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Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin
Published 2014“…Bat Algorithm (BA) was hybrid based Multi-Layer Feedforward Neural Network (MLFNN) for modeling the temperature operating of photovoltaic module. …”
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Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin
Published 2014“…Bat Algorithm (BA) was hybrid based Multi-Layer Feedforward Neural Network (MLFNN) for modeling the temperature operating of photovoltaic module. …”
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Thesis -
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One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network
Published 2012“…Based on result obtained, it shows that IWO learning algorithm is capable to produce accurate prediction load demand. …”
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Pairwise Test Suite Generation Using Adaptive Teaching Learning-Based Optimization Algorithm with Remedial Operator
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Operating a reservoir system based on the shark machine learning algorithm
Published 2018“…Therefore, the development of a mathematical optimization model is crucial for selecting the optimal policies for the reservoir operation. In the current study, the shark machine learning algorithm (SMLA) is proposed to develop an optimal rule for operating the reservoir. …”
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Classification of fault and stray gassing in transformer by using duval pentagon and machine learning algorithms
Published 2022“…Data resampling technique (SMOTETomek) is applied and shows further improvement on the accuracy of predictions by machine learning algorithms when deal with imbalance data. …”
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Rough-Set-and-Genetic-Algorithm based data mining and Rule Quality Measure to hypothesize distance protective relay operation characteristics from relay event report
Published 2011“…Firstly, the data mining approach of the integrated-Rough-Set-and-Genetic-Algorithm is used to discover the relay CD-decision algorithm. …”
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Anomaly detection in ICS datasets with machine learning algorithms
Published 2021“…The machine learning algorithms have been performed with labeled output for prediction classification. …”
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Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023“…An alternative method is proposed, utilizing machine learning algorithms. Therefore, this thesis explores the comparative analysis for BOTDA data processing using the six most suited machine learning algorithms. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2023“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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Applications of deep learning algorithms for supervisory control and data acquisition intrusion detection system
Published 2022“…In this paper, we have examined and presented the most recent research on developing robust IDSs using Deep Learning (DL) algorithms, including Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Stacked Autoencoders (SAE), and Deep Belief Networks (DBN). …”
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Machine learning and deep learning approaches for cybersecurity: a review
Published 2022“…This paper reviewed intrusion detection systems and discussed what types of learning algorithms machine learning and deep learning are using to protect data from malicious behavior. …”
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