Titlebook: Combustion Optimization Based on Computational Intelligence; Hao Zhou,Kefa Cen Book 2018 Springer Nature Singapore Pte Ltd. and Zhejiang U

出汗

Hao Zhou,Kefa CenProvides a book-length examination of combustion optimization based on computational intelligence.Presents advances made in the past ten years, ranging from fundamentals to applications.Includes contr

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Combustion Optimization Based on Computational Intelligence978-981-10-7875-0Series ISSN 1995-6819 Series E-ISSN 1995-6827

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Michael Jenkins,Cleveland McSwainrial fields including pattern recognition and speech recognition. Then, two typical kinds of ANN algorithm (BPNN and GRNN) are introduced in this section. Through the comparative analysis of the principle and the conditions of the two methods of BPNN and GRNN, a new method combining the two methods is proposed.

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Apraxia

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Neural Network Modeling of Combustion Characteristics,rial fields including pattern recognition and speech recognition. Then, two typical kinds of ANN algorithm (BPNN and GRNN) are introduced in this section. Through the comparative analysis of the principle and the conditions of the two methods of BPNN and GRNN, a new method combining the two methods is proposed.

NIP

Combining Neural Network or Support Vector Machine with Optimization Algorithms to Optimize the Comlso multi-objective optimization is introduced, like MOCell, AbYSS, OMOPSO, and SPEA2. They are compared in many aspects. Among them, OMOPSO and MOCell are the proposed algorithms for online multi-object optimization of coal-fired boilers.

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Combustion Optimization Based on Computational Intelligence