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Mathematical Problems in Engineering
Volume 2017 (2017), Article ID 3075432, 13 pages
https://doi.org/10.1155/2017/3075432
Research Article

Optimization of Indoor Thermal Comfort Parameters with the Adaptive Network-Based Fuzzy Inference System and Particle Swarm Optimization Algorithm

1School of Energy and Environmental Engineering, University of Science & Technology Beijing, Beijing 100083, China
2Beijing Key Laboratory of Energy Saving and Emission Reduction for Metallurgical Industry, University of Science and Technology Beijing, Beijing 100083, China
3School of Mechanical Engineering, University of Science & Technology Beijing, Beijing 100083, China

Correspondence should be addressed to Shao-Wu Yin; nc.ude.btsu@wsniy

Received 1 December 2016; Revised 21 February 2017; Accepted 26 February 2017; Published 22 March 2017

Academic Editor: Alessandro Lo Schiavo

Copyright © 2017 Jing Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Jing Li, Shao-Wu Yin, Guang-Si Shi, and Li Wang, “Optimization of Indoor Thermal Comfort Parameters with the Adaptive Network-Based Fuzzy Inference System and Particle Swarm Optimization Algorithm,” Mathematical Problems in Engineering, vol. 2017, Article ID 3075432, 13 pages, 2017. doi:10.1155/2017/3075432