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Self-adaptive hybrid PSO-GA method for change detection under varying contrast conditions in satellite images
2016
2016 SAI Computing Conference (SAI)
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The purpose of using Self-Adaptive Hybrid Particle Swarm Optimization-Genetic Algorithm (SAPSOGA) is to combine two meta-heuristic optimization algorithms to search and find the feasible solution in the ...
Then, we use the corrected input data to define a new fitness function based on the difference image. ...
Self-Adaptive Hybrid Particle Swarm Optimisation-Genetic Algorithm (SAPSOGA) In the proposed method, binary based SAPSOGA is used to optimise the change detection problem to find the final change detection ...
doi:10.1109/sai.2016.7556007
fatcat:vl7m2nh7ezgkvebzdu6s3q5cvi
Multi-Mode Wave Energy Converter Design Optimisation Using an Improved Moth Flame Optimisation Algorithm
2021
Energies
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bio-inspired swarm-evolutionary optimisation algorithms based on a sample wave regime at a site in the Mediterranean Sea, in the west of Sicily, Italy. ...
An improved version of a recent optimisation algorithm, called the Moth–Flame Optimiser (MFO), is also proposed for this application area. ...
[30] proposed a bi-level optimisation algorithm that consists of Grey Wolf Optimiser [21] (GWO) and a self-adaptive differential evolution with ensemble sinusoidal parameter adaptation called LSHADE-EpSin ...
doi:10.3390/en14133737
fatcat:4iqj7qxkvfdc7phbxdejuqq2ke
GEML: A Grammatical Evolution, Machine Learning Approach to Multi-class Classification
[chapter]
2016
Studies in Computational Intelligence
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We investigate the effectiveness of GEML on several supervised, semi-supervised and unsupervised multiclass problems and demonstrate its competitive performance when compared with several well known machine ...
The method, Grammatical Evolution Machine Learning (GEML) adapts machine learning concepts from decision tree learning and clustering methods and integrates these into a Grammatical Evolution framework ...
In that work, particle swarm optimisation (PSO) was used to generate a mapping which had some similarities to a type of artificial neural network known as a self organising map. ...
doi:10.1007/978-3-319-48506-5_7
fatcat:jz33vloqcbbfdjwmayfcsmwyma
Multi-grid cellular genetic algorithm for optimizing variable ordering of ROBDDs
2012
2012 IEEE Congress on Evolutionary Computation
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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. ...
and Self-Adaptive French Flag Organism Based on Lateral Activation Model 393, Jun-Wei Qiu, John K. ...
doi:10.1109/cec.2012.6256590
dblp:conf/cec/RotaruB12
fatcat:4ly3nrktw5habc6lf5err7d5py
Thorough state-of-the-art analysis of electric and hybrid vehicle powertrains: Topologies and integrated energy management strategies
2019
Renewable & Sustainable Energy Reviews
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A R T I C L E I N F O Keywords: Plug-in hybrid electric vehicle Full-electric vehicle Energy management strategy optimisation Online EMS Offline EMS Optimal control strategy A B S T R A C T Hybrid and ...
Adaptive fuzzy logic control. Adaptive algorithms are integrated in an FL-RB strategy to improve its self-adaption. Regarding the (P)HEV, Saeks et al. ...
A knowledge-based control strategy based on a fuzzy c-means clustering algorithm will be trained throughout all the driving cycles. ...
doi:10.1016/j.rser.2019.109596
fatcat:ybks774km5htvb6f7foyetum7m
Thin Cap Fibroatheroma Detection in Virtual Histology Images Using Geometric and Texture Features
2018
Applied Sciences
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To more accurately segment VH-IVUS images, a semi-supervised model is developed by means of hybrid K-means with Particle Swarm Optimisation (PSO) and a minimum Euclidean distance algorithm (KMPSO-mED). ...
TCFA detection has only focused on the geometric features. ...
This algorithm has five important parameters, as presented in Table 2 . Table 2 . PSO parameters. ...
doi:10.3390/app8091632
fatcat:llzdi7ctwrf6pcufgslt76a4cm
A survey of band selection techniques for hyperspectral image classification
2020
Journal of Spectral Imaging
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Focusing on the classification task, this article provides an extensive and comprehensive survey on band selection techniques describing the categorisation of methods, methodology used, different searching ...
Genetic Algorithms (GA), Particle Swarm Optimisation (PSO), Cuckoo Search (CS) optimisation algorithm, Grey Wolf Optimisation (GWO), Differential Evolution (DE) and so on. 29,81-84 These methods consider ...
Band selection based on availability of prior information Based on the availability of prior information, the band selection techniques are categorised as supervised band selection, 30, 35, 39, 40 semi-supervised ...
doi:10.1255/jsi.2020.a5
fatcat:cvibjoofbbd6jpu4ij626wigdy
A reinforcement learning algorithm for building collaboration in multi-agent systems
[article]
2018
arXiv
pre-print
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Particles are devised with Q learning algorithm for self training to learn how to act as members of a swarm and how to produce collaborative/collective behaviours. ...
This paper presents a proof-of concept study for demonstrating the viability of building collaboration among multiple agents through standard Q learning algorithm embedded in particle swarm optimisation ...
Particle swarm optimisation (PSO) PSO is a population-based optimization technique inspired of social behaviour of bird flocking and fish schooling. ...
arXiv:1711.10574v2
fatcat:kqoshzk77bdvld75cia3h3ko7m
Financial Fraud Detection using Bio-Inspired Key Optimization and Machine Learning Technique
2019
International Journal of Security and Its Applications
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In this paper, new FF detection model has been proposed for accurate detect financial frauds using one of the Bio-inspired optimization algorithms as particle swarm optimization (PSO), feature selection ...
The findings of this study clearly illustrate that the Bioinspired algorithm (PSOS) gives more appropriate results compared with the non-Bio-inspired algorithm (RIG). ...
The MLTs are three types of learning approaches like Supervised Learning, Unsupervised Learning, and Semi-Supervised Learning. ...
doi:10.33832/ijsia.2019.13.4.08
fatcat:4n7om7c6nrf5fo3tkzgyv5hgom
Swarm Intelligence-Based Feature Selection for Multi-Label Classification: A Review
2021
Asian Journal of Research in Computer Science
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To this end, in this review, we have investigated most of the well-known and state-of-the-art methods and categorize them based on different perspectives. ...
After reviewing various researches, it seems there are no researches that provide a review of swarm intelligence-based methods for multi-label feature selection. ...
Swarm intelligence feature algorithm based on graph clustering and selection based on max- Based Systems. 2020;187:104823. algorithms in gene selection profile based dependency ant colony optimization. ...
doi:10.9734/ajrcos/2021/v9i430230
fatcat:mmkvev4hmrbrdl2eg6iwzufo7u
Advances in Meta-Heuristic Optimization Algorithms in Big Data Text Clustering
2021
Electronics
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This paper presents a comprehensive survey of the meta-heuristic optimization algorithms on the text clustering applications and highlights its main procedures. ...
This paper reviews all of the relevant literature on meta-heuristic-based text clustering applications, including many variants, such as basic, modified, hybridized, and multi-objective methods. ...
He-Nian et al. recommended a procedure called OK-PSO [52] to cluster text based on k-means (KM) and a PSO algorithm. ...
doi:10.3390/electronics10020101
fatcat:fb3sopje4fegphs5b6g673ipqa
Segmentation Method for Pathological Brain Tumor and Accurate Detection using MRI
2018
International Journal of Advanced Computer Science and Applications
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Then to classify tumor for segmentation hybrid Fuzzy K Mean-Self Organization Mapping (FKM-SOM) for variation of intensities is used. ...
Thirteen features from every image of dataset have been classified for accuracy using Support Vector Machine (SVM) kernel classification (RBF, linear, polygon) so results have been achieved using evaluation parameters ...
Magnetic Resonance Brain Image has been classified based on Adaptive Chaotic PSO [2] . ...
doi:10.14569/ijacsa.2018.090851
fatcat:gyd2pbgdjfggfd3dlb7wn7wbym
Special issue on soft computing and intelligent systems: Tools, techniques and applications
2017
Journal of Intelligent & Fuzzy Systems
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In [1], a classification system that combines feature selection techniques with semi-supervised fuzzy * Corresponding author. Sabu M. ...
In [2], a new texture-based feature extraction algorithm is proposed for extracting relevant and informative features from brain MR images having tumor. ...
In [1] , a classification system that combines feature selection techniques with semi-supervised fuzzy c-means (FCM) algorithm is proposed and evaluated on publicly available gene expression datasets. ...
doi:10.3233/jifs-169221
fatcat:f43kb5ygbfhlho5cfwogbcyegq
Table of Contents
2020
2020 IEEE Symposium Series on Computational Intelligence (SSCI)
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for Positional-based UAS Missions Bradley Fraser, Claudia Szabo, Andrew Coyle and Robert Hunjet .......... 2584 Self-Adaptation of Meta-Parameters for Lamarckian-Inherited Neuromodulated Neurocontrollers ...
Lam
.......... 1794
Autonomous decision making by the self-generated priority under multi-task
Takuma Kambayashi and Kentarou Kurashige
.......... 1879
xxxi
Self-generation of reward based on sensor ...
doi:10.1109/ssci47803.2020.9308155
fatcat:hyargfnk4vevpnooatlovxm4li
Welcome message from the General Chairs
2009
2009 International Workshop on Satellite and Space Communications
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Based on these rigorous reviews, IES 2014 accepted 106 papers for inclusion in the conference program, which represents an acceptance rate of 69%. ...
All accepted papers will be included in the Proceeding of Adaptation, Learning and Optimization Series published by Springer-Verlag. ...
Keywords: Differential evolution, Covariance adaptation matrix evolution strategy, Genetic algorithm, Self-adaptation. ...
doi:10.1109/iwssc.2009.5286448
fatcat:wcu4uzasizhzjmdkzyekynnqwi
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