A modified teaching–learning-based optimization algorithm for solving optimization problem

In order to reduce the NOx emissions concentration of a circulation fluidized bed boiler, a modified teaching–learning-based optimization algorithm (MTLBO) is proposed, which introduces a new population group mechanism into the conventional teaching–learning based optimization algorithm. The MTLBO s...

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Vydáno v:	Knowledge-based systems Ročník 212; s. 106599
Hlavní autoři:	Ma, Yunpeng, Zhang, Xinxin, Song, Jiancai, Chen, Lei
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier B.V 05.01.2021 Elsevier Science Ltd
Témata:	Academic achievement Algorithms Artificial neural networks Circulation fluidized bed boiler Concentration Convergence Emissions Extreme learning machine Fluidized bed reduction Fluidized beds Groups Learning Machine learning Modified teaching–learning-based optimization Nitrogen oxides NOx emission model Optimization Optimization algorithms Students Teaching Teaching–learning-based optimization Extreme learning machine NOx emission model Teaching–learning-based optimization Modified teaching–learning-based optimization Circulation fluidized bed boiler
ISSN:	0950-7051, 1872-7409
On-line přístup:	Získat plný text
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