Search Results - (( waste active learning algorithm ) OR ( java application bat algorithm ))

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    Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations by Hossain, S.K.S., Ayodele, B.V., Alhulaybi, Z.A., Alwi, M.M.A.

    Published 2022
    “…In this study, a data-driven machine-learning approach is employed to model the prediction of biohydrogen from waste glycerol. …”
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    Article
  3. 3

    A review of Artificial Intelligence application of sustainable solid waste management practices in Western Asia by Nagimeldin, Olla, Ahmad Tajuddin, Husna, Jami, Mohammed Saedi

    Published 2022
    “…Over the past few years, Machine-learning algorithms and Artificial intelligence models have demonstrated great ability to optimize and automate critical solid waste and waste management complications. …”
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    Proceeding Paper
  4. 4

    An intelligent risk management framework for monitoring vehicular engine health by Rahim, Md. Abdur, Rahman, Md. Arafatur, Rahman, Md. Mustafizur, Zaman, Nafees, Moustafa, Nour, Razzak, Imran

    Published 2022
    “…The stacked ensemble of the deep learning algorithm outperformed other standard machine learning and deep learning algorithms in providing 80.3% decision accuracy for the 80% training data and efficiently managing large amounts of data. …”
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    Article
  5. 5

    Modelling of biogas production process with evolutionary artificial neural network and genetic algorithm by Fakharudin, Abdul Sahli

    Published 2017
    “…In recent years, several researchers have actively pursued the application of machine learning to biogas production processes. …”
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    Thesis
  6. 6

    Mixed waste classification based on vision inspection / Hassan Mehmood Khan by Hassan Mehmood , Khan

    Published 2022
    “…Classification of dry waste garbage is crucial since incorrect labelling of dry waste types may contribute huge loss to waste industry. …”
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    Thesis
  7. 7

    Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin by Husam , N. S. Yasin

    Published 2021
    “…The computation time complexity of the Q-Learning-based test coverage algorithm was also analyzed. …”
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    Thesis
  8. 8

    Artificial Neural Network-Forecasted Compression Strength of Alkaline-Activated Slag Concretes by Yi, Xuan Tang, Yeong, Huei Lee, Mugahed, Amran, Roman, Fediuk, Nikolai, Vatin, Beng, Ahmad Hong Kueh, Yee, Yong Lee

    Published 2022
    “…To remedy this, an environmentally friendly concrete, alkaline-activated slag concrete (AASC), where OPC is completely replaced by ground granulated blast-furnace slag (GGBFS) industrial waste, is one of the currently pursued research interests. …”
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    Article