zeshui Xu Junjie Wu 《Journal of Systems Engineering and Electronics》 SCIE EI 2010年第4期580-590,共11页
Intuitionistic fuzzy sets(IFSs) are useful means to describe and deal with vague and uncertain data.An intuitionistic fuzzy C-means algorithm to cluster IFSs is developed.In each stage of the intuitionistic fuzzy C-me... Intuitionistic fuzzy sets(IFSs) are useful means to describe and deal with vague and uncertain data.An intuitionistic fuzzy C-means algorithm to cluster IFSs is developed.In each stage of the intuitionistic fuzzy C-means method the seeds are modified,and for each IFS a membership degree to each of the clusters is estimated.In the end of the algorithm,all the given IFSs are clustered according to the estimated membership degrees.Furthermore,the algorithm is extended for clustering interval-valued intuitionistic fuzzy sets(IVIFSs).Finally,the developed algorithms are illustrated through conducting experiments on both the real-world and simulated data sets. 展开更多
关键词 intuitionistic fuzzy set(IFS) intuitionistic fuzzy Cmeans algorithm clustering interval-valued intuitionistic fuzzy set(IVIFS).
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An Efficient Content-Based Image Retrieval System Using kNN and Fuzzy Mathematical Algorithm 认领 引用 被引量：3
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作者 Chunjing Wang Li Liu Yanyan Tan 《Computer Modeling in Engineering & Sciences》 SCIE EI 2020年第9期1061-1083,共23页
The implementation of content-based image retrieval(CBIR)mainly depends on two key technologies:image feature extraction and image feature matching.In this paper,we extract the color features based on Global Color His... The implementation of content-based image retrieval(CBIR)mainly depends on two key technologies:image feature extraction and image feature matching.In this paper,we extract the color features based on Global Color Histogram(GCH)and texture features based on Gray Level Co-occurrence Matrix(GLCM).In order to obtain the effective and representative features of the image,we adopt the fuzzy mathematical algorithm in the process of color feature extraction and texture feature extraction respectively.And we combine the fuzzy color feature vector with the fuzzy texture feature vector to form the comprehensive fuzzy feature vector of the image according to a certain way.Image feature matching mainly depends on the similarity between two image feature vectors.In this paper,we propose a novel similarity measure method based on k-Nearest Neighbors(kNN)and fuzzy mathematical algorithm(SBkNNF).Finding out the k nearest neighborhood images of the query image from the image data set according to an appropriate similarity measure method.Using the k similarity values between the query image and its k neighborhood images to constitute the new k-dimensional fuzzy feature vector corresponding to the query image.And using the k similarity values between the retrieved image and the k neighborhood images of the query image to constitute the new k-dimensional fuzzy feature vector corresponding to the retrieved image.Calculating the similarity between the two kdimensional fuzzy feature vector according to a certain fuzzy similarity algorithm to measure the similarity between the query image and the retrieved image.Extensive experiments are carried out on three data sets:WANG data set,Corel-5k data set and Corel-10k data set.The experimental results show that the outperforming retrieval performance of our proposed CBIR system with the other CBIR systems. 展开更多
关键词 Content-based image retrieval kNN fuzzy mathematical algorithm recall precision
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A New Fuzzy Clustering-Ranking Algorithm and Its Application in Process Alarm Management 认领 引用 被引量：6
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作者 ZHU Qunxiong +1 位作者 GENG Zhiqiang 《Chinese Journal of Chemical Engineering》 SCIE EI CAS 2005年第4期477-483,共7页
Overmany alarms of modern chemical process give the operators many difficulties to decision and diag- nosis. In order to ensure safe production and process operating, management and optimization of alarm information a... Overmany alarms of modern chemical process give the operators many difficulties to decision and diag- nosis. In order to ensure safe production and process operating, management and optimization of alarm information are challenge work that must be confronted. A new process alarm management method based on fuzzy clustering- ranking algorithm is proposed. The fuzzy clustering algorithm is used to cluster rationally the process variables, and difference driving decision algorithm ranks different clusters and process parameters in every cluster. The alarm signal of higher rank is handled preferentially to manage effectively alarms and avoid blind operation. The validity of proposed algorithm and solution is verified by the practical application of ethylene cracking furnace system. It is an effective and dependable alarm management method to improve operating safety in industrial process. 展开更多
关键词 process alarm management fuzzy clustering-ranking algorithm ethylene cracking furnace
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Blockchain technology‑based FinTech banking sector involvement using adaptive neuro‑fuzzy‑based K‑nearest neighbors algorithm 认领 引用 被引量：4
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作者 Husam Rjoub Tomiwa Sunday Adebayo Dervis Kirikkaleli 《Financial Innovation》 2023年第1期1765-1787,共23页
The study aims to investigate the financial technology(FinTech)factors influencing Chinese banking performance.Financial expectations and global realities may be changed by FinTech’s multidimensional scope,which is l... The study aims to investigate the financial technology(FinTech)factors influencing Chinese banking performance.Financial expectations and global realities may be changed by FinTech’s multidimensional scope,which is lacking in the traditional financial sector.The use of technology to automate financial services is becoming more important for economic organizations and industries because the digital age has seen a period of transition in terms of consumers and personalization.The future of FinTech will be shaped by technologies like the Internet of Things,blockchain,and artificial intelligence.The involvement of these platforms in financial services is a major concern for global business growth.FinTech is becoming more popular with customers because of such benefits.FinTech has driven a fundamental change within the financial services industry,placing the client at the center of everything.Protection has become a primary focus since data are a component of FinTech transactions.The task of consolidating research reports for consensus is very manual,as there is no standardized format.Although existing research has proposed certain methods,they have certain drawbacks in FinTech payment systems(including cryptocurrencies),credit markets(including peer-to-peer lending),and insurance systems.This paper implements blockchainbased financial technology for the banking sector to overcome these transition issues.In this study,we have proposed an adaptive neuro-fuzzy-based K-nearest neighbors’algorithm.The chaotic improved foraging optimization algorithm is used to optimize the proposed method.The rolling window autoregressive lag modeling approach analyzes FinTech growth.The proposed algorithm is compared with existing approaches to demonstrate its efficiency.The findings showed that it achieved 91%accuracy,90%privacy,96%robustness,and 25%cyber-risk performance.Compared with traditional approaches,the recommended strategy will be more convenient,safe,and effective in the transition period. 展开更多
关键词 FinTech Economic growth Blockchain technology Adaptive neural fuzzy based KNN algorithm Rolling window autoregressive lag modelling
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Advanced Fuzzy C-Means Algorithm Based on Local Density and Distance 认领 引用 被引量：4
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作者 Shaochun PANG Yijie +1 位作者 SHAO Sen JIANG Keyuan 《Journal of Shanghai Jiaotong university(Science)》 EI 2018年第5期636-642,共7页
This paper presents an advanced fuzzy C-means(FCM) clustering algorithm to overcome the weakness of the traditional FCM algorithm, including the instability of random selecting of initial center and the limitation of ... This paper presents an advanced fuzzy C-means(FCM) clustering algorithm to overcome the weakness of the traditional FCM algorithm, including the instability of random selecting of initial center and the limitation of the data separation or the size of clusters. The advanced FCM algorithm combines the distance with density and improves the objective function so that the performance of the algorithm can be improved. The experimental results show that the proposed FCM algorithm requires fewer iterations yet provides higher accuracy than the traditional FCM algorithm. The advanced algorithm is applied to the influence of stars' box-office data, and the classification accuracy of the first class stars achieves 92.625%. 展开更多
关键词 objective function clustering center fuzzy C-means （FCM） clustering algorithm degree of member-ship
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Improved Kernel Possibilistic Fuzzy Clustering Algorithm Based on Invasive Weed Optimization 认领 引用 被引量：1
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作者 赵小强 周金虎 《Journal of Shanghai Jiaotong university(Science)》 EI 2015年第2期164-170,共7页
Fuzzy c-means(FCM) clustering algorithm is sensitive to noise points and outlier data, and the possibilistic fuzzy c-means(PFCM) clustering algorithm overcomes the problem well, but PFCM clustering algorithm has some ... Fuzzy c-means(FCM) clustering algorithm is sensitive to noise points and outlier data, and the possibilistic fuzzy c-means(PFCM) clustering algorithm overcomes the problem well, but PFCM clustering algorithm has some problems: it is still sensitive to initial clustering centers and the clustering results are not good when the tested datasets with noise are very unequal. An improved kernel possibilistic fuzzy c-means algorithm based on invasive weed optimization(IWO-KPFCM) is proposed in this paper. This algorithm first uses invasive weed optimization(IWO) algorithm to seek the optimal solution as the initial clustering centers, and introduces kernel method to make the input data from the sample space map into the high-dimensional feature space. Then, the sample variance is introduced in the objection function to measure the compact degree of data. Finally, the improved algorithm is used to cluster data. The simulation results of the University of California-Irvine(UCI) data sets and artificial data sets show that the proposed algorithm has stronger ability to resist noise, higher cluster accuracy and faster convergence speed than the PFCM algorithm. 展开更多
关键词 data mining clustering algorithm possibilistic fuzzy c-means(PFCM) kernel possibilistic fuzzy c-means algorithm based on invasiv
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Design of a Multi-axis Motion Control Platform Based on LabVIEW’s Fuzzy Control Algorithm 认领 引用 被引量：5
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作者 Chuang Li Yan Zhang 《Journal of Mechanics Engineering and Automation》 2021年第1期11-16,共6页
This paper presents a fuzzy control algorithm applied to the position control of a multi-axis motion platform to achieve high precision motion control of the multi-axis motion platform.A LabVIEW-based multi-axis motio... This paper presents a fuzzy control algorithm applied to the position control of a multi-axis motion platform to achieve high precision motion control of the multi-axis motion platform.A LabVIEW-based multi-axis motion control system is designed.This system controls stepper motors using trapezoidal acceleration/deceleration pulse types and fuzzy control algorithms,which effectively avoids mechanical jitter and loss of step in the process of multi-angle motion of the stepper motor,and achieves accurate control of the stepper motor.The TCP/IP(transmission control protocol/internet protocol)communication protocol is used,so that data are output stably and not lost in the process of transmission and communication,achieving the purpose of interconnection of different systems and remote control of equipment.This control system has been tested to maintain a high level of stability and repeatability during actual operation. 展开更多
关键词 LabVIEW stepper motors multi-axis linkage fuzzy algorithms TCP/IP communication.
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Adaptive control of parallel manipulators via fuzzy-neural network algorithm 认领 引用 被引量：3
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作者 Dachang ZHU Yuefa FANG 《控制理论与应用（英文版）》 2007年第3期295-300,共6页
This paper considers adaptive control of parallel manipulators combined with fuzzy-neural network algorithms （FNNA）. With this algorithm, the robustness is guaranteed by the adaptive control law and the parametric u... This paper considers adaptive control of parallel manipulators combined with fuzzy-neural network algorithms （FNNA）. With this algorithm, the robustness is guaranteed by the adaptive control law and the parametric uncertainties are eliminated. FNNA is used to handle model uncertainties and external disturbances. In the proposed control scheme, we consider modifying the weight of fuzzy rules and present these rules to a MIMO system of parallel manipulators with more than three degrees-of-freedom （DoF）. The algorithm has the advantage of not requiring the inverse of the Jacobian matrix especially for the low DoF parallel manipulators. The validity of the control scheme is shown through numerical simulations of a 6-RPS parallel manipulator with three DoF. 展开更多
关键词 Parallel manipulator Adaptive control Fuzzy neural network algorithm Simulation
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Novel robust approach for constructing Mamdani-type fuzzy system based on PRM and subtractive clustering algorithm 认领 引用 被引量：1
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作者 褚菲 马小平 +1 位作者 王福利 贾润达 《Journal of Central South University》 SCIE EI CAS CSCD 2015年第7期2620-2628,共9页
A novel approach for constructing robust Mamdani fuzzy system was proposed, which consisted of an efficiency robust estimator(partial robust M-regression, PRM) in the parameter learning phase of the initial fuzzy syst... A novel approach for constructing robust Mamdani fuzzy system was proposed, which consisted of an efficiency robust estimator(partial robust M-regression, PRM) in the parameter learning phase of the initial fuzzy system, and an improved subtractive clustering algorithm in the fuzzy-rule-selecting phase. The weights obtained in PRM, which gives protection against noise and outliers, were incorporated into the potential measure of the subtractive cluster algorithm to enhance the robustness of the fuzzy rule cluster process, and a compact Mamdani-type fuzzy system was established after the parameters in the consequent parts of rules were re-estimated by partial least squares(PLS). The main characteristics of the new approach were its simplicity and ability to construct fuzzy system fast and robustly. Simulation and experiment results show that the proposed approach can achieve satisfactory results in various kinds of data domains with noise and outliers. Compared with D-SVD and ARRBFN, the proposed approach yields much fewer rules and less RMSE values. 展开更多
关键词 Mamdani-type fuzzy system robust system subtractive clustering algorithm outlier partial robust M-regression
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Mathematical Foundation of Basic Algorithms of Fuzzy Reasoning 认领 引用 被引量：1
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作者 潘正华 《Journal of Shanghai University(English Edition)》 2005年第3期219-223,共5页
Algorithm of fuzzy reasoning has been successful applied in fuzzy control,but its theoretical foundation of algorithms has not been thoroughly investigated. In this paper,structure of basic algorithms of fuzzy reasoni... Algorithm of fuzzy reasoning has been successful applied in fuzzy control,but its theoretical foundation of algorithms has not been thoroughly investigated. In this paper,structure of basic algorithms of fuzzy reasoning was studied, its rationality was discussed from the viewpoint of logic and mathematics, and three theorems were proved. These theorems shows that there always exists a mathe-~matical relation (that is, a bounded real function) between the premises and the conclusion for fuzzy reasoning, and in fact various algorithms of fuzzy reasoning are specific forms of this function. Thus these results show that algorithms of fuzzy reasoning are theoretically reliable. 展开更多
关键词 fuzzy reasoning algorithm of fuzzy reasoning FMP (fuzzy modus ponens) CRI(compositional rule of inference) algorithm 3I algorithm.
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Identification and Removal of Non-meteorological Echoes in Dual-polarization Radar Data Based on a Fuzzy Logic Algorithm 认领 引用 被引量：4
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作者 Bo-Young YE Gyu Won LEE Hong-Mok PARK 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2015年第9期1217-1230,共14页
A major issue in radar quantitative precipitation estimation is the contamination of radar echoes by non-meteorological targets such as ground clutter,chaff,clear air echoes etc.In this study,a fuzzy logic algorithm f... A major issue in radar quantitative precipitation estimation is the contamination of radar echoes by non-meteorological targets such as ground clutter,chaff,clear air echoes etc.In this study,a fuzzy logic algorithm for the identification of non-meteorological echoes is developed using optimized membership functions and weights for the dual-polarization radar located at Mount Sobaek.For selected precipitation and non-meteorological events,the characteristics of the precipitation and non-meteorological echo are derived by the probability density functions of five fuzzy parameters as functions of reflectivity values.The membership functions and weights are then determined by these density functions.Finally,the nonmeteorological echoes are identified by combining the membership functions and weights.The performance is qualitatively evaluated by long-term rain accumulation.The detection accuracy of the fuzzy logic algorithm is calculated using the probability of detection（POD）,false alarm rate（FAR）,and clutter–signal ratio（CSR）.In addition,the issues in using filtered dual-polarization data are alleviated. 展开更多
关键词 dual-polarization radar non-meteorological echo quality control fuzzy logic algorithm
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Dynamic multicast sharing protection algorithm based on fuzzy game in multi-domain optical network 认领 引用
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作者 WU Qi-wu CHEN Hao +1 位作者 JIANG Ling-zhi ZHOU Yang 《Optoelectronics Letters》 EI 2020年第6期455-461,共7页
Aiming at the problem of dynamic multicast service protection in multi-domain optical network, this paper proposes a dynamic multicast sharing protection algorithm based on fuzzy game in multi-domain optical network. ... Aiming at the problem of dynamic multicast service protection in multi-domain optical network, this paper proposes a dynamic multicast sharing protection algorithm based on fuzzy game in multi-domain optical network. The algorithm uses the minimum cost spanning tree strategy and fuzzy game theory. First, it virtualizes two planes to calculate the multicast tree and the multicast protection tree respectively. Then, it performs a fuzzy game to form a cooperative alliance to optimize the path composition of each multicast tree. Finally, it generates a pair of optimal multicast work tree and multicast protection tree for dynamic multicast services. The time complexity of the algorithm is O(k3 m2 n), where n represents the number of nodes in the networks, k represents the number of dynamic multicast requests, and m represents the number of destination nodes for each multicast request. The experimental results show that the proposed algorithm reduces significantly the blocking rate of dynamic multicast services, and improves the utilization of optical network resources within a certain number of dynamic multicast request ranges. 展开更多
关键词 service Dynamic multicast sharing protection algorithm based on fuzzy game in multi-domain optical network domain
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A NEW UNSUPERVISED CLASSIFICATION ALGORITHM FOR POLARIMETRIC SAR IMAGES BASED ON FUZZY SET THEORY 认领 引用 被引量：2
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作者 Fu Yusheng Xie Yan Pi Yiming Hou Yinming 《Journal of Electronics(China)》 2006年第4期598-601,共4页
In this letter, a new method is proposed for unsupervised classification of terrain types and man-made objects using POLarimetric Synthetic Aperture Radar (POLSAR) data. This technique is a combi-nation of the usage o... In this letter, a new method is proposed for unsupervised classification of terrain types and man-made objects using POLarimetric Synthetic Aperture Radar (POLSAR) data. This technique is a combi-nation of the usage of polarimetric information of SAR images and the unsupervised classification method based on fuzzy set theory. Image quantization and image enhancement are used to preprocess the POLSAR data. Then the polarimetric information and Fuzzy C-Means (FCM) clustering algorithm are used to classify the preprocessed images. The advantages of this algorithm are the automated classification, its high classifica-tion accuracy, fast convergence and high stability. The effectiveness of this algorithm is demonstrated by ex-periments using SIR-C/X-SAR (Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar) data. 展开更多
关键词 Radar polarimetry Synthetic Aperture Radar （SAR） Fuzzy set theory Unsupervised classification Image quantization Image enhancement Fuzzy C-Means （FCM） clustering algorithm Membership function
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Agricultural Water Resources Utilization and Management under Agricultural Safety Aim Based on Fuzzy Neural Network Algorithm 认领 引用
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作者 Shengxin WAN 《Asian Agricultural Research》 2021年第12期1-4,8,共4页
[Objectives]To explore the agricultural water resources utilization and management under the agricultural safety aim.[Methods]Fuzzy neural network algorithm was adopted.The evaluation model of agricultural water resou... [Objectives]To explore the agricultural water resources utilization and management under the agricultural safety aim.[Methods]Fuzzy neural network algorithm was adopted.The evaluation model of agricultural water resources utilization and management carrying capacity based on quantitative system was established.[Results]With the remarkable improvement of China's national income,great progress has been made in China's agricultural development.However,in the process of agricultural safety production,the problem of sustainable development has not been noticed,the problem of water resources exceeding the limit bearing capacity frequently occurs.[Conclusions]It is of great significance to effectively solve the problem of water resources utilization and management.In the feasibility test for the algorithm,further tests on various indicators show that the research is feasible. 展开更多
关键词 Fuzzy neural network algorithm Quantification system Utilization and management of water resources
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A Fuzzy-based Sliding Mode Control Approach for Acceleration Slip Regulation of Battery Electric Vehicle 认领 引用 被引量：6
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作者 Qin Shi Mingwei Wang +3 位作者 Zejia He Cheng Yao Yujiang Wei Lin He 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2022年第4期287-297,共11页
Due to quick response and large quantity of electric motor torque,the traction wheels of battery electric vehicle are easy to slip during the initial phase of starting.In this paper,a sliding mode control approach of ... Due to quick response and large quantity of electric motor torque,the traction wheels of battery electric vehicle are easy to slip during the initial phase of starting.In this paper,a sliding mode control approach of acceleration slip regulation is designed to prevent the slip of the traction wheels.The wheel slip ratio is used as the state variable for the formulation of system dynamics model.The fuzzy algorithm is utilized to adjust the switch function of sliding mode controller.After stability and robustness analysis,the sliding mode control law is transferred into C code and downloaded into vehicle control unit,which is validated under wet and dry road conditions.The experimental results with a small overshoot and a quick response during starting indicate that the sliding mode controller has good control efect on the slip ratio regulation.This article proposes an acceleration slip regulation method that improves the safety during acceleration for battery electric vehicle. 展开更多
关键词 Electric motor torque Wheel slip ratio Stability Fuzzy algorithm Robustness analysis
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Investigation on the interaction of dispersed and elongated bubbles based on laser-induced fluorescence 认领 引用
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作者 Ting XUE Ruini SHI +1 位作者 Haixia WANG Yan WU 《Optoelectronics Letters》 EI 2026年第2期124-128,共5页
The purpose of this paper is to investigate the interaction between dispersed and elongated bubbles in horizontal slug flow utilizing the laser-induced fluorescence method. A segmentation method based on the fuzzy C-m... The purpose of this paper is to investigate the interaction between dispersed and elongated bubbles in horizontal slug flow utilizing the laser-induced fluorescence method. A segmentation method based on the fuzzy C-mean(FCM) algorithm is proposed to effectively separate elongated bubbles from the liquid phase, and an extreme value extraction method is developed to calculate the number of dispersed bubbles in front of the nose of elongated bubbles. Moreover, the velocity offsets of elongated bubbles with and without dispersed bubbles are calculated separately based on contour extraction. In addition, the effects of dispersed bubbles on the fluctuating offsets of the nose tip position and velocity of elongated bubbles are statistically investigated under different flow velocities. The experimental results show that the increase of the gas-liquid flow velocity exacerbates the radial deviation of the nose tip and the fluctuation of axial velocity. 展开更多
关键词 fuzzy c mean algorithm elongated bubbles laser induced fluorescence segmentation method dispersed elongated bubbles horizontal slug flow dispersed bubbles extreme value extraction method
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Optimization of a Heat Exchanger Using an ARM Core Intelligent Algorithm 认领 引用 被引量：4
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作者 Yajuan Jia Juanjuan Wang Lisha Shang 《Fluid Dynamics & Materials Processing》 EI 2020年第5期871-882,共12页
In order to optimize heat transfer in a heat exchanger using an ARM(advanced RISC machine)core intelligent computer algorithm,a new type of controller has been designed.The whole control structure of the heat exchange... In order to optimize heat transfer in a heat exchanger using an ARM(advanced RISC machine)core intelligent computer algorithm,a new type of controller has been designed.The whole control structure of the heat exchange unit has been conceived on the basis of seven functional modules,including data processing and output,human-computer interaction,alarm,and data communication.The main controller and communication controller have been used in a combined fashion and a new MCU(micro control unit)system scheme has been proposed accordingly.A fuzzy controller has been designed by using a fuzzy control algorithm,and a new mode of heat transfer for the heat exchanger has been implemented by combining the fuzzy controller and the PID(proportioning integral derivative)controller.Finally,the model has been applied to an actual heat exchange station to test and verify the performances of the new approach. 展开更多
关键词 ARM heat exchanger fuzzy control algorithm communication controller PID controller
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Substation clustering based on improved KFCM algorithm with adaptive optimal clustering number selection 认领 引用 被引量：2
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作者 Yanhui Xu Yihao Gao +4 位作者 Yundan Cheng Yuhang Sun Xuesong Li Xianxian Pan Hao Yu 《Global Energy Interconnection》 EI CSCD 2023年第4期505-516,共12页
The premise and basis of load modeling are substation load composition inquiries and cluster analyses.However,the traditional kernel fuzzy C-means(KFCM)algorithm is limited by artificial clustering number selection an... The premise and basis of load modeling are substation load composition inquiries and cluster analyses.However,the traditional kernel fuzzy C-means(KFCM)algorithm is limited by artificial clustering number selection and its convergence to local optimal solutions.To overcome these limitations,an improved KFCM algorithm with adaptive optimal clustering number selection is proposed in this paper.This algorithm optimizes the KFCM algorithm by combining the powerful global search ability of genetic algorithm and the robust local search ability of simulated annealing algorithm.The improved KFCM algorithm adaptively determines the ideal number of clusters using the clustering evaluation index ratio.Compared with the traditional KFCM algorithm,the enhanced KFCM algorithm has robust clustering and comprehensive abilities,enabling the efficient convergence to the global optimal solution. 展开更多
关键词 Load substation clustering Simulated annealing genetic algorithm Kernel fuzzy C-means algorithm Clustering evaluation
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Fuzzy stochastic generalized reliability studies on embankment systems based on first-order approximation theorem 认领 引用 被引量：1
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作者 Wang Yajun Zhang Wohua +2 位作者 Jin Weiliang Wu Changyu Ren Dachun 《Water Science and Engineering》 CAS 2008年第4期36-46,共11页
In order to address the complex uncertainties caused by interfacing between the fuzziness and randomness of the safety problem for embankment engineering projects, and to evaluate the safety of embankment engineering ... In order to address the complex uncertainties caused by interfacing between the fuzziness and randomness of the safety problem for embankment engineering projects, and to evaluate the safety of embankment engineering projects more scientifically and reasonably, this study presents the fuzzy logic modeling of the stochastic finite element method （SFEM） based on the harmonious finite element （HFE） technique using a first-order approximation theorem. Fuzzy mathematical models of safety repertories were introduced into the SFEM to analyze the stability of embankments and foundations in order to describe the fuzzy failure procedure for the random safety performance function. The fuzzy models were developed with membership functions with half depressed gamma distribution, half depressed normal distribution, and half depressed echelon distribution. The fuzzy stochastic mathematical algorithm was used to comprehensively study the local failure mechanism of the main embankment section near Jingnan in the Yangtze River in terms of numerical analysis for the probability integration of reliability on the random field affected by three fuzzy factors. The result shows that the middle region of the embankment is the principal zone of concentrated failure due to local fractures. There is also some local shear failure on the embankment crust. This study provides a referential method for solving complex multi-uncertainty problems in engineering safety analysis. 展开更多
关键词 first-order approximation stochastic finite element method fuzzy math algorithm stability of embankment and foundation reliability
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