Modeling and Optimization of Biodiesel Engine Performance using Kernel-based Extreme Learning Machine and Cuckoo Search

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Status	已發表Published
	Modeling and Optimization of Biodiesel Engine Performance using Kernel-based Extreme Learning Machine and Cuckoo Search
	Wong, P. K.; Wong, K. I.; Vong, C. M.; Cheung, C. S.
	2015-02-01
Source Publication	Renweable Energy (SCI-E)
ISSN	0960-1481
Pages	640-647
Abstract	This study presents the optimization of biodiesel engine performance that can achieve the goal of fewer emissions, low fuel cost and wide engine operating range. A new biodiesel engine modeling and opti- mization framework based on extreme learning machine (ELM) is proposed. As an accurate model is required for effective optimization result, kernel-based ELM (K-ELM) is used instead of basic ELM because K-ELM can provide better generalization performance, and the randomness of basic ELM does not occur in K-ELM. By using K-ELM, a biodiesel engine model is first created based on experimental data. Logarithmic transformation of dependent variables is used to alleviate the problems of data scarcity and data exponentiality simultaneously. With the K-ELM engine model, cuckoo search (CS) is then employed to determine the optimal biodiesel ratio. A flexible objective function is designed so that various user-defined constraints can be applied. As an illustrative study, the fuel price in Macau is used to perform the optimization. To verify the modeling and optimization framework, the K-ELM model is compared with a least-squares support vector machine (LS-SVM) model, and the CS optimization result is compared with particle swarm optimization and experimental results. The evaluation result shows that K-ELM can achieve comparable performance to LS-SVM, resulting in a reliable prediction result for optimization. It also shows that the optimization results based on CS is effective.
Keyword	Biodiesel Engine optimization Kernel-based extreme learning machine Cuckoo search
Language	英語English
The Source to Article	PB_Publication
PUB ID	15397
Document Type	Journal article
Collection	Faculty of Science and Technology
Corresponding Author	Wong, P. K.
Recommended Citation GB/T 7714	Wong, P. K.,Wong, K. I.,Vong, C. M.,et al. Modeling and Optimization of Biodiesel Engine Performance using Kernel-based Extreme Learning Machine and Cuckoo Search[J]. Renweable Energy (SCI-E), 2015, 640-647.
APA	Wong, P. K.., Wong, K. I.., Vong, C. M.., & Cheung, C. S. (2015). Modeling and Optimization of Biodiesel Engine Performance using Kernel-based Extreme Learning Machine and Cuckoo Search. Renweable Energy (SCI-E), 640-647.
MLA	Wong, P. K.,et al."Modeling and Optimization of Biodiesel Engine Performance using Kernel-based Extreme Learning Machine and Cuckoo Search".Renweable Energy (SCI-E) (2015):640-647.

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