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Current issues and future directions in evolutionary fuzzy systems research
2003
European Society for Fuzzy Logic and Technology
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Contributors to the special track on Evolutionary Fuzzy Systems at the EUSFLAT 2003 conference were asked to record their thoughts and ideas on the current state of evolutionary fuzzy systems research, ...
Evolutionary fuzzy systems should be viewed in a multi-objective optimization (MO) framework: there are many trade-offs to be made between possibly conflicting goals. ...
Multi-objective Optimization (MO) is a "burning" line within Evolutionary Computation because population-based algorithms are capable of capturing a set of non-dominated solutions in a single run of the ...
dblp:conf/eusflat/CarsePRGGJSCHGWGP03
fatcat:vegbyw37dregrbcfdpkucbjhwu
Engineering Evolutionary Intelligent Systems: Methodologies, Architectures and Reviews
[chapter]
2008
Studies in Computational Intelligence
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We also provide a review of some of the recent interesting evolutionary intelligent system frameworks reported in the literature. ...
In this Chapter, we illustrate the various possibilities for designing intelligent systems using evolutionary algorithms and also present some of the generic evolutionary design architectures that has ...
Juang and Chung [39] proposed a recurrent TakagiSugenoKang (TSK) fuzzy network design using the hybridization of a multi-group genetic algorithm and particle swarm optimization (R-MGAPSO). ...
doi:10.1007/978-3-540-75396-4_1
fatcat:xplkbxzk4vbpbmnp4zxrjomj3q
Special issue on "Genetic Fuzzy Systems: Recent Developments and Future Directions"
2008
Soft Computing - A Fusion of Foundations, Methodologies and Applications
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This edition process has been developed under the support of the EUSFLAT working group on ''Genetic Fuzzy Systems'' coordinated by the guest editors. ...
We sincerely thank Vincenzo Loia, Co-Editor-in-Chief of the Soft Computing journal, and Francisco Herrera, Area Editor of ''Genetic Algorithms and Genetic Fuzzy Systems'' in this journal, for providing ...
A multi-objective optimization approach is used to generate a range of interpretability-accuracy tradeoffs. ...
doi:10.1007/s00500-008-0358-0
fatcat:vi6stqg3urffbpayassamgsdh4
Multi-grid cellular genetic algorithm for optimizing variable ordering of ROBDDs
2012
2012 IEEE Congress on Evolutionary Computation
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This paper presents a cellular genetic algorithm for optimizing the variable order in Reduced Ordered Binary Decision Diagrams. The evolution process is inspired by a basic genetic algorithm. ...
The approach considers multiple parallel evolving grids. A similarity based communication protocol between clusters of individuals from parallel grids is defined. ...
Faijul Amin and Kazuyuki Murase, Design of a Self-Tuning Hierarchical Fuzzy Logic Controller for Nonlinear Swing Up and Stabilizing Control of Inverted Pendulum Tuesday, Hybrid, TuH 5-1, 16:10-17:10, Computational ...
doi:10.1109/cec.2012.6256590
dblp:conf/cec/RotaruB12
fatcat:4ly3nrktw5habc6lf5err7d5py
A Review on the Interpretability-Accuracy Trade-Off in Evolutionary Multi-Objective Fuzzy Systems (EMOFS)
2012
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To deal with this trade-off Multi-Objective Evolutionary Algorithms (MOEA) are frequently applied in the design of fuzzy systems. ...
This paper introduces and reviews the approaches to the issue of developing fuzzy systems using Evolutionary Multi-Objective Optimization (EMO) algorithms considering 'Interpretability-Accuracy Trade-off ...
In this, a hybrid algorithm is also proposed by the integration of a learning method of classification rules and a multi-objective genetic algorithm. ...
doi:10.3390/info3030256
fatcat:q6pac63qz5dwpceyg4qabxvjqi
Guest Editorial: Smart Fuzzy Optimization in Operational Research and Renewable Energy: Modeling, Simulation, and Application
2020
IEEE transactions on fuzzy systems
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In the article "Hybrid Microgrid Many-Objective Sizing Optimization With Fuzzy Decision," Cao et al. present an improved two-archive many-objective evolutionary algorithm based on fuzzy decisions to solve ...
The article "A Fuzzy Mining Approach for Energy Efficiency in a Big Data framework," by Fernandez-Basso et al. addresses discovery and exploitation of hidden information in collected data. ...
doi:10.1109/tfuzz.2020.3023572
fatcat:okpf5v6if5dz5d4azproy6ni5u
A Review of the Application of Multiobjective Evolutionary Fuzzy Systems: Current Status and Further Directions
2013
IEEE transactions on fuzzy systems
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The design of fuzzy systems has been successfully performed by applying evolutionary and, in particular, genetic algorithms, and recently this approach has been extended by using Multi-Objective Evolutionary ...
The hybridization between Multi-Objective Evolutionary Algorithms and fuzzy systems is currently known as Multi-Objective Evolutionary Fuzzy Systems. ...
These hybrid approaches are known as Multi-Objective Evolutionary Fuzzy Systems (MOEFSs). ...
doi:10.1109/tfuzz.2012.2201338
fatcat:yeqnj7oiwvcf5le5y4bveyv2jm
Multi-objective Evolutionary Fuzzy Systems
[chapter]
2011
Lecture Notes in Computer Science
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(a) Two-objective case (b) Three-objective case Weight vector MOEA/D: Multi-objective evolutionary algorithm based on decomposition by Zhang and Li (IEEE TEC 2007) New Trend in EMO Algorithm Design Hybrid ...
Fuzzy Sets & Systems. [4] Wang et al. (2005) Multi-objective hierarchical genetic algorithm for interpretable fuzzy rule-based knowledge extraction. ...
. • The quality measures selected as objectives: -Support (Sup c N) -Unusualness (WRA cc ) • To create an initial population whose size is prefixed by an external parameter. • A part of the population ...
doi:10.1007/978-3-642-23713-3_11
fatcat:si6yp6do7vfejfrjij2yg4i7vm
Recent progress in natural computation and knowledge discovery: an ICNC'09-FSKD'09 special issue
2010
Soft Computing - A Fusion of Foundations, Methodologies and Applications
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As a primer international forum for scientists and researchers to present the state of the art of neural computation, fuzzy computation, evolutionary computation, and other intelligent algorithms inspired ...
The paper by PeihanWen, Jian Zhou, and Li Zheng presents a modified hybrid method of spatial credibilistic clustering and particle swarm optimization for addressing the clustering problem with improved ...
The paper by Lei Zhang and Jun Ma proposes a new image annotation approach by incorporating word correlations into multi-class support vector machine. ...
doi:10.1007/s00500-010-0559-1
fatcat:mqsmq67nkraydes5px25tt7aia
Approaches to solve cell formation, machine layout and cell layout problem: A Review
2014
Transactions on Machine Learning and Artificial Intelligence
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Many approaches have been advocated by researchers to obtain better cell formation & layout design. ...
An attempt has been done in this paper to review such approaches based on heuristics, meta-heuristics, hybrid methods and exact solution methods developed by past researchers to solve these problems. ...
Multi-objective design methodology The application of recently developed multi-objective intra-cell layout & inter-cell layout designs methodologies in a cellular manufacturing was presented in [53] ...
doi:10.14738/tmlai.25.600
fatcat:lojcd2i4fvdxfh6us6ur7lwpdy
A Multi-Agent Architecture for the Design of Hierarchical Interval Type-2 Beta Fuzzy System
2019
IEEE transactions on fuzzy systems
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The main function of the structure agent is to perform a multi-objective evolutionary structure learning step by means of the Multi-Objective Immune Programming algorithm (MOIP). ...
For the system design, a tree-based encoding method is adopted to hierarchically link low dimensional fuzzy systems. ...
doi:10.1109/tfuzz.2018.2871800
fatcat:gzjgded3xzclpmofyeqjktul7a
Ten years of genetic fuzzy systems: current framework and new trends
2004
Fuzzy sets and systems (Print)
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After a brief introduction to models and applications of genetic fuzzy systems, the ÿeld is overviewed, new trends are identiÿed, a critical evaluation of genetic fuzzy systems for fuzzy knowledge extraction ...
The objective of this paper is to provide an account of genetic fuzzy systems, with special attention to genetic fuzzy rule-based systems. ...
The parameters of the model are identiÿed by a hybrid GA, that combines global evolutionary search with a local hill-climbing technique. ...
doi:10.1016/s0165-0114(03)00111-8
fatcat:ctct6xyh6zekfnovveirqbajbu
Progress in on-line adaptive, learning and evolutionary strategies for fuzzy logic control
1999
Proceedings of the IEEE 1999 International Conference on Power Electronics and Drive Systems. PEDS'99 (Cat. No.99TH8475)
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Abstracli -In this paper, the eight kinds of on-line adaptive, learning ansd evolutionary strategies for fuzzy logic control are systematicallly introduced. ...
Hence a systematic way of combination and hybridizaticin of these strategies will be very useful for improving the learning capacity and performance of algorithms based on these strategies. ...
The latter is designed to minimize an H2-performance objective. ...
doi:10.1109/peds.1999.792863
fatcat:wjwgvmbyzzcadm7d74gqh7onoe
Introduction to the Special Issue on Nature-Inspired Optimization Methods in Fuzzy Systems
2020
IEEE transactions on fuzzy systems
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The article "A new type of fuzzy rule-based system with chaotic swarm intelligence for multi-classification of pain perception from fMRI" by Anter et al. presents a new fuzzy rule based hybrid optimization ...
Five alternative fuel vehicles, such as diesel, hybrid, electric, CNG, and biodisel, are evaluated using fuzzy hierarchical technique for order preference by similarity to ideal solution. ...
doi:10.1109/tfuzz.2020.2983712
fatcat:3xvjzkaagvernkwv4zs3xsptfy
Evolutionary swarm cooperative optimization in dynamic environments
2009
Natural Computing
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D Lim, YS Ong, Y Jin, B Sendhoff, BS Lee, Inverse multi-objective robust evolutionary design-Genetic Programming and …, 2006 -Springer AM Brintrup, H Takagi, The effect of user interaction mechanisms in ...
Fuzzy-genetic approach to recommender systems based on a novel hybrid user … MYH Al-
Shamri, KK Bharadwaj -Expert Systems with Applications, 2008 -Elsevier
33. ...
doi:10.1007/s11047-009-9129-9
fatcat:2qyicwkcfzatxcsrepp3ljxii4
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