DocumentCode
3331101
Title
Prediction of coal mining gas emission based on clustering algorithm and fuzzy neural network
Author
Xiaoyue Liu ; Yiwen Liu ; Zhenyou Zhang ; Lin Zhang
Author_Institution
Coll. of Electr. Eng., Hebei United Univ., Tangshan, China
Volume
2
fYear
2011
fDate
22-24 Aug. 2011
Firstpage
975
Lastpage
978
Abstract
Coal mining gas emission was constrained by many factors. Considering the eight main factors of gas emission, using ant colony clustering and fuzzy C means clustering applied to data pre-processing, determine the membership function of emission. Fuzzy rules extracted from the data sample, establish a fuzzy neural network prediction system of coal mining gas emission.
Keywords
coal; fuzzy neural nets; fuzzy set theory; mining; mining industry; natural gas technology; optimisation; pattern clustering; syngas; ant colony clustering; coal mining gas emission prediction; data preprocessing; fuzzy C means clustering algorithm; fuzzy neural network; fuzzy rules extraction; membership function; Cities and towns; Clustering algorithms; Data mining; Educational institutions; Fuzzy control; Fuzzy neural networks; Simulation; Gas emission; cluster analysis; information fusion; neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
Strategic Technology (IFOST), 2011 6th International Forum on
Conference_Location
Harbin, Heilongjiang
Print_ISBN
978-1-4577-0398-0
Type
conf
DOI
10.1109/IFOST.2011.6021183
Filename
6021183
Link To Document