Title :
Multi-Sensor Data Fusion in Coal Mine Safety Supervision
Author :
Gang, Hua ; Yi, Bao ; Wen-song, Liu
Author_Institution :
China Univ. of Min.& Technol., Xuzhou
Abstract :
This paper applies the fuzzy closeness degree and RBF neural network in the coal mine safety supervision to fuse the environment feature data in the local district. The fusion result can evaluate the safety status of the coal mine production. To improve the precision of data fusion, this paper adjusts the RBF neural network parameters with hierarchy genetic algorithm. The research result shows that using the method proposed in this paper can converge faster with a higher precision, comparing to the traditional method.
Keywords :
fuzzy set theory; genetic algorithms; mining; radial basis function networks; safety; sensor fusion; coal mine safety supervision; fuzzy closeness degree RBF neural network; genetic algorithm; multisensor data fusion; Cities and towns; Electrical safety; Fuses; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Intelligent networks; Neural networks; Paper technology; Sensor fusion; RBF neural network; data fusion; fuzzy closeness degree; hierarchy genetic algorithm;
Conference_Titel :
Information Acquisition, 2007. ICIA '07. International Conference on
Conference_Location :
Seogwipo-si
Print_ISBN :
1-4244-1220-X
Electronic_ISBN :
1-4244-1220-X
DOI :
10.1109/ICIA.2007.4295728