Water allocation improvement in river basin using Adaptive Neural Fuzzy Reinforcement Learning approach

نویسندگان

  • B. Abolpour
  • M. Javan
  • M. Karamouz
چکیده

Optimal use of water is an important objective of water resource development projects all over the world. An integrated approach toward better water resources management in river basins for irrigation planning is needed to find optimal water use policies. In the past, researchers used variables affecting crop pattern and reservoir releases as decision variables (Yeh, 1985). Labadie, 1993, found discrepancies in simulation and optimization models which are important factors in non-adaptive and weak system managements in river basins. These models become more complicated considering conflicting objectives, stochastic hydrology behavior, and uncertain consumptive water use. Labadie, 1993, presented a combined simulation-optimization strategy for river system management. In his studies, decision variable was reservoir release and objective function was maximization of power generation. However, the objective of his study was to assess directly the optimal water use. The other group of studies is concerned with indirect optimization of water use by selecting the best strategies or alternatives in the river basin or even on the farms. Multi-objective methods have been widely used in different water resource projects. Bogardi & Nachtnebel, 1994, used multicriteria decision analysis in the study of water resources management. Other applications of this group can be found in the works of.Karamouz et al., 1992, and Owen et al., 1997. The theory of fuzzy logic provides a mechanism to represent the degree of satisfaction of reservoir objective through the use of fuzzy membership function measures that can be combined in an integrated fashion. The fuzzy approach, alluding to the vagueness or imprecision inherent in problems of this type, has found increasing application in many fields. Fontane et al., 1997, applied reservoir operation based on Fuzzy Logic concept in order to deal with imprecise objectives for the reservoirs located in the monographic area on the Cache la Poudre river basin in the northern Colorado. Sasikumar and Mujumdar, 1998, developed a Fuzzy Waste-Load Allocation Model (FWLAM) for water quality management of a river system using fuzzy multiple objective optimization. Dubrovin et al., 2002, used a new methodology for fuzzy inference and compared it with a traditional (Sugeno style) method, for multipurpose real-time reservoir operation. In these researches, it is implicitly

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Hybrid Models Performance Assessment to Predict Flow of Gamasyab River

Awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. Therefore, the present study two hybrid models, Wavelet- Adaptive Neural Fuzzy Interference System (WANFIS) and Wavelet- Artificial Neural Network (WANN) are used for flow prediction of Gamasyab River (Nahavand, Hamedan, Iran...

متن کامل

Artificial intelligence-based approaches for multi-station modelling of dissolve oxygen in river

ABSTRACT: In this study, adaptive neuro-fuzzy inference system, and feed forward neural network as two artificial intelligence-based models along with conventional multiple linear regression model were used to predict the multi-station modelling of dissolve oxygen concentration at the downstream of Mathura City in India. The data used are dissolved oxygen, pH, biological oxygen demand and water...

متن کامل

Hybrid Models Performance Assessment to Predict Flow of Gamasyab River

Awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. Therefore, the present study two hybrid models, Wavelet- Adaptive Neural Fuzzy Interference System (WANFIS) and Wavelet- Artificial Neural Network (WANN) are used for flow prediction of Gamasyab River (Nahavand, Hamedan, Iran...

متن کامل

Long-term Streamflow Forecasting by Adaptive Neuro-Fuzzy Inference System Using K-fold Cross-validation: (Case Study: Taleghan Basin, Iran)

Streamflow forecasting has an important role in water resource management (e.g. flood control, drought management, reservoir design, etc.). In this paper, the application of Adaptive Neuro Fuzzy Inference System (ANFIS) is used for long-term streamflow forecasting (monthly, seasonal) and moreover, cross-validation method (K-fold) is investigated to evaluate test-training data in the model.Then,...

متن کامل

Modeling of streamflow- suspended sediment load relationship by adaptive neuro-fuzzy and artificial neural network approaches (Case study: Dalaki River, Iran)

Modeling of stream flow–suspended sediment relationship is one of the most studied topics in hydrology due to itsessential application to water resources management. Recently, artificial intelligence has gained much popularity owing toits application in calibrating the nonlinear relationships inherent in the stream flow–suspended sediment relationship. Thisstudy made us of adaptive neuro-fuzzy ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Appl. Soft Comput.

دوره 7  شماره 

صفحات  -

تاریخ انتشار 2007