Search Results - (( variable learning drops algorithm ) OR ( java application matching algorithm ))
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…Moreover, the LSA optimization technique is introduced to optimally determine the LSTM deep neural model hyperparameters including the number of hidden neurons, learn rate, epoch, learn rate drop factor, learn rate drop period, and gradient decay factor. …”
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Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman
Published 2025“…In the development phase, Convolutional Neural Network model was designed and trained using sophisticated techniques of data augmentation, dropping out and hyperparameter tuning under the supervised learning methodology to increase the performance of the system. …”
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DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS
Published 2011“…It was found that (by the Group Method of Data Handling algorithm), length of the pipe, wellhead pressure, and angle of inclination have a pronounced effect on the pressure drop estimation under these conditions. …”
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Message based random variable length key encryption algorithm.
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Securing cloud data system (SCDS) for key exposure using AES algorithm
Published 2021“…The AES algorithm has its own structure to encrypt and decrypt sensitive data that make the attackers difficult to get the real data when encrypting by AES algorithm. …”
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Predictive modelling of student academic performance using machine learning approaches : a case study in universiti islam pahang sultan ahmad shah
Published 2024“…The predictive algorithm can also be added to the Learning Management System along with a dashboard so that it is easier to do analyses in the future.…”
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An Agent-Based System with Personalization and Intelligent Assistance Services for Facilitating Knowledge Sharing
Published 2006“…The main algorithms used are profile determination and user similarity. …”
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