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1
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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2
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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3
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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4
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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5
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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6
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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7
1D Multigrid Solver For Finite Element Method
Published 2022“…Usually, the mathematical problem can be solved using only one of those two methods. A sample of such code written in MATLAB programming language was found in the GitHub repository, where the implemented algorithms are far from optimal. …”
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Monograph -
8
Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja
Published 2004“…For most of the cases of the shortest route finding, the Dijkstra's algorithm is known to be an optimal search algorithm. …”
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9
Network reconfiguration and control for loss reduction using genetic algorithm
Published 2010“…Tests have shown that the differences are demonstrated only in execution time to arrive the best fitness function of the Genetic Algorithm. …”
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10
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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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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Book Chapter -
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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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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
The solution of 2048 puzzle game using A* algorithm / Zafhira Ismail
Published 2017“…The input data of this project is retrieved from the game’s rule itself and implemented with the proposed algorithm which is A* algorithm. …”
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15
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…The third set affirmed that the enhancement on the proposed algorithm, which made use of indexing method that suits the medoids, could boost the performance to about 9 to 27 times in terms of execution time depending on the complexity of the dataset. …”
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16
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 -
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Development of the cascading module for hydro energy decision support system (HEDSS) for Temenggor-Bersia-Kenering power plants
Published 2002“…A generalized network flow algorithm is used to find the optimal solution.…”
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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
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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20
Deep Reinforcement Learning For Control
Published 2021“…To generate the visual simulation in the simulator, the Python programming language is employed. The improved algorithm will help encourage the real-world implementation of DRL in many autonomous driving applications.…”
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