Search Results - (( java adaptation optimization algorithm ) OR ( using gasification learning algorithm ))

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 by Bahadar A., Kanthasamy R., Sait H.H., Zwawi M., Algarni M., Ayodele B.V., Cheng C.K., Wei L.J.

Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele B.V., Mustapa S.I., Kanthasamy R., Mohammad N., AlTurki A., Babu T.S.

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 by Bahadar, A., Kanthasamy, R., Sait, H.H., Zwawi, M., Algarni, M., Ayodele, B.V., Cheng, C.K., Wei, L.J.

“…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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Modeling the prediction of hydrogen production by co-gasification of plastic and rubber wastes using machine learning algorithms by Ayodele B.V., Mustapa S.I., Kanthasamy R., Zwawi M., Cheng C.K.

Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

“…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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Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

“…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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Producer gas composition prediction using artificial neural network algorithm / Mohd Mahadzir Mohammud ... [et al.] by Mohammud, Mohd Mahadzir, Mohamad Bakre, Muhammad Syaham, Mohd Fohimi, Nor Azirah, Rabilah, Rosniza, Ahmad, Muhammad Iqbal

“…Simulation is a useful tool for learning about the governing principles and optimal operating points of the gasification process. …”
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BCLH2Pro: a novel computational tools approach for hydrogen production prediction via machine learning in biomass chemical looping processes by Tuntiwongwat, Thanadol, Thammawiset, Sippawit, Srinophakun, Thongchai Rohitatisha, Ngamcharussrivichai, Chawalit, Sukpancharoen, Somboon

“…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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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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