FORECASTING SHAHARCHAY RIVER FLOW IN LAKE URMIA BASIN USING GENETIC PROGRAMMING AND M5 MODEL TREE

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SAMADIANFARD S.; DELIRHASANNIA R.

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Journal Paper

Paper Information

Journal: Journal of Water and Soil Year:2016 | Volume:29 | Issue:5 Page(s): 1190-1206

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Title

FORECASTING SHAHARCHAY RIVER FLOW IN LAKE URMIA BASIN USING GENETIC PROGRAMMING AND M5 MODEL TREE

Author(s)

SAMADIANFARD S. | DELIRHASANNIA R. | Issue Writer Certificate

Keywords

ESTIMATIONQ2

FLOW DISCHARGEQ1

INTELLIGENCE METHODSQ1

STATISTICAL PARAMETERSQ2

Abstract

Introduction: Precise prediction of river flows is the key factor for proper planning and management of water resources. Thus, obtaining the reliable methods for predicting river flows has great importance in water resource engineering. In the recent years, applications of intelligent methods such as artificial neural networks, fuzzy systems and genetic programming in water science and engineering have been grown extensively. These mentioned methods are able to model nonlinear process of river flows without any need to geometric properties. …

Cites

PERFORMANCE ASSESSMENT OF M5 TREE MODEL AND GENETIC PROGRAMMING IN TABRIZ STATION REFERENCE EVAPOTRANSPIRATION MODELING

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APA: Copy

SAMADIANFARD, S., & DELIRHASANNIA, R.. (2016). FORECASTING SHAHARCHAY RIVER FLOW IN LAKE URMIA BASIN USING GENETIC PROGRAMMING AND M5 MODEL TREE. JOURNAL OF WATER AND SOIL (AGRICULTURAL SCIENCES AND TECHNOLOGY), 29(5), 1190-1206. SID. https://sid.ir/paper/141461/en

Vancouver: Copy

SAMADIANFARD S., DELIRHASANNIA R.. FORECASTING SHAHARCHAY RIVER FLOW IN LAKE URMIA BASIN USING GENETIC PROGRAMMING AND M5 MODEL TREE. JOURNAL OF WATER AND SOIL (AGRICULTURAL SCIENCES AND TECHNOLOGY)[Internet]. 2016;29(5):1190-1206. Available from: https://sid.ir/paper/141461/en

IEEE: Copy

S. SAMADIANFARD, and R. DELIRHASANNIA, “FORECASTING SHAHARCHAY RIVER FLOW IN LAKE URMIA BASIN USING GENETIC PROGRAMMING AND M5 MODEL TREE,” JOURNAL OF WATER AND SOIL (AGRICULTURAL SCIENCES AND TECHNOLOGY), vol. 29, no. 5, pp. 1190–1206, 2016, [Online]. Available: https://sid.ir/paper/141461/en

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