Search Results - (( program implementation function algorithm ) OR ( based optimization techniques algorithm ))
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1
Genetic algorithm based for optimizing filter design / Rohana Awang Ahmed
Published 2000“…GA is then implemented using the Genetic Algorithm Toolbox (GAOT). …”
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2
Design and implementation of an optimal fuzzy logic controller using genetic algorithm
Published 2008“…Said approach was first simulated using MATLAB/SIMULINK using the techniques of Proportional Derivative Fuzzy Logic Controller (PD-FLC) whose membership function, fuzzy logic rules and scaling gains were optimized by the genetic algorithm technique. …”
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3
Network reconfiguration and control for loss reduction using genetic algorithm
Published 2010“…The proposed solution to this problem is based on a general combinatorial optimization algorithm known as Genetic Algorithm, and the load flow equations in distribution network. …”
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4
Integrated immune-commensal-evolutionary programming for economic dispatch and distributed generation installation / Mohd Helmi Mansor
Published 2020“…EP is the leading optimizer of the hybrid algorithm while cloning operator of AIS and commensal operator of SOS are adopted into the EP algorithm to improve its performance. …”
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5
Optimization of Digital Electronic Circuit Structure Design Using Genetic Algorithm
Published 2008“…Karnaugh map can provide the simple minimization process for Boolean expression, but it encounters difficulties when the variable is more than four In this research, Genetic Algorithm (GA) technique is used as a tool to search for the optimal solution for the digital circuit structure. …”
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6
Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain
Published 2020“…Thus, a reliable optimization technique such as Nature Inspired Metaheuristic Algorithms (NIMA) is crucial to address this issue. …”
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7
An alternative method to solve combined economic emission dispatch problems using flower pollination algorithm
Published 2016“…Flower Pollination Algorithm (FPA) is a new biologically inspired meta-heuristic optimization technique based the pollination process of flowers. …”
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8
Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman
Published 2025“…The research adopts a Genetic Algorithm-based approach, where examination scheduling details such as date, time, course code, program code, student group, student numbers, and available spaces are encoded as chromosomes. …”
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A hybrid optimization technique for solving economic emission load dispatch problems
Published 2023text::Final Year Project -
10
Optimal location and sizing of SVC using Particle Swarm Optimization technique
Published 2011“…Particle Swarm Optimization (PSO) is population-based stochastic search algorithms approaches as the potential techniques to solving such a problem. …”
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11
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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12
An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications.
Published 2020“…The results show the Q-EMCQ is also capable of outperforming the original EMCQ as well as several recent meta/hyper-heuristic including modified choice function, Tabu high-level hyperheuristic, teaching learning-based optimization, sine cosine algorithm, and symbiotic optimization search in clustering quality within comparable execution time.…”
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13
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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14
Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin
Published 2014“…To enhance the robustness of the algorithm, the QIEP technique is constructed based on multiobjective model in which the multiobjective functions consist of reducing power losses, increasing maximum loadability and cost minimisation. …”
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15
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…In general, genetic based clustering algorithms showed the ability to reach near global optimal solution. …”
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16
Discrete-time system identification using genetic algorithm with single parent-based mating technique
Published 2024“…The methodology encompasses data acquisition, GA program development, SPM technique implementation, and simulation using MATLAB. …”
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17
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…DE has effectively solved various global optimization problems, including benchmark functions. …”
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18
Performance improvement through optimal location and sizing of distributed generation / Zuhaila Mat Yasin
Published 2014“…To enhance the robustness of the algorithm, the QIEP technique is constructed based on multiobjective model in which the multiobjective functions consist of reducing power losses, increasing maximum loadability and cost minimisation. …”
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19
Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli
Published 2014“…Neural network is an efficient tool for forecasting financial time series as well as many other areas and has shown a great success, outperforming other forecasting techniques. 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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20
Computational intelligence based power system security assessment and improvement under multi-contingencies conditions / Nor Rul Hasma Abdullah
Published 2012“…The minimizations of SVSI and transmission loss are used as two separate objective functions for the development of optimization technique. …”
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