Search Results - (( swarm optimization method algorithm ) OR ( program implementation method algorithm ))
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1
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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2
Modification of particle swarm optimization algorithm for optimization of discrete values
Published 2011“…Among the stochastic optimization methods is Particle Swarm Optimization (PSO). …”
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Research Reports -
3
A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali
Published 2015“…In this thesis, we implement the modified ant colony programming (ACP) algorithm for solving the matrix Riccati differential equation (MRDE). …”
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4
Coordination of PSS and PID controller for power system stability enhancement - overview
Published 2023“…This paper broadly reviews the optimization methods and algorithms such as Conventional methods, Soft Computing, Genetic Algorithm (GA), Evolutionary Programming (EP), Differential Evolution (DE) and Swarm Intelligence methods were available for tuning the PID gains and PSS parameters successfully. …”
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A review on the applications of PSO-based algorithm in demand side management: Challenges and opportunities
Published 2023“…Owing to its simplicity and consistent performance in fast convergence time, Particle Swarm Optimization (PSO) is widely used as a part of the swarm AI algorithm and has become a prominent technique in the optimization process to exploit the full benefit of the demand-side program. …”
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6
A DNR by Using Rank Evolutionary Particle Swarm Optimization for Power Loss Minimization
Published 2014“…The proposed method is a combination of the Particle Swarm Optimization (PSO) and the traditional Evolutionary Programming (EP) algorithm with a rejuvenation of the additional of ranking element. …”
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7
Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…Firstly, using MATLAB program, the ANN model is developed based on optimized topology and is then furthered optimized by genetic algorithm (GA) and particle swarm optimization (PSO) using MINITAB program. …”
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8
The assessment and improvement of angle stability condition of the power system using particle swarm optimization (PSO) technique / Nor Azwan Mohamed Kamari
Published 2016“…In order to accelerate the determination of angle stability, particle swarm optimization (PSO) is proposed to be implemented in this study. …”
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9
Logic Programming In Radial Basis Function Neural Networks
Published 2013“…The analysis revealed that performance of particle swarm optimization algorithm and Prey predator algorithm are better to use in training the networks. …”
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10
Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman
Published 2025“…This study applies Genetic Algorithms (GA) to optimize space distribution for test scheduling, addressing the challenge of managing multiple test sessions across distinct locations. …”
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11
A 33kV distribution network feeder reconfiguration by Using REPSO for voltage profile improvement
Published 2014“…It has been produced by a hybridization of the conventional Particle Swarm Optimization (PSO) and the traditional Evolutionary Programming (EP) algorithm. …”
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12
Modeling Of Electrical Distribution Networks With Particle Swarm Optimization Technique For The Improvement Of Voltage Profile And Loss Reduction
Published 2016“…The method is accurate and has advantage as easy to implement which accomplished with Carson's equations. …”
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13
The assessment and improvement of angle stability condition of the power system using particle swarm optimization (PSO) technique / Nor Azwan Mohamed Kamari
Published 2017“…In order to accelerate the determination of angle stability, particle swarm optimization (PSO) is proposed to be implemented in this study. …”
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Book Section -
14
A hybrid optimization technique for solving economic emission load dispatch problems
Published 2023text::Final Year Project -
15
Adaptive Embedded Clonal Evolutionary Programming (AECEP) for optimal Distributed Generation (DG) location and sizing in a distribution system
Published 2013“…AI methods mainly include Artificial Neural Network (ANN), Expert System (ES), Genetic Algorithm (GA), Evolutionary Programming (EP), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). …”
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16
Sub-route reversal repair mechanism and differential evolution for urban transit network design problem
Published 2017“…All proposed algorithms are executed using Python programming language, and the computational results show that the proposed algorithms improve the best-so-far results from the literature in most cases.…”
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17
Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli
Published 2014“…The backpropagation algorithm is one of the most famous algorithms to train neural network based on the mean square error (MSE) of ordinary least squares (OLS). …”
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Book Section -
18
Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment
Published 2017“…For these proposed approaches, this study adopted a hybridization of a fuzzy programming, modify simulated annealing, and simplex downhill (SD) algorithm called Fuzzy-MSASD to resolve multiple objective linear programming APP problems in a fuzzy environment. …”
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19
Modelling knowledge transfer of nursing students during clinical placement / Nor Azairiah Fatimah Othman
Published 2017“…In order to accelerate the determination of angle stability, particle swarm optimization (PSO) is proposed to be implemented in this study. …”
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Book Section -
20
Improved particle swarm optimization by fast annealing algorithm
Published 2019“…We also apply the algorithm in clustering problem, and the results shows that the proposed method has better accuracy than the optimization methods.…”
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