Daily irrigation water demand prediction using Adaptive Neuro- Fuzzy Inferences Systems (ANFIS)
نویسنده
چکیده
One of the main problems in the management of large water supply and distribution systems is the forecasting of daily demand in order to schedule pumping effort and minimize costs. This paper examines a methodology for consumer demand modeling and prediction in a real-time environment of an irrigation water distribution system. The approach is based on Adaptive Neuro-Fuzzy Inferences System (ANFIS) technique. The data was taken from a Cretan water company named O.A.DY.K and concerns the area of prefecture of Chania. ANFIS was comprised with traditional forecasting techniques as the autoregressive (AR) and autoregressive moving average (ARMA) models. ANFIS provide the better prediction results of daily water demand. Key-Words: ANFIS; forecasting; neuro-fuzzy; water forecasting, irrigation water, neuro-fuzzy forecasting
منابع مشابه
Adaptive Network-based Fuzzy Inference System-Genetic Algorithm Models for Prediction Groundwater Quality Indices: a GIS-based Analysis
The prediction of groundwater quality is very important for the management of water resources and environmental activities. The present study has integrated a number of methods such as Geographic Information Systems (GIS) and Artificial Intelligence (AI) methodologies to predict groundwater quality in Kerman plain (including HCO3-, concentrations and Electrical Conductivity (EC) of groundwater)...
متن کاملCoastal Water Level Prediction Model Using Adaptive Neuro-fuzzy Inference System
This paper employs Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict water level that leads to flood in coastal areas. ANFIS combines the verbal power of fuzzy logic and numerical power of neural network for its action. Meteorological and astronomical data of Santa Monica, a coastal area in California, U. S. A., were obtained. A portion of the data was used to train the ANFIS network, wh...
متن کاملPredicting the Risk of Fault-Induced Water Inrush Using the Adaptive Neuro-Fuzzy Inference System
Sudden water inrush has been a deadly killer in underground engineering for decades. Currently, especially in developing countries, frequent water inrush accidents still kill a large number of miners every year. In this study, an approach for predicting the probability of fault-induced water inrush in underground engineering using the adaptive neuro-fuzzy inference system (ANFIS) was developed....
متن کاملPrediction of toxicity of aliphatic carboxylic acids using adaptive neuro-fuzzy inference system
Toxicity of 38 aliphatic carboxylic acids was studied using non-linear quantitative structure-toxicityrelationship (QSTR) models. The adaptive neuro-fuzzy inference system (ANFIS) was used to construct thenonlinear QSTR models in all stages of study. Two ANFIS models were developed based upon differentsubsets of descriptors. The first one used log ow K and LUMO E as inputs and had good predicti...
متن کاملModelling Bod Concentration by Using Adaptive Neuro-fuzzy Inference System
BOD is a parameter frequently used to evaluate the water quality on different rivers. The aim of the present study is to investigate applicability of artificial intelligence techniques such as ANFIS (Adapti ve Neuro-Fuzzy Inference System) in water quality BOD prediction for the case study, Mahi river at Khanpur in Thasara Taluka of Kheda District in Gujarat State, India. The proposed technique...
متن کامل