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Urban Water Consumption Forecasting Using Intelligent Systems
, M.Sc. Thesis Sharif University of Technology ; Akhavan Niaki, Taghi (Supervisor)
Abstract
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...
Estimation of Origin-Destination Trip Matrix Using Mobile Phone Network’s Spatiotemporal Dataset
, M.Sc. Thesis Sharif University of Technology ; Shafahi, Yousef (Supervisor)
Abstract
Knowledge about travel demand patterns is an important requirement for strategic planning and management of urban transportation networks. Use of theoretical trip distribution models such as growth, gravity or intervening opportunities, estimation with the help of questionnaire surveys and development of volume- based O-D estimation methods have been major fields of scientific efforts in recent years.Rapid changes in land use and transportation networks especially in developing countries has raised the importance level of knowledge about changes in travel demand.Traditional approaches are costly, time consuming and suffer from inaccuracies, so,...
Development of a Real-Time Heuristic Algorithm to Integrate Inertial and Celestial Navigation Systems
, M.Sc. Thesis Sharif University of Technology ; Nobahari, Hadi (Supervisor) ; GhanbarpourAsl, Habib (Supervisor)
Abstract
Unscented kalman filter is able to integrate strapdown inertial navigation system (SINS) and celestial navigation system (CNS) and estimate current attitude and gyro drift precisely. However, initial attitude error, accelerometer bias and attitude error caused by gyro drift prior to CNS setting to work may cause large errors in velocity and position. So a novel method is presented for compensating these errors. The proposed method implements Fixed-interval smoothing to the integrated system. The procedure of filtering, smoothing and accelerometer bias estimation has been explained in details. The validity of the designed method has been proved through a simulation which admits the capability...