Biodiesel preparation is broadly led through transesterification process with homogeneous or heterogeneous catalyst. The most remarkable catalyst utilized in preparing biodiesel is the homogeneous catalyst, for example, NaOH, KOH, Na2O2, and CH3ONa. The decision of selecting among these catalysts is because of their higher response rates. Accordingly, this paper examines the impacts of various catalyst utilized for preparing biodiesel. Machine learning has demonstrated to be an amazing for various modeling during the previous decades. Artificial neural networks (ANN) stand out among the most prominent modeling methods investigated. The utilization of ANN for improvement of catalyst in biodiesel preparation was not well‐studied until ongoing decades. In this analysis, the focus is on the use of ANNs for catalysis advancement in biodiesel preparation. From the points of view of experimental analysis and ANN modeling, this investigation indicates how ANNs can be adequately connected for catalyst optimization in biodiesel preparation.


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    Title :

    Experimental Catalyst Optimization and Artificial Neural Network Modeling in Biodiesel Preparation


    Additional title:

    Lect.Notes Mechanical Engineering


    Contributors:

    Conference:

    National Conference on IC Engines and Combustion ; 2019 ; Kurukshetra, India November 01, 2019 - November 04, 2019



    Publication date :

    2020-08-19


    Size :

    9 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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