Search Results - (( java application optimisation algorithm ) OR ( using gasification learning algorithm ))
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Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach
Published 2022“…A total of 12 machine learning algorithms which comprises the regression models, SVM, GPR, and ANN were configured, trained using 124 datasets. …”
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Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed...
Published 2022“…Whereas the best performance in terms of prediction of the syngas composition was obtained using the NLRQM algorithm with an inbuilt SQP and LM algorithms. …”
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Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed...
Published 2022“…Whereas the best performance in terms of prediction of the syngas composition was obtained using the NLRQM algorithm with an inbuilt SQP and LM algorithms. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Producer gas composition prediction using artificial neural network algorithm / Mohd Mahadzir Mohammud ... [et al.]
Published 2023“…Simulation is a useful tool for learning about the governing principles and optimal operating points of the gasification process. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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BCLH2Pro: a novel computational tools approach for hydrogen production prediction via machine learning in biomass chemical looping processes
Published 2024“…This study optimizes biomass chemical looping processes (BCLpro), a technique for converting biomass to energy, through machine learning (ML) for sustainable energy production. The study proposes an integrated Fe2O3-based ฺBCLpro combining steam gasification for H2 production. …”
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