Power forecasting of combined heating and cooling systems based on chaotic time series

DOI10.1155/2015/174203zbMath1326.93060OpenAlexW1559173904WikidataQ59112360 ScholiaQ59112360MaRDI QIDQ892574

Liu Hai, Song Yong, Du Qingfu

Publication date: 19 November 2015

Published in: Journal of Control Science and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2015/174203

zbMATH Keywords

chaoslargest Lyapunov exponentneural network modelnonlinear dynamic systemchaotic power time seriesdistributed generation systemimproved C-C method

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Nonlinear systems in control theory (93C10) Application models in control theory (93C95) Lyapunov and storage functions (93D30) Chaos control for problems involving ordinary differential equations (34H10)

Cites Work

• Time series prediction using Lyapunov exponents in embedding phase space
• Optimization and applications of echo state networks with leaky- integrator neurons

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