Performance assessment of artificial neural network on the prediction of Calophyllum inophyllum biodiesel through two-stage transesterification

Autor:	Md. Faizaan A, K L Vasudev, Sivamani Seralathan, Venkatesan Hariram, T. Micha Premkumar, Akilandabharathi K, Ezhil Maran K, Dhanush C
Rok vydání:	2019
Předmět:	Biodiesel Artificial neural network biology Renewable Energy Sustainability and the Environment 020209 energy Computer Science::Neural and Evolutionary Computation Bayesian probability Energy Engineering and Power Technology 02 engineering and technology Process variable Transesterification biology.organism_classification Calophyllum inophyllum Fuel Technology 020401 chemical engineering Nuclear Energy and Engineering Genetic algorithm 0202 electrical engineering electronic engineering information engineering Stage (hydrology) 0204 chemical engineering Biological system Mathematics
Zdroj:	Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. 43:1060-1072
ISSN:	1556-7230 1556-7036
DOI:	10.1080/15567036.2019.1634164
Popis:	Bayesian regularized Artificial Neural Network (ANN) coupled with genetic algorithm was used to develop a model to predict the optimized process variable parameters for the transesterification proc...
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::9f7860ca8aaf2d3658bbbcbbc03dd5ba https://doi.org/10.1080/15567036.2019.1634164 Zobrazit plný text záznamu