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Overview of Particle Swarm Optimisation for Feature Selection in Classification [chapter]

Binh Tran, Bing Xue, Mengjie Zhang
2014 Lecture Notes in Computer Science  
Particle swarm optimisation (PSO) is an EC technique which recently has caught much interest from researchers in the field.  ...  This paper presents a review of PSO for feature selection in classification. After describing the background of feature selection and PSO, recent work involving PSO for feature selection is reviewed.  ...  Particle Swarm Optimisation Continuous Particle Swarm Optimisation Particle swarm optimisation (PSO) is an evolutionary computation technique proposed by Kennedy and Eberhart in 1995 [12,17] .  ... 
doi:10.1007/978-3-319-13563-2_51 fatcat:ju3w5orwmng5vppfoxhhpkdmoa

Overview on Binary Optimisation using Swarm-inspired Algorithms

Mariana Macedo, Hugo Siqueira, Elliackin Figueiredo, Clodomir Santana, Rodrigo C. Lira, Anuradha Gokhale, Carmelo Bastos-Filho
2021 IEEE Access  
is more efficient for binary optimisation in accuracy and computational cost.  ...  Swarm Intelligence is applied to optimisation problems due to its robustness, scalability, generality, and flexibility.  ...  [200] have proposed a new hybrid method called Binary Particle Swarm Optimization Differential Evolution (BPSODE) to solve feature selection problem in EMG signals classification.  ... 
doi:10.1109/access.2021.3124710 fatcat:v7heosioojg3pcwpswm3yvmrmy

Multi-objective particle swarm optimisation (PSO) for feature selection

Bing Xue, Mengjie Zhang, Will N. Browne
2012 Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference - GECCO '12  
Based on particle swarm optimisation (PSO), this paper proposes two multi-objective algorithms for selecting the Pareto front of non-dominated solutions (feature subsets) for classification.  ...  The second new algorithm outperforms the first algorithm in both continuous and binary versions.  ...  in nonDomS according to the crowding distance; copy all the particles in Swarm to a form temporary swarm (temSwarm); for i=1 to Population Size (P ) do update the pbest of particle i; randomly selecting  ... 
doi:10.1145/2330163.2330175 dblp:conf/gecco/XueZB12 fatcat:edfftdfhrjao5kegzjn6p2glqi

Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation

Hazlee Azil Illias, Wee Zhao Liang, Xiangtao Li
2018 PLoS ONE  
In this work, a hybrid support vector machine (SVM) with modified evolutionary particle swarm optimisation (EPSO) algorithm was proposed to determine the transformer fault type.  ...  OPEN ACCESS Citation: Illias HA, Zhao Liang W (2018) Identification of transformer fault based on dissolved gas analysis using hybrid support vector machine-modified evolutionary particle swarm optimisation  ...  Acknowledgments The authors thank the Ministry of Higher Education Malaysia and University of Malaya, Malaysia for supporting this work through HIR research grant (grant no.: H-16001-D00048) and PPP (grant  ... 
doi:10.1371/journal.pone.0191366 pmid:29370230 pmcid:PMC5784944 fatcat:dizhasgd2rbxlp354szijgrnpe

Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques

Hazlee Azil Illias, Xin Rui Chai, Ab Halim Abu Bakar, Hazlie Mokhlis, Daqing Li
2015 PLoS ONE  
Since artificial neural network (ANN) and particle swarm optimisation (PSO) techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques  ...  However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions.  ...  Acknowledgments The authors thank the Malaysian Ministry of Education and University of Malaya, Malaysia for supporting this work through HIR research grant (grant no.: H-16001-D00048).  ... 
doi:10.1371/journal.pone.0129363 pmid:26103634 pmcid:PMC4478012 fatcat:gqflpwrvf5ddzbxas5v3qljeam

Bare-Bone Particle Swarm Optimisation for Simultaneously Discretising and Selecting Features for High-Dimensional Classification [chapter]

Binh Tran, Bing Xue, Mengjie Zhang
2016 Lecture Notes in Computer Science  
In this study, we propose a new method called PSO-DFS using bare-bone particle swarm optimisation (BBPSO) for discretisation and feature selection in a single stage.  ...  These techniques are usually applied in two stages, discretisation and then selection since many feature selection methods work only on discrete features.  ...  Particle Swarm Optimisation PSO [10] is a population-based algorithm proposed by Kennedy and Eberhart in 1995.  ... 
doi:10.1007/978-3-319-31204-0_45 fatcat:rkkarz54mncwbnpe6r675dlpya

Continuous presentation for multi-objective channel selection in Brain-Computer Interfaces

Noura Al Moubayed, Bashar Awwad Shiekh Hasan, John Q. Gan, Andrei Petrovski, John McCall
2012 2012 IEEE Congress on Evolutionary Computation  
A multi-objective particle swarm optimization method (D 2 M OP SO) is employed where particles move in the EEG cap space to locate the optimum set of solutions that minimize the number of selected channels  ...  In addition continuous presentation is a more natural way for problem solving in PSO framework. The method is validated on 10 subjects performing right-vs-left motor imagery BCI.  ...  In [11] a mixture of CSP and PSO based method was used for channel selection. In [12] , [13] Sequential Floating Forward Search (SFFS) based methods were employed for channel/feature selection.  ... 
doi:10.1109/cec.2012.6252991 dblp:conf/cec/MoubayedHGPM12 fatcat:bsh3jxuyivcybiq4jcu5qcqksu

Research on parameters optimisation of SVM based on swarm intelligence

Shifei Ding, Huajuan Huang
2014 International Journal of Collaborative Intelligence  
At present, swarm intelligence is the most common method to optimise the parameters of SVM.  ...  Secondly, we describe the latest progress of parameters optimisation of SVM based on swarm intelligence in recent years.  ...  In literature (Yang et al., 2009 ), a chaotic adaptive particle swarm optimisation (CAPSO) method was applied to select parameters of SVM and genetic characteristics of the subset of choices (GA_FSS)  ... 
doi:10.1504/ijci.2014.064852 fatcat:rrm56gksfzapjkfx6eke64dzmm

New fitness functions in binary particle swarm optimisation for feature selection

Bing Xue, Mengjie Zhang, Will N. Browne
2012 2012 IEEE Congress on Evolutionary Computation  
This paper proposes two new fitness functions in binary particle swarm optimisation (BPSO) for feature selection to choose a small number of features and achieve high classification accuracy.  ...  They outperform two conventional feature selection methods in almost all cases.  ...  [21] propose a wrapper feature selection method in which BPSO is used to search the optimal subset of features and continuous PSO is used to simultaneously optimise the parameters in the kernel function  ... 
doi:10.1109/cec.2012.6256617 dblp:conf/cec/XueZB12 fatcat:ex6parjjovd4xg2xsk7ycpbwpe

A novel two‐stage Dissolved Gas Analysis fault diagnosis system based semi‐supervised learning

Xuemin Tan, Chao Guo, Ke Wang, Fu Wan
2022 High Voltage  
transformer fault diagnosis model based improved Artificial Fish Swarm Algorithm (AFSA) and SVM (SSL-IAFSA-SVM) for optimising the SVM parameter.  ...  Dissolved Gas Analysis (DGA) is an important method for oil-immersed transformer fault diagnosis.  ...  ) and some conventional optimisation methods combined SSL such as SSL-PSO-SVM (SSL optimised SVM classifier based particle swarm optimisation), SSL-GA-SVM (SSL optimised SVM classifier based genetic algorithm  ... 
doi:10.1049/hve2.12195 fatcat:5cfi5xtrszfm5a6i7c4srw5jwq

PSO for feature construction and binary classification

Bing Xue, Mengjie Zhang, Yan Dai, Will N. Browne
2013 Proceeding of the fifteenth annual conference on Genetic and evolutionary computation conference - GECCO '13  
Particle swarm optimisation (PSO) is a powerful search technique, but has never been applied to feature construction.  ...  This paper represents the first study on using PSO for feature construction in classification.  ...  BACKGROUND Particle Swarm Optimisation (PSO) Particle Swarm Optimisation (PSO) [11, 22] is an evolutionary computation technique.  ... 
doi:10.1145/2463372.2463376 dblp:conf/gecco/XueZDB13 fatcat:xtunk2i3rzcunoijxepay62z5e

Applying particle swarm optimization-based decision tree classifier for wart treatment selection

Junhua Hu, Xiangzhu Ou, Pei Liang, Bo Li
2021 Complex & Intelligent Systems  
The proposed method classifies better than k-nearest neighbour, C4.5 and logistic regression. It also performs better than the conventional optimisation method for the CART algorithm.  ...  This paper establishes a classification and regression tree (CART) model based on particle swarm optimisation to help patients choose between immunotherapy and cryotherapy.  ...  Acknowledgements The authors would like to thank Editor-in-Chief, editor, and anonymous reviewers for their valuable comments and helpful suggestions.  ... 
doi:10.1007/s40747-021-00348-3 fatcat:lxp6gjukifartm4d4gylca2uqe

Determination of Basic Reservoir Parameters in Shale Formations as a Solution of Inverse Problem in the Computer Assisted History Matching of their Simulation Models. Part II – Hybrid Optimization Algorithm

Piotr Łętkowski, Wiesław Szott
2016 Nafta - gaz : miesiecznik poswiecony nauce i technice w przemysle  
One of the stochastic sampling method used and presented in the paper is the method of Particle Swamp Optimization (PSO).  ...  The selection of an appropriate global optimization method is crucial in the situation of many expected local minima of the problem.  ...  In the form presented above the particle swarm optimisation is the basic optimisation method of the presented algorithm.  ... 
doi:10.18668/ng.2016.10.06 fatcat:id5m2asnmbfu7gqcinvnfb7vgu

Particle Swarm Optimised polynomial neural network for classification: a multi-objective view

S. Dehuri, A. Ghosh, S B. Cho
2008 International Journal of Intelligent Defence Support Systems  
Using these two metrics as the objectives of classification problem, this paper uses a Pareto based Particle Swarm Optimisation (PPSO) technique to find out a set of non-dominated solutions with less complex  ...  The proposed method is used to train PNN through simultaneous optimisation of topological structure and weights.  ...  Acknowledgements Authors would like to thank the Department of Science and Technology, Government of India, for the financial support under the BOYSCAST fellowship 2007-2008 and BK21 research program on  ... 
doi:10.1504/ijidss.2008.023008 fatcat:omoj4yw7zbcypnho6r3k2msqmi

A Particle Swarm Optimisation Based Multi-objective Filter Approach to Feature Selection for Classification [chapter]

Bing Xue, Liam Cervante, Lin Shang, Mengjie Zhang
2012 Lecture Notes in Computer Science  
Based on binary particle swarm optimisation (BPSO), we develop a multi-objective FS framework for classification, which is NSBPSO based on multi-objective BPSO using the idea of non-dominated sorting.  ...  Feature selection (FS) has two main objectives of minimising the number of features and maximising the classification performance.  ...  This work is supported in part by the National Science Foundation of China (NSFC No. 61170180) and the Marsden Fund of New Zealand (VUW0806).  ... 
doi:10.1007/978-3-642-32695-0_59 fatcat:ijyf3zdunrdwjidpuyf4jiinda
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