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A fuzzy clustering neural networks for motion equations of synchro-drive robot

EXPERT SYSTEMS WITH APPLICATIONS 2010年第12期37卷 7819-7824页

作者： Aydin, Serkan Celal Bayar Univ TMYO Ind Elect Programme TR-45400 Turgutlu Manisa Turkey

Motion equations for synchro-drive robot Nomad 200 are solved by using fuzzy clustering neural networks. The trajectories of the Nomad 200 are assumed to be composed of line segments and curves. The structure of the curves is determined by only two parameters (turn angle and translational velocity in the curve). The curves of the trajectories are found by using artificial neural networks (ANN) and fuzzy C-means clustered (fcm) ANN. In this study a clustering method is used in order to improve the learning and the test performance of the ANN. The fcm algorithm is successfully used in clustering ANN datasets. Thus, the best of training dataset of ANN is achieved and minimum error values are obtained. It is seen that, fcm-ANN models are better than the classic ANN models. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Synchro-drive robot Neural networks fcm algorithm Clustering

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Automatic detection of layout of color yarns of yarn-dyed fabric. Part 1: Single-system-melange color fabrics

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COLOR RESEARCH AND APPLICATION 2015年第6期40卷 626-636页

作者： Zhang, Jie Pan, Ruru Gao, Weidong Zhu, Dandan Jiangnan Univ Sch Text & Clothing Key Lab Ecotext Wuxi Jiangsu Peoples R China

To recognize the layout of color yarns of single-system-melange color fabric automatically, a novel fcm-based stepwise classification method is proposed in this article. This method consists of three main steps: (1) warp yarn segmentation, (2) weft color recognition, and (3) the layout of color warps recognition. In the first step, the yarn segmentation method based on mathematical statistics of subimages is adopted to localize warp yarns preliminarily;and then the segmentation results of warp yarn are corrected by misrecognized-boundary remove and missing-boundary interpolation. In the second step, the weft color is extracted based on RGB color histograms of whole fabric image. In the third step, the pixels in each warp yarn are classified into two clusters by fuzzy C-means clustering (fcm) algorithm in CIELAB color model separately, and the preliminary recognized layout of color warps is obtained. All warp colors are clustered by fcm algorithm in CIELAB color model again and the precise layout of color warps is output. The experimental and theoretical analysis proved that the proposed method can recognize the layout of color yarns of single-system- melange color fabrics with satisfactory accuracy and good robustness. (c) 2015 Wiley Periodicals, Inc. Col Res Appl, 40, 626-636, 2015

关键词： yarn-dyed fabric the layout of color yarns fcm algorithm yarn segmentation single-system-melange color fabrics

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An Improved LEACH Routing algorithm for Wireless Sensor Network

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INTERNATIONAL JOURNAL OF WIRELESS INFORMATION NETWORKS 2018年第3期25卷 323-331页

作者： Huang, Wenwei Ling, Yun Zhou, Weilong Hunan Univ Technol Sch Elect & Informat Engn Zhuzhou Peoples R China Key Lab Elect Drive Control & Intelligent Equipme Zhuzhou Peoples R China

Optimization of energy consumption is major concern for the design and planning of wireless sensor networks (WSNs). Recent research has demonstrated that organizing nodes in clusters has higher energy efficiency. LEACH is the most popular routing protocol for cluster-based in WSNs, and fcm algorithm is used for the optimum number of the clusters and their location. Aiming at the shortcomings of LEACH and fcm-LEACH, which including inaccurate cluster centers, unreasonable clustering and sole data transmission mode. This paper proposes a new energy efficient routing algorithm (NF-LEACH). In the new algorithm, There are many factors have considered to prolong the network life cycle that they are the degree of membership, residual energy, base station distance and data transmission mode. Finally, the comparison among LEACH, fcm-LEACH, and NF-LEACH has been done. The results show that the NF-LEACH has the longest lifetime and the most evenly distributed amongst three algorithms.

关键词： LEACH protocol fcm algorithm Wireless sensor network Energy-efficient routing algorithm

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The application of fcm-based computer image segmentation technology in agricultural production

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SERVICE ORIENTED COMPUTING AND APPLICATIONS 2024年 1-11页

作者： Liao, Heng Huang, Huadong Guangxi Int Business Vocat Coll Sch Intelligence & Informat Engn Nanning 530007 Guangxi Peoples R China

Traditional pest and disease detection methods mainly rely on manual observation and diagnosis, which is not only inefficient but also prone to errors. Therefore, studying an efficient and accurate computer image segmentation technology is of great significance for agricultural production. Therefore, this study employs the fuzzy C-means clustering algorithm and support vector machine to segment images in agricultural production through computer image segmentation technology, with the aim of solving issues in agricultural production. Based on the collected image dataset of the same crop with different diseases and degrees of disease, experiments are conducted. The results show that the average hue of the sample is between 0.0015 and 0.2613, and the average saturation is between 0.0136 and 0.6513. The histogram of pest and disease image segmentation in the research algorithm is relatively dense, indicating that the research algorithm has advantages in crop pest and disease image segmentation. Under different numbers of images, the regional consistency of different diseases is not significant, with an average consistency of over 8.0. Among the disease prediction accuracy, the highest is black spot disease, with a prediction accuracy of 96.3%. This indicates that the technology studied can effectively extract the characteristics of crop diseases and pests, improving the accuracy and efficiency of disease and pest detection. Meanwhile, this technology can also provide technical support for other applications in agricultural production, such as precision agriculture and intelligent agriculture.

关键词： Computer image segmentation technology fcm algorithm Support vector machine Agricultural production Pest and disease images

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Application of Fuzzy c-means algorithm for the estimation of Asphaltene precipitation

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PETROLEUM SCIENCE AND TECHNOLOGY 2018年第3期36卷 239-243页

作者： Taherpour, Alireza Sefidi, Alireza Cheshmeh Bemani, Amin Hamule, Touba Petr Univ Technol Dept Petr Engn Ahvaz *** Iran Petr Univ Technol Dept Basic Sci Abadan Iran

One of problematic topics in petroleum engineering is Asphaltene precipitation issue which causes problems such as tubing plugging and formation damage due to temperature, pressure and composition changes so the notability of this issue increases. In the present investigation a novel Fuzzy c-means (fcm) algorithm was developed to predict precipitated asphaltene as function of dilution ratio, carbon number of precipitants and temperature for solving the problem. The results showed that this novel approach has great ability to predict precipitated asphaltene in terms of aforementioned parameters. The coefficients of determination (R-2) for training and testing steps are calculated as 0.9828 and 0.9387 respectively. This great degree of accuracy expresses that the predicting algorithm has potential to be utilized as software for prediction of asphaltene behavior.

关键词： asphaltene fcm algorithm precipitation predicting model deposition

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Quality Evaluation of Marine Statistical Data on the Basis of Clustering algorithms

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JOURNAL OF COASTAL RESEARCH 2019年第Sup1期000卷 151-154页

作者： Cui, Yingji Xianyang Normal Univ Shaanix 712000 Peoples R China

The quality of marine statistical data is the life of marine statistical work, and it is the key to reflecting the level of marine statistical work, which is related to the credibility of marine statistical departments. Therefore, in marine statistics work, we need to establish perfect marine statistical data quality evaluation criteria. Only by meeting the basic standards will we gradually establish a comprehensive and systematic marine statistical data quality monitoring system, which will guarantee the authority of the marine statistical data. This paper further improves the quality of marine statistical data in China by using a clustering algorithm.

关键词： Quality evaluation marine statistical data clustering algorithms fcm algorithm

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A Novel Single Phase Grounding Fault Protection Scheme Without Threshold Setting for Neutral Ineffectively Earthed Power Systems

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CSEE Journal of Power and Energy Systems 2016年第3期2卷 73-81页

作者： Xiangjun Zeng Kun Yu Yuanyuan Wang Yao Xu Hunan Province Key Laboratory of Smart Grids Operation and Control School of Electrical&Information EngineeringChangsha University of Science and TechnologyChangsha 410076China Department of Electrical and Computer Engineering Purdue University NorthwestWestvilleIN46391USA

The setting values of thresholds for fault feature parameters are critical in all kinds of protection *** the detected feature parameter value exceeds the setting value,the protection will ***,the setting value based conventional protection schemes sometimes cannot satisfy the protection requirements of neutral ineffectively earthed power systems(NIEPS)due to wide variations in operating conditions and the complexities of fault *** this paper,a novel single phase grounding fault protection scheme without threshold setting is *** fault detection is achieved based on operating states rather than setting values.A fuzzy c-means algorithm is used to divide the operating state of the protected feeder into non-fault states and fault *** cluster center of each state is then obtained by classifying the historical feature samples of the protected feeder extracted under various operating conditions into their corresponding states in a constructed multi-dimensional fault feature *** distances between the detected feature samples and the cluster centers of the non-fault and the fault states are *** the distance to the fault state is shorter than that to the non-fault state,a fault is ***,the feeder is considered normal.A PSCAD/EMTDC simulator is used to simulate a 35 kV NIEPS under various operating conditions,non-linear loads,and complex fault *** show that the proposed single phase grounding fault protection scheme without threshold setting can protect the system correctly under all kinds of faults.

关键词： Distribution networks fcm algorithm neutral ineffectively earthed power systems protection scheme without threshold setting

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Optimization of the Structure of the Intelligent Active System as a Necessary Condition for the Harmonization of Creative Solutions

Optimization of the Structure of the Intelligent Active Syst...

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International Symposium on Computer Science, Digital Economy and Intelligent Systems (CSDEIS)

作者： Mutovkina, N. Yu Kuznetsov, V. N. Tver State Tech Univ Tver Russia

ISBN: (纸本)9783030392161;9783030392154

This article is devoted to the problem of identifying the most effective intelligent agents suitable in their personal qualities for solving nonstandard, complex, creative tasks. The effectiveness of the decisions made by intelligent agents determines the productivity of the entire system. The possibilities of generating creative solutions to complex, non-standard problems largely depend on the state of intelligent agents. An intelligent agent, taking into account its inherent anthropomorphic properties and qualities, can be in various psycho-emotional states: from a depressed mood to creative uplift and insight. The states of the agent change over time, which he informs the system about at specified points in time. It is assuming that all agents provide reliable information about their states to the system. Based on the data obtained, the system should determine the most and least stable agents and redistribute the functions and responsibilities between them to maximize own utility function. The task is characterizing by the need to analyze large volumes of subjective information and belongs to the class of difficulty formalized tasks. To solve it, fuzzy clustering algorithms that are well implementing in the Matlab software environment can be using.

关键词： Intelligent active system Intelligent agent Fuzzy clustering Creative solutions Coordination problem Optimization Agent status fcm algorithm

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Condition Division Method for Complex Processes Based on the Modified Fuzzy C-Means Clustering algorithm

Condition Division Method for Complex Processes Based on the...

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第25届中国控制与决策会议

作者： Guan Shouping Yan Yan College of Information Science and Engineering Northeastern University Northeastern University

ISBN: (纸本)9781467355339

A kind of Modified Fuzzy C-Means(Mfcm)clustering algorithm is presented to improve the problems of the conventional Fuzzy GMeans (fcm) clustering algorithm from three aspects:the way of clustering centre selection, application of the method of weighted dot density and the theory of information *** this new algorithm Mfcm solves the problems suffer from fcm algorithm such as the sensitivity to initial value,the slow convergence speed,the possibility to fall into local optimal solution,the lost of best clustering number and equivalence partition and so *** on Mfcm algorithm,anew condition division method for complex processes is proposed and applied to the glutamic acid fermentation process. The satisfactory simulation results are obtained and illustrated in the end of the paper.

关键词： Condition division Clustering analysis fcm algorithm Glutamate acid fermentation process

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An Improved Fuzzy C-Means Clustering algorithm and Application in Meteorological Data

An Improved Fuzzy C-Means Clustering Algorithm and Applicati...

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International Conference on Materials Science and Technology

作者： Li, Hongfei Wang, Fuling Zheng, Shijue Gao, Li Cent China Normal Univ Dept Comp Sci Wuhan Hebei Peoples R China

ISBN: (纸本)9783037850152

The fuzzy clustering algorithm is sensitive to the m value and the degree of membership. Because of the deficiencies of traditional fcm clustering algorithm, we made specific improvement. Through the calculation of the value of m, the amendments of degree of membership to the discussion of issues, effectively compensate for the deficiencies of the traditional algorithm and achieve a relatively good clustering effect. Finally, through the analysis of temperature observation data of the three northeastern province of china in 2000, the reasonableness of the method is verified.

关键词： fcm algorithm weight exponent membership degree cluster validity

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