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A Review on the Interpretability-Accuracy Trade-Off in Evolutionary Multi-Objective Fuzzy Systems (EMOFS)

Praveen Kumar Shukla, Surya Prakash Tripathi
2012 Information  
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  ...  The fine fuzzy partitions are used in the evolutionary multi-objective optimization for designing the fuzzy rule-based classifiers in [102] .  ... 
doi:10.3390/info3030256 fatcat:q6pac63qz5dwpceyg4qabxvjqi

Introduction to the special issue on evolutionary computer vision and image understanding

Gustavo Olague, Stefano Cagnoni, Evelyne Lutton
2006 Pattern Recognition Letters  
This approach to the design of vision systems seems to be on its way to be accepted as a standard technique in computer vision research.  ...  as a multi-agent system.  ... 
doi:10.1016/j.patrec.2005.07.013 fatcat:dm4s7rmifraelm755rxsy4ysjm

Engineering Evolutionary Intelligent Systems: Methodologies, Architectures and Reviews [chapter]

Ajith Abraham, Crina Grosan
2008 Studies in Computational Intelligence  
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  ...  We also provide a review of some of the recent interesting evolutionary intelligent system frameworks reported in the literature.  ...  The main focus was on designing evolutionary neural networks and evolutionary fuzzy systems.  ... 
doi:10.1007/978-3-540-75396-4_1 fatcat:xplkbxzk4vbpbmnp4zxrjomj3q

Foreword: Intelligent data analysis

S. Ventura, C. Romero, A. Abraham
2014 Journal of computer and system sciences (Print)  
We would also like to thank Professor Edward Blum (Editor-in-chief of the Journal of Computer and System Sciences) for the opportunity to edit this special issue and his guidance.  ...  The special issue is based on substantially extended and updated papers presented at the IEEE 11th International Conference on Intelligent Systems Design and Applications (ISDA-2011), that held in Cordoba  ...  The fourth paper titled "Hierarchical Multi-Label Classification Using Local Neural Networks" describes a classification local-based method named Hierarchical Multi-Label Classification with Local Multi-Layer  ... 
doi:10.1016/j.jcss.2013.03.003 fatcat:hadfhsmntzdelox7ffl2vkjsmu

Applications of evolutionary computation techniques to analog, mixed-signal and RF circuit design - an overview

E. Roca, M. Fakhfakh, R. Castro-Lopez, F. V. Fernandez
2009 2009 16th IEEE International Conference on Electronics, Circuits and Systems - (ICECS 2009)  
This paper reviews the application of evolutionary computation techniques to analog, mixed-signal and radiofrequency design problems.  ...  Design needs, limitations of existing approaches and open challenges are pointed out.  ...  BASIC EVOLUTIONARY COMPUTATION TECHNIQUES Evolutionary Computation (EC) is a very active research area of computer science [4] .  ... 
doi:10.1109/icecs.2009.5410987 dblp:conf/icecsys/RocaFCF09 fatcat:mbvieihpyjd5he37xog6c3igsm

Evolving artificial cell signaling networks using molecular classifier systems

James Decraene, George Mitchell, Barry McMullin
2006 Proceedings of the 1st international conference on Bio inspired models of network, information and computing systems - BIONETICS '06  
The MCS that we have designed is derived from Holland's Learning Classifier System.  ...  In this paper we present a novel evolutionary approach named Molecular Classifier System (MCS) to simulate such ACSNs.  ...  One way to design ACNs to carry out such complex operations is to use artificial evolutionary techniques.  ... 
doi:10.1145/1315843.1315851 dblp:conf/bionetics/DecraeneMM06 fatcat:j3owqahobjgjfjpxudkpkoc5ma

Evolving Artificial Cell Signaling Networks using Molecular Classifier Systems

James Decraene, George Mitchell, Barry McMullin
2006 2006 1st Bio-Inspired Models of Network, Information and Computing Systems  
The MCS that we have designed is derived from Holland's Learning Classifier System.  ...  In this paper we present a novel evolutionary approach named Molecular Classifier System (MCS) to simulate such ACSNs.  ...  One way to design ACNs to carry out such complex operations is to use artificial evolutionary techniques.  ... 
doi:10.1109/bimnics.2006.361815 fatcat:2nwmzltv3vg5pmfeohwxqnglfq

Data Mining by Symbolic Fuzzy Classifiers and Genetic Programming [chapter]

Suhail Owais, Pavel Krömer, Jan Platoš, Václav Snášel, Ivan Zelinka
2013 Advances in Intelligent Systems and Computing  
In this paper, we present an application of evolutionary-fuzzy classification technique for data mining, outline state of the art of related methods and draw future directions of the research.  ...  In the presented application, genetic programming was deployed to evolve a fuzzy classifier and an example of real world application was presented.  ...  Muni et al. (2006) [11] , proposed a methodology for online feature selection and classifier design using a multi-tree genetic programming based feature selection called GPmtfs.A simultaneous feature  ... 
doi:10.1007/978-3-642-33227-2_28 fatcat:6ef3rneuczayla6f27z5c5tova

Multi-grid cellular genetic algorithm for optimizing variable ordering of ROBDDs

Cristian Rotaru, Octav Brudaru
2012 2012 IEEE Congress on Evolutionary Computation  
The population evolves on a bidimensional grid and is implicitly organized in geographical clusters that present a form of structural similarity between individuals.  ...  A similarity based communication protocol between clusters of individuals from parallel grids is defined. The exchange of genetic material proves to considerably boost the quality of the solution.  ...  dynamic programming based on fuzzy critic estimator 389, Ni Zhen, He Haibo, Zhao Dongbin and Prokhorov Danil, Reinforcement Learning Control Based on Multi-Goal Representation Using Hierarchical Heuristic  ... 
doi:10.1109/cec.2012.6256590 dblp:conf/cec/RotaruB12 fatcat:4ly3nrktw5habc6lf5err7d5py

Evolutionary Machine Learning: A Survey

Akbar Telikani, Amirhessam Tahmassebi, Wolfgang Banzhaf, Amir H. Gandomi
2022 ACM Computing Surveys  
Evolutionary Computation (EC) approaches are inspired by nature and solve optimization problems in a stochastic manner.  ...  For each category, we discuss evolutionary machine learning in terms of three aspects: problem formulation, search mechanisms, and fitness value computation.  ...  Recommender systems in businesses, which can be constructed based on knowledge generated by EML techniques, use information discovery techniques to offer items to potential customers.  ... 
doi:10.1145/3467477 fatcat:o6m3nekqfnaudjnxxoeferhine

Role of Machine Learning Algorithms Intrusion Detection in WSNs: A Survey

Dr. E. Baraneetharan
2020 Journal of Information Technology and Digital World  
To secure data from attackers the WSNs system should be able to delete the instruction if any hackers/attackers are trying to steal data.  ...  Machine learning techniques survey for WSNs provide a wide range of applications in which security is given top priority.  ...  It also uses evolutionary computational techniques to deal with complex MANET environments.  ... 
doi:10.36548/jitdw.2020.3.004 fatcat:vub46pkvjjgnljaua4jougihw4

Evolutionary swarm cooperative optimization in dynamic environments

Rodica Ioana Lung, Dumitru Dumitrescu
2009 Natural Computing  
Dumitrescu, Exploring Population Geometry and Multi-Agent Systems: A New Approach to Developing Evolutionary Techniques, Genetic and Evolutionary Computation Conference GECCO'08, ACM, 1953-1959, July 12  ...  .; An Agent-based, Evolutionary Computation, 2009. CEC '09.  ... 
doi:10.1007/s11047-009-9129-9 fatcat:2qyicwkcfzatxcsrepp3ljxii4

Hierarchical Approach to Evolutionary Multi-Objective Optimization [chapter]

Eryk Ciepiela, Joanna Kocot, Leszek Siwik, Rafał Dreżewski
2008 Lecture Notes in Computer Science  
In this paper a new "hierarchical" evolutionary approach to solving multi-objective optimization problems is introduced.  ...  The results of experiments with standard multi-objective test problems, which were aimed at comparing "hierarchical" and "classical" versions of multiobjective evolutionary algorithms, show that the proposed  ...  During over 20 years of research on evolutionary multi-objective algorithms (EMOAs) quite many techniques have been proposed.  ... 
doi:10.1007/978-3-540-69389-5_82 fatcat:lzvache2ubg2dl23xlthslj4zm

2019 Index IEEE Transactions on Emerging Topics in Computational Intelligence Vol. 3

2019 IEEE Transactions on Emerging Topics in Computational Intelligence  
., +, TETCI June 2019 271-285 Evolutionary computation A Novel Portfolio Optimization Model Based on Trend Ratio and Evolutionary Computation.  ...  ., +, TETCI April 2019 93-105 Optical design techniques A Parallel Surrogate Model Assisted Evolutionary Algorithm for Electromagnetic Design Optimization.  ... 
doi:10.1109/tetci.2019.2960994 fatcat:2crjc5ajvzdxpj3g6nqmgkimpm

Hierarchical Bi-level Multi-Objective Evolution of Single- and Multi-layer Echo State Network Autoencoders for Data Representations [article]

Naima Chouikhi, Boudour Ammar, Adel M. Alimi
2018 arXiv   pre-print
In this paper, a hierarchical bi-level evolutionary optimization is proposed to deal with these issues.  ...  However, this randomly hand crafted task, on one hand, may not guarantee best training results and on the other hand, it can raise the network's complexity.  ...  Since this design is multi-constrained, a multi-objective optimization technique is used here which is MOPSO.  ... 
arXiv:1806.01016v2 fatcat:z3yfsvmp6jgbtfoemxquom73du
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