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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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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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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…The growing global populations, particularly in major cities, have created new problems, notably in terms of public safety regulation and optimization. As a result, in this paper, a strategy is provided for predicting crime occurrences in a city based on historical events and demographic observation. …”
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Interval type-2 fuzzy logic control optimize by spiral dynamic algorithm for two-wheeled wheelchair
Published 2020“…The two-wheeled wheelchair is designed using SimWise 4D software to subduing shortcomings of a linearized mathematical model where lengthy equation with various assumptions is required to represent the proposed system; without forgoing its nonlinearity and complexity. …”
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Algorithm-program visualization model : An intergrated software visualzation to support novices' programming comprehension
Published 2015“…This model is then to be used in the prototype tool development that is called 3De-ALPROV (Design Development Debug – Algorithm Program Visualization). …”
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The Development Of System For Algorithms Visualization Using Simjava
Published 2020“…Algorithm visualization which is a form of high-level dynamic visualization of software that uses user interface techniques to portray and monitor the computational steps of algorithms. …”
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The optimization of technical trading strategy using genetic algorithm approach / Khairunnisa Musa
Published 2006“…Recently, the use of genetic algorithm for the optimization of technical trading strategies has been receiving a great deal of attention. …”
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…The evolutionary algorithm has been extensively used to solve a range of combinatorial optimization problems. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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Simulation and Visualization of TSP Using Ant Colony Optimization
Published 2023“…This study aims to simulate and visualize the TSP by developing a software simulation model. …”
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An adaptively switching iteration strategy for population based metaheuristics / Nor Azlina Ab. Aziz
Published 2017“…Experiments conducted using three parent algorithms namely particle swarm optimization (PSO), which is a popular population-based optimizer with population and individual memories, gravitational search algorithm (GSA), a memoryless young optimizer, and simulated Kalman filter (SKF), a newly introduced optimization algorithm that use population’s memory to guide an agent’s search, show that iteration strategy is an algorithm dependent parameter as well as function dependent. …”
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Optimization of operations of reservoir systems for hydropower generation in Tigris River Basin, Iraq
Published 2016“…The two strategies mentioned previously were also used in the combined GAOMs and SMs to determine the optimal operation policies for the multi-reservoir system in the case of using a new storage of Makhoul reservoir. …”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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Optimization of hydropower reservoir operation based on hedging policy using Jaya algorithm
Published 2023Article -
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Optimal charging strategy for plug-in hybrid electric vehicle using evolutionary algorithm
Published 2016“…Upon this study, a control charging system is needed to control the charging so that the distribution network is not overloaded. An optimal charging strategy for plug-in hybrid electric vehicle (PHEV) is proposed and developed by using evolutionary algorithm to obtain the most suitable charging condition for each PHEV charging. …”
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Undergraduates Project Papers
