Sharif Digital Repository

Water demand forecasting and modeling is very important and needful in water resource planning and management as well as water consumption forecasting. The forecasting helps the managers to design and operate various infrastructures of water supply such as tanks and other distribution equipments. Nowadays, intelligent systems are very efficient and practical tools because of their high ability in forecasting and independency from limitative assumptions in classic methods. In this thesis, one of the newest methods, called support vector regression method, is used to forecast monthly demands of water consumption in Tehran, Iran. To develop the method, data is first preprocessed through... 

In parallel to the growing of population in Tehran metropolitan, air pollution in this city has become to a major problem. From which high concentration of pollutants have adverse effects on public health, accurate estimating and forecasting of concentrations for several days ahead, can provide the possibility to implement the management measures to reduce hazard and risks. Among the air pollution models, application of statistic models based on neural network in comparison to the traditional deterministic models are easier and less costly. In most studies, static models use a classical single MLP to predict one step ahead. For this purpose ANN models are required to estimate next value of...