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Optimization of mycelium growth using genetic algorithm for multi-objective functions
Published 2019“…To solve this issues, multi-objective genetic algorithm was chosen as the methodology for this project, specifically using NSGA-ii algorithm. …”
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Undergraduates Project Papers -
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Global gbest guided-artificial bee colony algorithm for numerical function optimization
Published 2018“…Numerous computational algorithms are used to obtain a high performance in solving mathematics, engineering and statistical complexities. …”
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African Buffalo Optimization
Published 2016“…This paper presents an overview of major metaheuristic algorithms with the aim of providing a basis for the development of the African Buffalo Optimization algorithm which is a nature-inspired, population-based metaheuristic algorithm. …”
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Optimal power flow using hybrid firefly and particle swarm optimization algorithm
Published 2020“…In this paper, a novel, effective meta-heuristic, population-based Hybrid Firefly Particle Swarm Optimization (HFPSO) algorithm is applied to solve different non-linear and convex optimal power flow (OPF) problems. …”
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Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…On the other hand, LM algorithms which are derivative based algorithms still face a risk of getting stuck in local minima. …”
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Thesis -
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Optimization machining parameters in pocket milling using genetic algorithm and mastercam
Published 2023“…Mastercam software has been used to verify the algorithm's results by applying the optimum parameter generated by GA in the Mastercam. …”
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Conference or Workshop Item -
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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PAPR Reduction Using Genetic Algorithm (GA) In OFDM System
Published 2018“…In this thesis, a Genetic algorithm (GA) technique is proposed. GA is a type of optimization algorithm, which is natural-based selection and is used to find the optimal solution to the computational problem that maximizes or minimizes a particular function. …”
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Monograph -
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Enhancing three variants of harmony search algorithm for continuous optimization problems
Published 2021“…Meanwhile, opposition-based learning (OBL), is an effective technique used to improve the performance of different optimization algorithms, including HS. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Sine-cosine optimization-based bijective substitution-boxes construction using enhanced dynamics of chaotic map
Published 2018“…This paper proposes a novel method of constructing strong substitution-boxes (S-boxes) of order n (4 ≤ n ≤ 8) based on a recent optimization algorithm known as sine-cosine algorithm (SCA). …”
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Detecting problematic vibration on unmanned aerial vehicles via genetic-algorithm methods
Published 2024“…The fitness function with the Genetic Algorithm (GA) optimization method is tested and evaluated based on Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and detection time. 51 sets of data have been collected using software in the loop (SITL) methods and are used to determine the effectiveness of the proposed fitness function and GA. …”
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Conference or Workshop Item -
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Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim
Published 2021“…In order to verify the effectiveness of this newly developed method, the algorithm was tested on common benchmark functions used in the literature. …”
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Article -
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Application of the Jaya algorithm to solve the optimal reliability allocation for reduction oxygen supply system of a spacecraft
Published 2021“…The original findings of this paper are: I) the system used in this paper is a spacecraft's reduced oxygen supply system with the logarithmic cost function; and ii) the results obtained were by using the Jaya algorithm to solve specific system reliability optimization problems.…”
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Optimized Load Balancing based Task Scheduling in Cloud Environment
Published 2014“…In addition, the salient feature of this algorithm is to optimize node available throughput dynamically using MatLab10A software. …”
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