Search Results - (( java application during algorithm ) OR ( variable abstraction model algorithm ))
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. …”
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An Intelligent Process Model for Manufacturing System Optimization
Published 2012“…The model sets inventory target variable to be achieved with automated computation through the data input from users. …”
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SUDOKU HELPER
Published 2015“…In this paper research, author presents an algorithm to provide a tutorial for any Sudoku player who got stuck during the solving process. …”
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DRIFT ANALYSIS ON NEURAL NETWORK MODEL OF HEAT EXCHANGER FOULING
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Design of digital circuit structure based on evolutionary algorithm method
Published 2008“…EAs introduce a new idea for automatic design of electronic systems; instead of imagine model, abstractions, and conventional techniques, it uses search algorithm to design a circuit. …”
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Regression study for thyroid disease prediction Comparison of crossing-over approaches and multivariate analysis
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Conference or Workshop Item -
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Talkout : Protecting mental health application with a lightweight message encryption
Published 2022“…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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Predicting Flow Rate of V-Shape Customm Tank Using Derivative Free Recursive Algorithm
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Advance speech recognition / Mohammad Amarulhariz Mohd Fairuz … [et al.]
Published 2024“…Speech recognition technology has undergone remarkable progress in recent years, driven by advancements in artificial intelligence, machine learning algorithms, and neural network architectures. This paper reviews key methodologies and approaches utilized in modern speech recognition systems, highlighting the shift from traditional statistical models to deep learning techniques. …”
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