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Self-adaptive hybrid PSO-GA method for change detection under varying contrast conditions in satellite images

Huseyin Kusetogullari, Amir Yavariabdi
2016 2016 SAI Computing Conference (SAI)  
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

Mehdi Neshat, Nataliia Sergiienko, Seyedali Mirjalili, Meysam Majidi Nezhad, Giuseppe Piras, Davide Astiaso Garcia
2021 Energies  
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]

Jeannie M. Fitzgerald, R. Muhammad Atif Azad, Conor Ryan
2016 Studies in Computational Intelligence  
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

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.  ...  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

Dai-Duong Tran, Majid Vafaeipour, Mohamed El Baghdadi, Ricardo Barrero, Joeri Van Mierlo, Omar Hegazy
2019 Renewable & Sustainable Energy Reviews  
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

Zahra Rezaei, Ali Selamat, Arash Taki, Mohd Mohd Rahim, Mohammed Abdul Kadir, Marek Penhaker, Ondrej Krejcar, Kamil Kuca, Enrique Herrera-Viedma, Hamido Fujita
2018 Applied Sciences  
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

Shrutika Sawant, Manoharan Prabukumar
2020 Journal of Spectral Imaging  
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]

Mehmet Emin Aydin, Ryan Fellows
2018 arXiv   pre-print
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

Ajeet Singh, Anurag Jain
2019 International Journal of Security and Its Applications  
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

Adnan Mohsin Abdulazeez, Dathar A. Hasan, Awder Mohammed Ahmed, Omar S. Kareem
2021 Asian Journal of Research in Computer Science  
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

Laith Abualigah, Amir H. Gandomi, Mohamed Abd Elaziz, Husam Al Hamad, Mahmoud Omari, Mohammad Alshinwan, Ahmad M. Khasawneh
2021 Electronics  
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

Khurram Ejaz, Mohd Shafry, Amjad Rehman, Huma Chaudhry, Tanzila Saba, Anmol Ejaz, Chaudhry Farhan
2018 International Journal of Advanced Computer Science and Applications  
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

Sabu M. Thampi, El-Sayed M. El-Alfy, Sabu M. Thampi, El-Sayed M. El-Alfy
2017 Journal of Intelligent & Fuzzy Systems  
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)  
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

Giovanni Giambene, Boon Sain Yeo
2009 2009 International Workshop on Satellite and Space Communications  
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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