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Generating Type 2 Trapezoidal Fuzzy membership function Using Genetic Tuning

Computers, Materials & Continua 2022年第4期71卷 717-734页

作者： Siti Hajar Khairuddin Mohd Hilmi Hasan Emilia Akashah P.Akhir Manzoor Ahmed Hashmani Centre for Research in Data Science Department of Computer and Information SciencesUniversiti Teknologi PETRONASPerakMalaysia

Fuzzy inference system(FIS)is a process of fuzzy logic reasoning to produce the output based on fuzzified *** system starts with identifying input from data,applying the fuzziness to input using membership functions(MF),generating fuzzy rules for the fuzzy sets and obtaining the *** are several types of input MFs which can be introduced in FIS,commonly chosen based on the type of real data,sensitivity of certain rule implied and computational *** paper focuses on the construction of interval type 2(IT2)trapezoidal shape MF from fuzzy C Means(FCM)that is used for fuzzification process of mamdani *** the process,upper MF(UMF)and lower MF(LMF)of the MF need to be identified to get the range of the footprint of uncertainty(FOU).This paper proposes Genetic tuning process,which is a part of genetic algorithm(GA),to adjust parameters in order to improve the behavior of existing system,especially to enhance the accuracy of the system *** novel process is a hybrid approach which produces Genetic Fuzzy System(GFS)that helps to enhance fuzzy classification problems and *** approach provides a new method for the construction and tuning process of the IT2 MF,based on the FCM *** result is compared to Gaussian shape IT2 MF and trapezoid IT2 MF generated by the classic GA *** is shown that the proposed approach is able to outperform the mentioned benchmarked *** work implies a wider range of IT2 MF types,constructed based on FCM outcomes,and an optimum generation of the FOU so that it can be implemented in practical applications such as prediction,analytics and rule-based solutions.

关键词： Fuzzy inference system membership function genetic tuning lateral adjustment trapezoidal MF fuzzy C means

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Rock burst laws in deep mines based on combined model of membership function and dominance-based rough set

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Journal of Central South University 2015年第9期22卷 3591-3597页

作者：刘浪陈忠强王李管 Energy School Xi’an University of Science and Technology Beijing General Research Institute of Mining and Metallurgy School of Resources and Safety Engineering Central South University

Rock bursts are spontaneous, violent fracture of rock that can occur in deep mines, and the likelihood of rock bursts occurring increases as depth of the mine increases. Rock bursts are also affected by the compressive strength, tensile strength, tangential strength, elastic energy index, etc. of rock, and the relationship between these factors and rock bursts in deep mines is difficult to analyze from quantitative point. Typical rock burst instances as a sample set were collected, and membership function was introduced to process the discrete values of these factors with the discrete factors as condition attributes and rock burst situations as decision attributes. Dominance-based rough set theory was used to generate preference rules of rock burst, and eventually rock burst laws analysis in deep mines with preference relation was taken. The results show that this model for rock burst laws analysis in deep mines is more reasonable and feasible, and the prediction results are more scientific.

关键词： deep mine rock burst membership function dominance relation rough set

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Properties of Fuzzy Entropy Based on the Shape Change of membership function

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Journal of Donghua University(English Edition) 2007年第2期24卷 268-271页

作者：卿铭秦应兵 Department of Mathematics Southwest Jiaotong University

Modification of a fuzzy partition often leads to the change of fuzziness of a fuzzy system. Researches on the change of fuzzy entropy of a fuzzy set, responding to shape alteration of membership function, therefore, play a significant role in analysis of the change of fuzziness of a fuzzy system because a fuzzy partition consists of a set of fuzzy sets which satisfy some special constraints. This paper has shown several results about entropy changes of a fuzzy set. First, the entropies of two same type of fuzzy sets have a constant proportional relationship which depends on the ratio of the sizes of their support intervals. Second, as for Triangular Fuzzy Numbers （TFNs）, the entropies of any two TFNs which can not be always the same type, also, have a constant proportional relationship which depends on the ratio of the sizes of their support intervals. Hence, any two TFNs with the same sizes of support intervals have the same entropies. Third, concerning two Triangular Fuzzy Sets （TFSs） with same sizes of support intervals and different heights, the relationship of their entropies lies on their height. Finally, we point it out a mistake that Chen＇s assertion that the entropy of resultant fuzzy set of elevation operation is directly to that of the original one while elevation factor just acts as a propartional factor. These results should contribute to the analysis and design of a fuzzy system.

关键词： fuzzy entropy membership function entropy function triangular fuzzy number support interval

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New Methods of Fitting the membership function of Oceanic Water Masses

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Journal of Ocean University of China 2004年第1期3卷 1-9页

作者： LIFengqi XIEJun LIYao CollegeofEnvironmentalScienceandEngineering OceanUniversityofChinaQingdao266003P.R.China

After reviewing the analytical theories of T S curve, some methods of T S relationship, and fuzzy sets for studying water masses, new methods of fitting the membership function of oceanic water masses are presented based on the characteristics of T S curve family of oceanic water masses. The membership functions of oceanic Subsurface Water Mass with high salinity and Intermediate Water Mass with low salinity are fitted and discussed using the new methods. The proposed methods are useful in analyzing the mixing and modifying processes of these water masses, especially in tracing their sources. The principles and formulae of the new methods and examples are given.

关键词： water mass T-S curve fuzzy sets membership function the South China Sea (SCS) Bashi Channel (Luzon Strait)

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Describing Fuzzy membership function and Detecting the Outlier by Using Five Number Summary of Data

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American Journal of Computational Mathematics 2020年第3期10卷 410-424页

作者： Md. Farooq Hasan Md. Abdus Sobhan Department of Mathematics and Statistics Bangladesh University of Business and Technology Dhaka Bangladesh

One of the most important activities in data science is defining a membership function in fuzzy system. Although there are few ways to describe membership function like artificial neural networks, genetic algorithms etc.;they are very complex and time consuming. On the other hand, the presence of outlier in a data set produces deceptive results in the modeling. So it is important to detect and eliminate them to prevent their negative effect on the modeling. This paper describes a new and simple way of constructing fuzzy membership function by using five-number summary of a data set. Five states membership function can be created in this new method. At the same time, if there is any outlier in the data set, it can be detected with the help of this method. Usually box plot is used to identify the outliers of a data set. So along with the new approach, the box plot has also been drawn so that it is understood that the results obtained in the new method are accurate. Several real life examples and their analysis have been discussed with graph to demonstrate the potential of the proposed method. The results obtained show that the proposed method has given good results. In the case of outlier, the proposed method and the box plot method have shown similar results. Primary advantage of this new procedure is that it is not as expensive as neural networks, and genetic algorithms.

关键词： Fuzzy Set membership function Five Number Summary Outliers

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Robust Fuzzy Association Rule Mining Based on Neighbors-Considered Clustering with Amended membership function

Robust Fuzzy Association Rule Mining Based on Neighbors-Cons...

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第40届中国控制会议

作者： Jinxian Wu Li Dai Weidong Zou Yuanqing Xia School of Automation Beijing Institute of Technology

Clustering based association rule mining algorithms usually deal with data sets by clustering numerical transactions into boolean ones then using the boolean method. However, the numerical data will often change slightly, which may be caused by errors in the data acquisition process or disturbance in the environment, as a result, the obtained association rules will change greatly. Therefore, the uncertainty in the association rule mining should be considered. In this paper, an improved fuzzy clustering based robust association rule mining algorithm（RFARM） is proposed, where a regularization term is added into the objective function in which each point considers its own k-nearest neighbors to offset small disturbance and we also derive the necessary conditions for the convergence to the local minimum. Meanwhile, fuzzy clustering methods with constraints produce ripple parts in membership functions, which cannot be explained in association rule mining. In order to solve this, we design a variant algorithm（RFARM*） that can perform and be understood better than the frequently-used methods. Experimental results have shown that the proposed methods are superior in the accuracy of association rules and the anti-noise capability.

关键词： Fuzzy association rule mining Data mining Fuzzy C Means membership function

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Design and experimental research on the sweet potato seedling transplanting mechanism of the planetary gear train with deformed elliptical gear transmission

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International Journal of Agricultural and Biological Engineering 2024年第3期17卷 91-99页

作者： Bingliang Ye Yuxuan Ye Haili Zhou Gaohong Yu Xiong Zhao Bin Deng Faculty of Mechanical Engineering Zhejiang Sci-Tech UniversityHangzhou 310018China Zhejiang Province Key Laboratory of Transplanting Equipment and Technology Hangzhou 310018China Key Laboratory of Agricultural Equipment for Hilly and Mountainous Areas in Southeastern China(Co-construction by Ministry and Province) Ministry of Agriculture and Rural AffairsHangzhou 310018China

Aiming at the lack of suitable machines for sweet potato seedling transplanting in China,and according to the agronomic requirements for the horizontal insertion method of sweet potato seedling,a new sweet potato seedling transplanting mechanism of planetary gear train was proposed based on the non-uniform transmission of deformed elliptical *** working principle of the transplanting mechanism was analyzed,and the kinematics modeling and analysis of the mechanism were carried *** study established the numerical objectives of the transplanting mechanism and applied the theory of membership function to establish a mathematical model for the parameter-guided optimization design of the transplanting *** parameter-guided optimization design software was developed to obtain a set of optimal mechanism parameters that satisfied the motion trajectory of sweet potato transplanting and the posture of the transplanting *** on the optimized parameters,the structure of the transplanting mechanism was designed,and a virtual prototype of the mechanism was created,whereby a virtual motion simulation of the transplanting mechanism was conducted to verify the correctness of the kinematics model and design of the *** high-speed photographic kinematics test of the mechanism prototype and sweet potato seedling transplanting tests were conducted to test the mechanism’s kinematic characteristics and transplanting *** test results show that the test trajectory of the mechanism and test posture of the transplanting arm are almost consistent with the theoretical and simulation trajectory,meeting the agronomic requirements of the horizontal insertion method of sweet potato seedling;And when the rotary speed of the mechanism are 20 r/min and 30 r/min,the average success ratios of sweet potato seedlings transplanting are 90%and 82%,respectively,which prove the application feasibility of the mechanism in the practical machines.

关键词： sweet potato seedling transplanter transplanting mechanism deformed elliptical gear transmission kinematics analysis membership function optimization design

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Feature Selection Based on Adaptive Fuzzy membership functions

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自动化学报 2006年第4期32卷 496-503页

作者： XIE Yan-Tao SANG Nong ZHANG Tian-Xu Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074

Neuro-fuzzy(NF)networks are adaptive fuzzy inference systems(FIS)and have been applied to feature selection by some ***,their rule number will grow exponentially as the data dimension *** the other hand,feature selection algorithms with artificial neural networks(ANN)usually require normalization of input data,which will probably change some characteristics of original data that are important for *** overcome the problems mentioned above,this paper combines the fuzzification layer of the neuro-fuzzy system with the multi-layer perceptron(MLP)to form a new artificial neural ***,fuzzification strategy and feature measurement based on membership space are proposed for feature selection. Finally,experiments with both natural and artificial data are carried out to compare with other methods,and the results approve the validity of the algorithm.

关键词： membership function feature selection architecture pruning artificial neural networks

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Fuzz-classification(p,l)-Angel:An enhanced hybrid artificial intelligence based fuzzy logic for multiple sensitive attributes against privacy breaches

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Digital Communications and Networks 2023年第5期9卷 1131-1140页

作者： Tehsin Kanwal Hasina Attaullah Adeel Anjum Abid Khan Gwanggil Jeon Department of Computer Science COMSATS University IslamabadPakistan Department of Information Technology Quaid-e-Azam University IslamabadPakistan College of Science and Engineering School of Computing and MathsUniversity of DerbyDE221GBUK Department of Embedded Systems Engineering Incheon National UniversitySouth Korea

The inability of traditional privacy-preserving models to protect multiple datasets based on sensitive attributes has prompted researchers to propose models such as SLOMS,SLAMSA,(p,k)-Angelization,and(p,l)-Angelization,but these were found to be insufficient in terms of robust privacy and performance.(p,l)-Angelization was successful against different privacy disclosures,but it was not *** the best of our knowledge,no robust privacy model based on fuzzy logic has been proposed to protect the privacy of sensitive attributes with multiple *** this paper,we suggest an improved version of(p,l)-Angelization based on a hybrid AI approach and privacy-preserving approach like ***-classification(p,l)-Angel uses artificial intelligence based fuzzy logic for classification,a high-dimensional segmentation technique for segmenting quasi-identifiers and multiple sensitive *** demonstrate the feasibility of the proposed solution by modelling and analyzing privacy violations using High-Level Petri *** results of the experiment demonstrate that the proposed approach produces better results in terms of efficiency and utility.

关键词： Generalization Fuzzy-logic MSA Privacy disclosures membership function (p,l)-Angelization QT HLPN

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Reliability Evaluation of Two-Phase Degradation Process with a Fuzzy Change-Point

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Journal of Shanghai Jiaotong university(Science) 2022年第6期27卷 867-872页

作者： LIU Kai DANG Wei ZOU Tianji LÜCongmin LI Peng ZHANG Haitao Technology and Engineering Center for Space Utilization Chinese Academy of SciencesBeijing 100094China University of Chinese Academy of Sciences Chinese Academy of SciencesBeijing 100049China

For some products,degradation mechanisms change during testing,and therefore,their degradation patterns vary at different points in time;these points are called *** to the limitation of measurement costs,time intervals for degradation measurements are usually very long,and thus,the value of change-points cannot be ***,a certain degradation measurement is selected as the change-point in a two-phase degradation *** to the tendency of the two-phase degradation process,the change-point is probably located in the interval between two neighboring degradation measurements,and it is a fuzzy *** imprecision of the change-point may lead to the incorrect product’s reliability evaluation *** this paper,based on the fuzzy theory,a two-phase degradation model with a fuzzy change-point and a statistical analysis method are ***,a two-phase Wiener degradation model is developed according to the membership function of the ***,the reliability evaluation is carried out using maximum likelihood estimation and a fuzzy simulation ***,the proposed methodology is verified via a case *** results of the study show that the proposed methodology can achieve more believable reliability evaluation results compared with those of the conventional approach.

关键词： two-phase degradation Wiener process fuzzy change-point membership function reliability evaluation statistical analysis

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