DocumentCode :
553100
Title :
An Adaptive Neural Fuzzy Inference System for prediction of average temperature
Author :
Xingfu Wang ; Yongyuan Cheng ; Qixian Qin ; Zhishan Gu
Author_Institution :
Coll. of Comput. Sci., Univ. of Sci. & Technol. of China, Hefei, China
Volume :
2
fYear :
2011
fDate :
26-28 July 2011
Firstpage :
778
Lastpage :
781
Abstract :
Average temperature prediction is important and of great interest because successful prediction of it may promise attractive benefits to our daily life. But the prediction of temperature is complicated and very difficult because of the non-linear nature of the task. In recent years many form of soft computation model are proposed to handle the non-linear problem. In this paper we explore the predictability of average temperature with Adaptive Based Neural Fuzzy Inference System. Simulation results show ANFIS is good alternative to traditional method like BP.
Keywords :
fuzzy neural nets; inference mechanisms; prediction theory; temperature; adaptive neural fuzzy inference system; average temperature prediction; soft computation model; Data models; Fuzzy neural networks; Meteorology; Predictive models; Temperature; Training; ANFIS; Fuzzy Inference System; Temperature Prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-180-9
Type :
conf
DOI :
10.1109/FSKD.2011.6019671
Filename :
6019671
Link To Document :
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