NDLI: Adaptive Neuro-fuzzy Inference System on Downstream Water Level Forecasting

Content Provider	IEEE Xplore Digital Library
Author	An-Pei Wang Heng-Yi Liao Te-Hsing Chang
Copyright Year	2008
Description	Author affiliation: Dept. of Civil Eng., Chung-Yuan Christian Univ., Chungli (An-Pei Wang; Heng-Yi Liao; Te-Hsing Chang)
Abstract	To optimize water resource management, a better reservoir operation system is required. However, all flood control decisions depend on many variables; it is never an easy task. For example, water level prediction under tidal effects is one of the essential judgments in flood control problems, and it determines that reservoir release water or not. Therefore, in order to predict the optimal reservoir drainage, avoidable of inundating downstream area, reliable water level prediction system is necessary. A five-layer ANFIS model with three input and one output variables is built in this paper. Differ from other researches in the past, the estuary tide is considered as an input variable in this ANFIS model. Since the downstream area is located in tideland, the tide impacts water level as well as the other two inputs, rainfall and drainage of reservoir. Predicting downstream water level accurately is very valuable for reservoir to manipulate drainage in flood season, and reservoir could control flood efficiently thus. The ten past years of 16 typhoon events with over four thousand hourly data are collected and used to train ANFIS model. Some successful results are displayed in this paper, and it demonstrates that ANFIS is appropriate for forecasting water level.
Starting Page	503
Ending Page	507
File Size	277161
Page Count	5
File Format	PDF
ISBN	9780769533056
DOI	10.1109/FSKD.2008.671
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Adaptive systems Input variables Artificial neural networks Fuzzy Inference System Rivers Floods Tides Danshuei River Reservoirs ANFIS Resource management Water Resource Management Water resources Water Level Fuzzy systems
Content Type	Text
Resource Type	Article

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