Optimization of Indoor Thermal Comfort Parameters with the Adaptive Network-Based Fuzzy Inference System and Particle Swarm Optimization Algorithm
Joint Authors
Wang, Li
Shi, Guangsi
Li, Jing
Yin, Shao-Wu
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-03-22
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
The goal of this study is to improve thermal comfort and indoor air quality with the adaptive network-based fuzzy inference system (ANFIS) model and improved particle swarm optimization (PSO) algorithm.
A method to optimize air conditioning parameters and installation distance is proposed.
The methodology is demonstrated through a prototype case, which corresponds to a typical laboratory in colleges and universities.
A laboratory model is established, and simulated flow field information is obtained with the CFD software.
Subsequently, the ANFIS model is employed instead of the CFD model to predict indoor flow parameters, and the CFD database is utilized to train ANN input-output “metamodels” for the subsequent optimization.
With the improved PSO algorithm and the stratified sequence method, the objective functions are optimized.
The functions comprise PMV, PPD, and mean age of air.
The optimal installation distance is determined with the hemisphere model.
Results show that most of the staff obtain a satisfactory degree of thermal comfort and that the proposed method can significantly reduce the cost of building an experimental device.
The proposed methodology can be used to determine appropriate air supply parameters and air conditioner installation position for a pleasant and healthy indoor environment.
American Psychological Association (APA)
Li, Jing& Yin, Shao-Wu& Shi, Guangsi& Wang, Li. 2017. 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, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1190061
Modern Language Association (MLA)
Li, Jing…[et al.]. Optimization of Indoor Thermal Comfort Parameters with the Adaptive Network-Based Fuzzy Inference System and Particle Swarm Optimization Algorithm. Mathematical Problems in Engineering No. 2017 (2017), pp.1-13.
https://search.emarefa.net/detail/BIM-1190061
American Medical Association (AMA)
Li, Jing& Yin, Shao-Wu& Shi, Guangsi& Wang, Li. Optimization of Indoor Thermal Comfort Parameters with the Adaptive Network-Based Fuzzy Inference System and Particle Swarm Optimization Algorithm. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-13.
https://search.emarefa.net/detail/BIM-1190061
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1190061