Computational Intelligence in Data-Driven Modelling and Its Engineering Applications
[...]artificial neural networks (ANNs) and fuzzy rule-based systems (FRBSs) serve as fundamental model frameworks, which are alternatives to statistical inference methods. The accepted papers involve a variety of data-driven modelling and data analytics techniques and contribute to a wide range of a...
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| Veröffentlicht in: | Mathematical problems in engineering 2018-01, Vol.2018, p.1-2 |
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| container_title | Mathematical problems in engineering |
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| creator | Zhang, Qian Spurgeon, Sarah Xu, Li Yu, Dingli |
| description | [...]artificial neural networks (ANNs) and fuzzy rule-based systems (FRBSs) serve as fundamental model frameworks, which are alternatives to statistical inference methods. The accepted papers involve a variety of data-driven modelling and data analytics techniques and contribute to a wide range of application areas, including transportation, environment, telecommunication, automatic control, product design, and finance. Q. Wang et al. combined the partial least square (PLS) approach with the back-propagation neural network (BPNN) and the radial basis function neural network (RBFNN) to predict short-term wind power. |
| doi_str_mv | 10.1155/2018/2576239 |
| format | Article |
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| language | eng |
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| source | Wiley Online Library Open Access; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection |
| subjects | Artificial intelligence Artificial neural networks Automatic control Back propagation networks Control algorithms Engineering Experiments Explicit knowledge Fuzzy logic Fuzzy systems Neural networks Product design Radial basis function Securities markets Statistical inference Statistical methods Wind power |
| title | Computational Intelligence in Data-Driven Modelling and Its Engineering Applications |
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