Search Results - (( variable lightning based algorithm ) OR ( java active learning algorithm ))
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Evaluation of lightning return stroke current using measured electromagnetic fields
Published 2012“…However, the improvement of Deindorfer and Uman on the Heidler function with an unknown variable is selected as the general channel base current function. …”
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Thesis -
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Lightning fault classification for transmission line using support vector machine
Published 2023“…The input variables for the models were based on the root mean square (RMS) current duration, voltage dip, and energy wavelet measured at the sending end of a line. …”
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Conference or Workshop Item -
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Lightning Fault Classification for Transmission Line Using Support Vector Machine
Published 2024“…The input variables for the models were based on the root mean square (RMS) current duration, voltage dip, and energy wavelet measured at the sending end of a line. …”
Conference Paper -
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The support vector machines (SVM) algorithm obtained the overall best results of 94.5% accuracy, 91.8% precision, 91.7% recall, and 91.1% f-Measure while the naïve bayes (NB) algorithm obtained the best AUC score of 0.944 with the tweet data of Dato Seri Anwar. …”
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6
Development Of Machine Learning User Interface For Pump Diagnostics
Published 2022“…Build up a user interface by using Visual Studio Code (VSC) to run the coding of Cascading Style Sheet (CSS), Hyper Text Markup Language (HTML) and JavaScript (JS) as a webpage and connect to Azure Machine Learning Model and this will allow the user from using the model from a webpage when they have active internet with any devices.…”
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Monograph -
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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8
Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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