Search Results - (( using optimization based algorithm ) OR ( using modulated learning algorithm ))
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Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin
Published 2014“…Bat algorithm is an optimizer tool and developed using of echolocation characteristics of bats, while the neural network is learning methods that approach the human brain using artificial neurons. …”
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Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin
Published 2014“…Bat algorithm is an optimizer tool and developed using of echolocation characteristics of bats, while the neural network is learning methods that approach the human brain using artificial neurons. …”
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Experimental implementation controlled SPWM inverter based harmony search algorithm
Published 2023Article -
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Software defect prediction framework based on hybrid metaheuristic optimization methods
Published 2015“…For the purpose of this study, ten classification algorithms have been selected. The selection aims at achieving a balance between established classification algorithms used in software defect prediction. …”
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Firefly algorithm-based neural network for GCPV system output prediction: article / Nor Syakila Mohd Zainol Abidin
Published 2014“…Additionally, the optimal population size, absorption confession, learning algorithm and type of transfer functions in FA were also investigated in this study. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan
Published 2024“…Text preprocessing ensures consistent data representation and facilitates validation. The Machine Learning algorithm, comprising Random Forest, Linear Regression, XGBoost, SVM, and Stacking Ensemble, is embedded in the system for job position predictions based on the analysed data. …”
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8
Opposition-Based Quantum Bat Algorithm to Eliminate Lower-Order Harmonics of Multilevel Inverters
Published 2021“…Various optimization algorithms have been developed to determine the optimum switching angles. …”
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Opposition-Based Quantum Bat Algorithm to Eliminate Lower-Order Harmonics of Multilevel Inverters
Published 2021“…Various optimization algorithms have been developed to determine the optimum switching angles. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications.
Published 2020“…Addressing this issue, we propose to integrate the memory into EMCQ for combinatorial t-wise test suite generation using reinforcement learning based on the Q-learning mechanism, called Q-EMCQ. …”
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Towards Autonomous Farming -A Novel Scheme based on Learning to Prediction and Optimization for Smart Greenhouse Environment Control
Published 2022“…Real environmental data collected for Jeju Island, South Korea is used for model validation and results analysis. Proposed learning-based optimization scheme results are compared with two other schemes i.e., baseline scheme and optimization scheme. …”
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Towards Autonomous Farming -A Novel Scheme based on Learning to Prediction and Optimization for Smart Greenhouse Environment Control
Published 2022“…Real environmental data collected for Jeju Island, South Korea is used for model validation and results analysis. Proposed learning-based optimization scheme results are compared with two other schemes i.e., baseline scheme and optimization scheme. …”
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Toward Autonomous Farming - A Novel Scheme Based on Learning to Prediction and Optimization for Smart Greenhouse Environment Control
Published 2022“…Real environmental data collected for Jeju Island, South Korea is used for model validation and result analysis. Proposed learning-based optimization scheme results are compared with two other schemes, i.e., baseline scheme and optimization scheme. …”
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Firefly algorithm-based neural network for GCPV system output prediction / Nor Syakila Mohd Zainol Abidin
Published 2014“…FA was used to optimize the number of neurons in the hidden layer, the learning rate and the momentum rate such that the Root Mean Square Error (RMSE) was minimized. …”
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Study of machine learning in computer vision using Raspberry Pi
Published 2024text::Final Year Project -
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2TSS: Two-tier semantic segmentation framework with enhancement for hotspot detection of solar photovoltaic thermal images
Published 2025“…Recently, intelligence-based hotspot detection has been widely used in solar photovoltaic (PV) image applications. …”
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Performance comparison of non-invasive blood glucose level using artificial neural network and ultra-wide band antenna
Published 2020“…Several experiments were carried out to investigate the optimal ANN learning algorithm (levenberg-marquardt (LM), resilient backpropagation (RP) and scaled conjugate gradient (SCG)) for performance comparison. …”
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Combination of perturb and observe with online sequential extreme learning machine for photovoltaic system maximum power point tracking
Published 2018“…From different MPPT techniques previously proposed, the online sequential extreme learning machine algorithm and conventional perturb and observe are combined together as a proposed MPPT algorithm. …”
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