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Flood is one of the well-known facts which endanger the lives and human resources around the world. Thus, accurate estimation of flood discharge in every region can lead to more precise hydraulic structures with adequate capacity to avoid the above problems. Usually, the estimation of flood capacity in any station required sufficient data. However, the lake of sufficient and long-term hydrological...
Nowadays, many researches are made to estimate some of socio-economic variables in which methods such as regression, time series (ARIMA, AR and etc.), Artificial Neural Networks (ANN) and so on are used. In this paper integrated System Approach and ANN are applied for estimating affects of subsidy on electricity consumption and social welfare. Actual electricity price is estimated by ANN, which has...
Air temperature, relative humidity and vapor pressure data during 1993-2004 for city of Manjil in Iran were used for the estimation of wind speed in future time domain using artificial neural network method. The estimations of wind speed were made using three combinations of data sets namely: (i) month of the year, monthly mean daily air temperature and relative humidity as inputs and wind speed as...
This paper introduces a new wireless networking approach to multiparameter vehicle navigation systems based on ant algorithm. The proposed system finds the optimum multiparameter route between a pair of origin and destination (O/D). The importance rate of each parameter is adjustable by the user. This system acquires traffic data in online and offline modes. In online mode, traffic data are available...
Accurate demand forecasting is one of the most crucial issues in inventory management of spare parts in process industries. The problem of modeling future consumption becomes especially difficult for lumpy patterns, which characterized by intervals in which there is no demand and, periods with actual demand occurrences with large variation in demand levels. However, many of these methods may perform...
Due to various changes in electricity consumption in Iran, it is hard to model with conventional methods and makes it suitable to estimate with Artificial Neural Network. Altough this method typically has been used to forecast short term consumptions, we use Neural Network to forecast annual consumption This paper illustrates an Artificial Neural Network (ANN) approach based on supervised multi layer...
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