Sharif Digital Repository

Groundwater beneath the cities is becoming an important and valuable resource. Conjunctive use of surface and groundwater is likely to become increasingly more common as urban population grows by time. Therefore, one important requirement for urban water management planning is forecasting the groundwater level fluctuations. Unfortunately less experience and information is available to evaluate the fluctuations of groundwater level in urban environment compare to the natural systems, also different processes (sources) are involved in an urban water cycle, which all together make it more complicated to study. Similar to many other megacities, there is a serious lack of hydrogeological and... 

today's financial markets such as stock market are more attractive and important position and wealth are considered income and therefore attracts many people have. But the other hand, activity in these markets requires a high risk of admission. The point that is important is that the risk of investing in these markets can be predicted to some extent with the trend of stocks and securities can be controlled. Time series trend of stock prices and non-static characters is excited. But analysis of such behavior is impossible, i.e., reliance on sophisticated tools and of course accept the possibility of an error can be predicted price to pay. Synthetic models of artificial intelligence today, due... 

Success in forecasting and analyzing sales for a given good or service can mean the difference between profit and loss for an accounting period and, ultimately, the success or failure of the business itself. Therefore reliable prediction of sales becomes a very important task. This thesis presents a novel sales forecasting approach by integration of Genetic Fuzzy Systems (GFS) and Data Clustering to construct a sales forecasting expert system. At first, we use stepwise regression analysis (SRA) to determine factors which have most influence on sales. At the next stage we divide our raw data into k clusters by means of K-means algorithm. Finally, all clusters will be fed into independent... 

The Urmia Lake in the north west of Iran and one of the most important habitats in the world is in danger of drying. Drought of recent years, increasing of temperature and evaporation and also construction of several dams in Urmia Lake basin can be considered as the main factors of decreasing the Lake level. Simultaneous forecasts of lake level and inflow streams help us to make better decisions for allocating and releasing enough water for environmental demands such as Urmia Lake. This study aims to determine relationships between historical information of basin with streamflow of Ajichai and Urmia Lake level, and use them for predicting the further conditions. In this process, streamflow... 

Forecasting has a crucial role for decision makers in economics and finance and is frequently used by firms, government institutions and professional economists. Academic studies in macroeconomics modeling and economic forecasting have been historically concentrated on models with few variables. But in practice, a decision maker has a large amount of information in the form of variables which has some predictive content for the target variable. One way to handle the large-scale information in forecasting is to use forecast combination methods. These methods generally combine the simple forecasts of some target variable while the forecasts are weighted according to their relative accuracy,... 

In this Thesis, a multi period portfolio optimization consisting stocks, gold and risk free asset is considered, in which periodical reinvestment and withdrawing is possible. Maximizing the net present value of investor’s cash flow is the objective. Due to the existence of uncertain parameters, two robust counterpart models are developed. In the first model, a conservative robust model is presented to generate feasible solution in all cases. In the second one, the conservative degree of investor is adjustable to control the risk of the model by investor appropriately. For evaluating the proposed models, the data of 5 well known stocks of Tehran market and gold prices are gathered. By using... 

Forecasting model of water consumption amounts could be used in order to manage water resources for future condition of city. In this thesis, a model for forecasting water demand for Tehran has been presented by evaluating regression models and intelligent models. In this study, uncertainties which are connected to climate and population changes are taken into account. The considered variables include minimum, maximum and medium temperature, precipitation and solar radiation. Considering objectives of this thesis and various forecasting methods and their advantages and regional conditions of Tehran, in addition to regression analysis, perceptron neural network, probabilistic neural network... 

Value at risk of an asset, is the asset’s expected maximum loss for a certain period of time and at a specified confidence level. Value-at-Risk can be calculated in the bank with its inter-nal method or standardized method. when a method have more violation number then bank need to keep more daily capital requirements. under the Basel 2 agreement if the violation of method more than 10 times in year, the Bank uses the standardized method.
There are trade off Between daily capital charge and violations. Therefore, existing methods for calculating the value at risk, usually lead to much daily capital charge or many violations. Studies show with combination of different methods to calculate... 

Iran is regarded as a dry land and has suffered from extreme to severe drought conditions in recent years. Drought – which is mainly caused by shortage in rainfall – affects the normal life in Iran. Development of tools for effectively monitoring and predicting drought intensity might help the policy makers to reduce the vulnerability of the areas affected by drought. In this thesis, we showed that the intensity of drought can be predicted using satellite imagery data and recurrent neural networks. To this end, the standardized precipitation index (SPI) was chosen as an index for drought and normalized deviation of vegetation index (NDVI) as a remote sensing measure extracted from NOAA-AVHRR... 

Energy is of the essential elements to improve every nation’s economy and society, which is influenced by a variety of parameters. Thus many empirical methods have been represented to assess the said parameters using other parameters by which they are affected. In this research, Linear Genetic Programming method (LGP) has been used for assessment, which has been applied to project the global shining of the sun in two Iranian metropolises (Tehran and Kerman), and also natural gas utilization in both industrial and domestic sectors. In this research, authentic data from the empirical results existing in technical documents has been used to develop the models. Most prevalent effective... 

Volatility is the most important components in numerous finance applications. So, the methods of volatility forecast with reasonable accuracy require a deep attention.In this thesis with considering several distributions for error term, GARCH forecasting performance is evaluated on the intra- day data of "Foolad" stock returns by two loss functions of "MAE" and "HMAE". This evaluation is done in three forecast horizons, 1 day, 5 days and 20 days. Finally, the result of this study is as follows. GARCH (1, 1) forecast model with skewed t- student error distribution has the minimum value in the both loss functions for 1 day and 5 day forecast horizons. Also GARCH (1, 1) forecast model with t-... 

Drought is a common phenomena which has a lot of unwanted conse-quences on human being life and environment. Drought forecasting plays a significant role in water resources and environmental systems. Considering IRAN inappropriate location which is on the arid and semi-arid area of the earth and Widespread damages which are related to drought during recent years in iran; importance of developing an accurate model by using new technologies becomes quite inevitable. In the last decay Neural Networks have appeared very useful in non-Stationary and non-linear time Series forecasting and modeling.
This study is about to use conjunctive model of adaptive neuro fuzzy inference system and... 

In this thesis we are going to forecast the hourly consumption of the electricity over the country with two models and then, combine them. The first model decomposes the consumption to a deterministic trend and a stochastic residual. The second one assumes that the trend part is also stochastic.Once the consumption is being predicted separately by the models, in the second part of the thesis, we will combine the results to get a final prediction. This prediction is going to be compared with the load forecast of the Dispatching Unit of the electricity network as a base model. We are going to answer two important questions: firstly, does combining the models give a better prediction or not,... 

Cloud computing is a way to increase capacity or add capabilities dynamically without investing in new infrastructure. The purpose of this project is the use of specialized algorithms for efficient energy management for cloud computing environments.One of the issues that is very important with respect to cloud computing is considering lifetime of servers or physical machines. Servers are some of the most important and critical elements of cloud computing. Server costseffect on the costs of the entire cloud computing system and the interference of serverseffects on entire system. Lifetime of each sever is dependent on a few factors, the most important of which is the number of switching... 

Due to the significance of exchange rates in economic policy making, different patterns have been proposed so as to explain the behavior, provide ways to model and deliver tools to forecast different exchange rates. Using a novel approach, this thesis tries to investigate the behavior of exchange rates by identifying time series nature of exchange rates, and performing nonlinear test for daily data between years 2003 to2006. In this study, we try to model and forecast the daily exchange rates by the use of Artificial Neural Networks (ANN). We also compare the results with ARIMA model outputs based on measures for forecasting accuracy. 80 percent of the daily data, that is, 1160 days from... 

In this study, in the base case using a modeling system WRF=CAMx Distribution concentration of all pollutants from mobile sources in an episode of 60 days (November and December 2015) is calculated in Tehran. In this context, the emissions inventory related to mobile sources outputs the code in Fortran and WRF meteorological model to model air quality prepared and then using the CAMx, Tehran’s air quality is simulated. In order to verification in this case, the results of pollutant concentration NO2, CO, PM2٫5, with concentrations of air pollution monitoring stations compared. Given that in this study the concentration of pollutants from mobile sources is modeled, predicted by the model,... 

Financial and monetary markets are appropriate areas of applying Chaos Theory. Firstly, current theories of financial and monetary economics state that economic and financial variables such as exchange rates and stock prices are stochastic, so forecasting them is almost impossible. Secondly, if we find the hidden ordered and deterministic trends, we can achieve considerable profits. In this piece of research, we evaluate different methods and tests of detecting chaos in financial time series, and choose the most applicable methods to test financial markets’ indices. The main three indices of Tehran Stock Exchange, including Price, Finance and Industry indices, are examined. A sample of the... 

Today, with advances in technology and communication equipments, supply chain management plays an important role in different industries. Bullwhip effect is the significant factor which can reduce efficiency of supply chain and increases costs and lead time of services and products to the ultimate customer. In this thesis we have investigated on forecasting method and ordering policy in the bullwhip effect. Basic model based on beer game, moving average, Holt and Brown are 4 models which were studied. Also we defined desired stock and desired stock line which the difference between desired and actual stock and also difference between desired and actual stock line in any period, have... 

There has been great progress in Intelligent Transportation Systems (ITS) during the past decade. It is often difficult to manage vehicle traffic systems due to high variations and complexity. Intelligent Transportation Systems try to devise more efficient and more reliable solutions for vehicle traffic systems. Many ITS applications rely on short-term predictions of traffic state and it is crucial to provide reliable estimates of the traffic state in near future.Providing an accurate estimate of transportation time in a specific piece of street is a key task in Intelligent Traffic Systems (ITS). This estimate can be either for the moment or a future prediction. A practical ITS must be... 

Severe Plastic Deformation (SPD) Processes have drawn lots of attention due to their ability to refine grain size and develop some properties of bulk metals and alloys. After deformation, however, ductility and formability of metals are reduced. Annealing has been used as a solution for improvement of these characteristics after deformations even after SPD processes. On the other hand, there is a possibility that during annealing grains could grow, therefore it can neutralize the effect of SPD process. Consequently, predicting behavior and evolution of microstructure during annealing finds an important role. In this research, accordingly, vertex model have been used in order to predict...