Catalytic thermal degradation of Chlorella vulgaris: Evolving deep neural networks for optimization

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Teng, S.Y. and Loy, A.C.M. and Leong, W.D. and How, B.S. and Chin, B.L.F. and MÃ¡Å¡a, V. (2019) Catalytic thermal degradation of Chlorella vulgaris: Evolving deep neural networks for optimization. Bioresource Technology, 292. ISSN 09608524

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

The aim of this study is to identify the optimum thermal conversion of Chlorella vulgaris with neuro-evolutionary approach. A Progressive Depth Swarm-Evolution (PDSE) neuro-evolutionary approach is proposed to model the Thermogravimetric analysis (TGA) data of catalytic thermal degradation of Chlorella vulgaris. Results showed that the proposed method can generate predictions which are more accurate compared to other conventional approaches (>90 lower in Root Mean Square Error (RMSE) and Mean Bias Error (MBE)). In addition, Simulated Annealing is proposed to determine the optimal operating conditions for microalgae conversion from multiple trained ANN. The predicted optimum conditions were reaction temperature of 900.0 Â°C, heating rate of 5.0 Â°C/min with the presence of HZSM-5 zeolite catalyst to obtain 88.3 of Chlorella vulgaris conversion. Â© 2019 Elsevier Ltd

Item Type:	Article
Additional Information:	cited By 38
Uncontrolled Keywords:	Algae; Deep neural networks; Mean square error; Microorganisms; Particle swarm optimization (PSO); Simulated annealing; Zeolites, Artificial neuron networks; Chlorella vulgaris; Conventional approach; Evolutionary approach; Micro-algae; Optimal operating conditions; Reaction temperature; Root mean square errors, Thermogravimetric analysis, artificial neural network; catalysis; environmental degradation; microalga; optimization; simulated annealing; thermal decomposition; thermogravimetry, article; catalyst; Chlorella vulgaris; heating; microalga; nerve cell; nonhuman; prediction; reaction temperature; simulation; thermogravimetry; artificial neural network; catalysis; temperature, Chlorella vulgaris, Catalysis; Chlorella vulgaris; Microalgae; Neural Networks (Computer); Temperature
Depositing User:	Mr Ahmad Suhairi UTP
Date Deposited:	10 Nov 2023 03:25
Last Modified:	10 Nov 2023 03:25
URI:	https://khub.utp.edu.my/scholars/id/eprint/11185

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