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Harmony search-based robust optimal controller with prior defined structure
Published 2013“…The second level compnses of two HS optimization algorithms developed and coded for robust stability examinations. …”
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Thesis -
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Bats echolocation-inspired algorithms for global optimisation problems
Published 2016“…The works related to swarm intelligence algorithms include the development of the algorithm itself, its modification and improvisation as well as its application in solving global optimisation problems. …”
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OPTIMIZATION OF PID CONTROLLER PARAMETERS USING ARTIFICIAL FISH SWARM ALGORITHM
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Improved particle swarm optimization by fast annealing algorithm
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Proceeding Paper -
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The fusion of particle swarm optimization (PSO) and interior point method (IPM) as cooperative movement control algorithm in Swarm Robotics / Dada Emmanuel Gbenga
Published 2016“…Research in Particle Swarm Optimisation and its applications to real world problems has become a very interesting field in recent years. …”
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Data Analysis using Particle Swarm Optimization Algorithm
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Application of Particle Swarm Optimization in Optimizing Stereo Matching Algorithm’s Parameters for Star Fruit Inspection System
Published 2014“…Based on this information, the particles will improve its position in the search space by moving towards its best record and the swarm best record. …”
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A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots
Published 2019“…As an algorithm, PSO can be applied to solve various function optimisation problems, as the main strength of the algorithm is its fast convergence [14]. …”
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Two objectives big data task scheduling using swarm intelligence in cloud computing
Published 2016“…It has been widely used for its enormous benefits and its ability to cope with large scale data such as workflows and big data applications. …”
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Crypt Edge Detection Using PSO,Label Matrix And BI-Cubic Interpolation For Better Iris Recognition(PSOLB)
Published 2017“…Recently,there has been renewed interest in iris features detection.Gabor filter,cross entrophy, upport vector,and canny edge detection are methods which produce iris codes in binary codes representation.However,problems have occurred in iris recognition since low quality iris images are created due to blurriness,indoor or outdoor settings, and camera specifications.Failure was detected in 21% of the intra-class comparisons cases which were taken between intervals of three and six months intervals.However,the mismatch or False Rejection Rate (FRR) in iris recognition is still alarmingly high.Higher FRR also causes the value of Equal Error Rate (EER) to be high.The main reason for high values of FRR and EER is that there are changes in the iris due to the amount of light entering into the iris that changes the size of the unique features in the iris.One of the solutions to this problem is by finding any technique or algorithm to automatically detect the unique features.Therefore a new model is introduced which is called Crypt Edge Detection which combines PSO,Label Matrix,and Bi-Cubic Interpolation for Iris Recognition (PSOLB) to solve the problem of detection in iris features.In this research, the unique feature known as crypts has been chosen due to its accessibility and sustainability.Feature detection is performed using particle swarm optimisation (PSO) as an algorithm to select the best iris texture among the unique iris features by finding the pixel values according to the range of selected features.Meanwhile, label matrix will detect the edge of the crypt and the bi-cubic interpolation technique creates sharp and refined crypt images.In order to evaluate the proposed approach,FAR and FRR are measured using Chinese Academy of Sciences' Institute of Automation (CASIA) database for high quality images.For CASIA version 3 image databases, the crypt feature shows that the result of FRR is 21.83% and FAR is 78.17%.The finding from the experiment indicates that by using the PSOLB,the intersection between FAR and FRR produces the Equal Error Rate (EER) with 0.28%,which indicated that equal error rate is lower than previous value, which is 0.38%.Thus,there are advantages from using PSOLB as it has the ability to adapt with unique iris features and use information in iris template features to determine the user.The outcome of this new approach is to reduce the EER rates since lower EER rates can produce accurate detection of unique features.In conclusion,the contribution of PSOLB brings an innovation to the extraction process in the biometric technology and is beneficial to the communities.…”
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Thesis -
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Swarm Intelligence Based Protein Conformational Search Algorithm.
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Facial emotion detection using GPSO and Lucas-Kanade algorithms
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Advances in Particle Swarm Algorithms in Asynchronous, Discrete and Multi-Objective Optimization
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
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Asynchronous particle swarm optimization for swarm robotics
Published 2012“…Hence this paper looks into the differences between synchronous and asynchronous PSO and its application in swarm robotics search.…”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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