FORECASTING THE RAINFALL DATA BY ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM

被引：0

作者：

Yarar, Alpaslan ^{[1
]}

Onucyildiz, Mustafa ^{[1
]}

Sevimli, M. Faik ^{[2
]}

机构：

[1] Selcuk Univ, Dept Civil Engn, Konya, Turkey

[2] Selcuk Univ, Dept Environm Engn, Konya, Turkey

来源：

SGEM 2009: 9TH INTERNATIONAL MULTIDISCIPLINARY SCIENTIFIC GEOCONFERENCE, VOL II, CONFERENCE PROCEEDING: MODERN MANAGEMENT OF MINE PRODUCING, GEOLOGY AND ENVIRONMENTAL PROTECTION | 2009年

关键词：

ANFIS; Regression; Rainfall Forecasting; NETWORK APPROACH; PREDICTION; MODEL;

D O I：

暂无

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Konya is the biggest city of Turkey in terms of area and agricultural land, on the other hand sixth biggest city in terms of population. Because of the decrease of rainfall and increase in temperature, the agricultural production and daily water consumption are effected negatively in last years. Rainfall, one of the basic parameters of the hydrological cycle, has a big importance to determine the water budgets and to improve the water supply policy. In this study, monthly total rainfall data belong to Konya between 1970-2002 years, have been studied to forecast by Adaptive Neuro-Fuzzy Inference System (ANFIS). And model's performance has been evaluated by comparison with the Lineer Regression (LR) as one of the traditional methods.

引用

页码：191 / +

页数：2

共 17 条

[1]

[Anonymous], 1997, IEEE T AUTOM CONTROL, DOI DOI 10.1109/TAC.1997.633847

[2] River flow forecast for reservoir management through neural networks [J].