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Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Precipitation intensity is strong and often lasts for a long time in the Xiangjiang river basin. However, the distribution of time and space is uneven. Moreover, the main stream and tributaries of the Xiangjiang river constitute asymmetric water system on two sides, Which leads the spatial variation of river hydrology and flow gathered fast and downstream flooding. All along, the Xiangjiang river basin has been frequently threatened by floods. The Xiangjiang River is the largest of the Dongting Lake water system and the middle and lower reaches of the Xiangjiang river is China's major grain production bases. So it is a great significance to do mid-to-long-term hydrological forecasting on the Xiangjiang river basin. Because mid-to-long-term hydrological forecasting have a longer period foreseen, people can take early measures to co-ordinate arrangements when solving flood control and fight a drought, water storage and disposal and the contradiction between the various departments. It is very important to hydropower plant production planning, flood prevention and drought control, water resources management and comprehensive utilization. The thesis, based on the mid-to-long-term hydrological phenomena is a typical fuzzy system of the basic thinking, combines cause-and-effect and statistical analysis with fuzzy analysis and chooses predictors such as rainfall and atmospheric circulation in earlier stage which effect the annual maximum peak discharge. Then sets up the fuzzy model of pattern recognition that used to t- e Xiangtan station of the Xiangjiang river. The high accuracy prediction result shows that models are reasonable and worth popularization and application.