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Optimization of multi-holes drilling path using particle swarm optimization
Published 2022“…This research aims to model and optimise multi-hole drilling problems using Particle Swarm Optimisation (PSO) algorithm. …”
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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“…Also, many of these PSO algorithms employed hybrid methods that integrate other optimisation algorithms with the standard PSO. …”
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Using the bees algorithm to optimise a support vector machine for wood defect classification
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An improved leader particle swarm optimisation algorithm for solving flexible ac transmission systems optimisation problem in power system
Published 2014“…The results of applying improved leader PSO to IEEE 14 bus power system shows its significant outperformance over six other optimisation algorithms including conventional PSO, mutated PSO, enhanced PSO, harmony search,genetic algorithm and gravitational search algorithm. …”
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Hybrid genetic algorithm for uncapacitated university examination timetabling problem
Published 2015“…All proposed algorithms are coded in C using Microsoft Visual C++ 6.0 as the compiler. …”
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Optimized Cover Selection for Audio Steganography Using Multi-Objective Evolutionary Algorithm
Published 2023“…Therefore, this research proposed a new method for optimising cover audio selection for audio steganography using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which falls under the MOEA Pareto dominance paradigm. …”
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Plant leaf recognition algorithm using ant colony-based feature extraction technique
Published 2013“…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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Empowering cloud providers: optimised locust-inspired algorithm for SLA violation mitigation in green cloud computing
Published 2025“…It enhances the locust-inspired algorithm by integrating SLA-awareness and adaptive host classification and is evaluated using real workload traces in the CloudSim toolkit. …”
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah
Published 2022“…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisation Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). …”
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A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks
Published 2022“…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisation Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). …”
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Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani
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Hybrid genetic algorithm for university examination timetabling problem
Published 2016“…The main components of the genetic operators in a GA will be tested and the best combination of the genetic operators will be adopted to construct a Pure Genetic Algorithm (PGA). The PGA will then hybridised with three new local optimisation techniques, which will make up the HGA; to improve the solutions found. …”
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Efficient task scheduling strategies using symbiotic organisms search algorithm for cloud computing environment
Published 2022“…The SOS and its variants Discrete Symbiotic Organisms Search (DSOS) algorithm have been used to solve different optimisation problems including tasks scheduling in cloud computing environment where results obtained are promising in comparison with stateof- the-art metaheuristic algorithms. …”
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Mathematical Modelling and Optimisation of Hydrogen Production from Photo-Fermentation in Microbial Electrolysis Cell using Sago Waste with Neural Network Algorithm
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Final Year Project Report / IMRAD -
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Optimisation and control of fed-batch yeast production using q-learning
Published 2013“…The final yeast production using QL-optimised feeding profile is 20.86% higher compare to the nominal exponential feeding (EF), and 19.59% higher compare to EF with process disturbance. …”
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