نتایج جستجو برای: neural model
تعداد نتایج: 2325349 فیلتر نتایج به سال:
Drought Forecasting in Khash City by Using Neural Network Model Hossein Negaresh Associate Professor of Geography and Environmental PlanningFaculty, University of Sistan & Baluchestan Mohsen Armesh Holding Master Degree in climatology in Environmental Planning Extended Abstract 1- Introduction Drought is condition of lack of rainfall and increase in temperature occurring in...
Although, speech recognition systems are widely used and their accuracies are continuously increased, there is a considerable performance gap between their accuracies and human recognition ability. This is partially due to high speaker variations in speech signal. Deep neural networks are among the best tools for acoustic modeling. Recently, using hybrid deep neural network and hidden Markov mo...
Introduction: These days, there is a consensus that emotional intelligence plays an important role in the success of individuals in different areas of life. Persons with higher emotional intelligence had lower stress in dealing with demands and pressures in the workplace. The purpose of this study was to use artificial neural network to predict job stress and to compare the performance of this ...
Introduction: Protein kinase causes many diseases, including cancer; therefore, inhibiting them plays an important role in the treatment of many diseases. Traditional discovery inhibitors of this enzyme is a time-consuming and costly process. Finding a reliable computer-aided drug discovery tools which can detect the inhibitors will reduce the cost. In this study, it is attempted to separate ki...
in this paper, i develop three forecasting models: namely structural, times series, and artificial neural networks; to forecast iranian inflation rates. the structural model uses aggregate demand and aggregate supply approach, the time series model is based on the standard arlma technique, and the artificial neural network applies multi-layer back propagation model the latter, which is rooted i...
This paper uses nonlinear regression, Artificial Neural Network (ANN) and Genetic Programming (GP) approaches for predicting an important tangible issue i.e. scours dimensions downstream of inverted siphon structures. Dimensional analysis and nonlinear regression-based equations was proposed for estimation of maximum scour depth, location of the scour hole, location and height of the dune downs...
During the recent decades, neural network models have been focused upon by researchers due to their more real performance and on this basis, different types of these models have been used in forecasting. Now, there is a question that which kind of these models has more explanatory power in forecasting the future processes of the stock. In line with this, the present paper made a comparison betw...
Rivers are important as the main source of supply for drinking, agriculture and industry.However, drinking water quality in terms of qualitative parameters, is the most important variable. Studias and predicting changes in quality parameters along a river, are one of the goals of water resources planners and managers. In this regard, many water quality models in order to maintain better water ...
Despite the fact that shape-memory alloy (SMA) has several mechanical advantages as it continues being used as an actuator in engineering applications, using it still remains as a challenge since it shows both non-linear and hysteretic behavior. To improve the efficiency of SMA application, it is required to do research not only on modeling it, but also on control hysteresis behavior of these m...
Accurate models of Overcurrent (OC) with inverse time relay characteristics play an important role for coordination of power system protection schemes. This paper proposes a new method for modeling OC relays curves. The model is based on fuzzy logic and artificial neural networks. The feed forward multilayer perceptron neural network is used to calculate operating times of OC relays for various...
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