Search Results - (( using function search algorithm ) OR ( sets optimization method algorithm ))
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1
Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy
Published 2014“…To overcome this problem, two successful swarm-intelligence-based global optimization algorithms, cuckoo search (CS) algorithm and wind driven optimization (WDO) for multilevel thresholding using Kapur’s entropy has been employed. …”
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Article -
2
Tree-based contrast subspace mining method
Published 2020“…Genetic algorithm has been widely used to find global solution to optimization and search problem. …”
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Thesis -
3
Comparative analysis of line search methods in the Steepest Descent algorithm for unconstrained optimization problems / Ahmad Zikri Shukeri, Puteri Qurratu Ain Megat Sulzamzamendi...
Published 2024“…This study focuses on "Comparative Analysis of Line Search Methods in SD Algorithm for Unconstrained Optimization Problems". …”
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Student Project -
4
Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…In the proposed HACPSO algorithm, initially accelerated particle swarm optimization (APSO) algorithm searches within the search space and finds the best sub-search space, and then the CS selects the best nest by traversing the sub-search space. …”
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5
Optimized processing of satellite signal via evolutionary search algorithm
Published 2000“…A combination of three methods, namely optimization, global random search and ambiguity function mapping has produced an efficient and robust mitigation technique. …”
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6
Application of Multi-objective Genetic Algorithm (MOGA) optimization in machining processes
Published 2020“…Multi-objectives Genetic Algorithm (MOGA) is one of many engineering optimization techniques, a guided random search method. …”
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Book Chapter -
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Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri
Published 2020“…In this research, the empirical experiments have been conducted for the five selected algorithms in the engineering optimization discipline, namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Ant Colony Optimization (ACO) and Artificial Immune System (AIS). …”
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9
Global gbest guided-artificial bee colony algorithm for numerical function optimization
Published 2018“…The two well-known honeybees-based upgraded algorithms, Gbest Guided Artificial Bee Colony (GGABC) and Global Artificial Bee Colony Search (GABCS), use the foraging behavior of the global best and guided best honeybees for solving complex optimization tasks. …”
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10
Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…The proposed CGWO and OBCGWO are then applied to select the relevant features from the original feature set. Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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11
Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems
Published 2010“…Most of the current methods of crossover determine o®spring by using a stochastic approach and without reference to the objective function with the result being that a potentially optimal solution could be lost through incorrect choices being made in the randomisation process. …”
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Thesis -
12
Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm
Published 2018“…In this research, swarming intelligence is used to solve optimisation problem. Grey Wolf Optimizer and Dragonfly Algorithm were chosen. …”
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Monograph -
13
Evaluation of Search Result of Document Search Based GA (DSEGA)
Published 2004“…Although i has become easier to collect and store information in document collections, it has become increasingly difficult to retrieve relevant information from these large document collections. Genetic algorithms describe a set of optimization techniques that given a goal or fitness function are used to search a space for optimal points. …”
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Thesis -
14
Modelling of multi-robot system for search and rescue
Published 2023“…This report focusses on developing a novel multi-robot path planning algorithm based on the Modified Particles Swarm Optimization (MPSO) algorithm for dynamic environments. …”
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Final Year Project / Dissertation / Thesis -
15
Curve fitting by rational cubic Bézier with C1 and G1 continuity using metaheuristics methods
Published 2019“…Rational cubic Bézier curves are used to approximate the data sets while minimizing the least-squares error function using different metaheuristics algorithms. …”
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Conference or Workshop Item -
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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…A statistical test was used to demonstrate the efficiency of the proposed algorithm over the compared methods. …”
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Thesis -
17
Crossover and mutation operators of real coded genetic algorithms for global optimization problems
Published 2016“…This study is primarily aimed at investigating two issues in genetic algorithm (GA) and one issue in conformational search (CS) problems. …”
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Thesis -
18
Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…These problems are known as discrete-valued optimal control problems. Most practical discrete-valued optimal control problems have multiple local minima and thus require global optimization methods to generate practically useful solutions. …”
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Thesis -
19
Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…In this study we show how to apply a particular class of optimization methods known as pattern search methods to address these challenges. …”
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Thesis -
20
A non-dominated sorting Differential Search Algorithm Flux Balance Analysis (ndsDSAFBA) for in silico multiobjective optimization in identifying reactions knockout
Published 2019“…Many methods consider growth coupling as the objective function, whereby it searches for mutants that maximise the growth and production rate. …”
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