نتایج جستجو برای: neural network model
تعداد نتایج: 2728035 فیلتر نتایج به سال:
life style and life expectancy of inhabitants have been affected by the increase of particulate matter 10 micrometers or less in diameter (pm10) in cities and this is why maximum pm10 concentrations have received extensive attention. an early notice system for pm10 concentrations necessitates an accurate forecasting of the pollutant. in the current study an artificial neural network was used t...
â abstract: in this paper, artificial neural network (ann) was used for modeling the nonlinear structure of a debutanizer column in a refinery gas process plant. the actual input-output data of the system were measured in order to be used for system identification based on root mean square error (rmse) minimization approach. it was shown that the designed recurrent neural network is able to pr...
linear semi-infinite programming problem is an important class of optimization problems which deals with infinite constraints. in this paper, to solve this problem, we combine a discretization method and a neural network method. by a simple discretization of the infinite constraints,we convert the linear semi-infinite programming problem into linear programming problem. then, we use...
reinforced concrete (rc) slabs exhibit complexities in their structural behavior under load due to the composite nature of the material and the multitude and variety of factors that affect such behavior. current methods for determining the load-deflection behavior of reinforced concrete slabs are limited in scope and are mostly dependable on the results of experimental tests. in this study, an ...
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...
this study employs a gmdh neural network model, which has high capability in recognition of complicated non-linear trends especially with small samples, for modeling and predicting iranian gdp growth. first a fundamental model containing 7 independent variables together with dependent variable is designed and then by using deductive process and omission of one variable at a time, a total of 18 ...
The accurate determination of river flow in watersheds without sufficient data is one of the major challenges in hydrology. In this regard, given the diversity of existing hydrological models, selection of an appropriate model requires evaluation of the performance of the hydrological models in each region. The objective of this study was to compare the performance of artificial neural network ...
in general, amount of sludge will definitely increase in near future and composting processes, optimum composting conditions and compost use as fertilizer and soil amendment will then be significant research topics. the present study was conducted for o2 parameter estimation by multiple regression and artificial neural networks methods. daily temperature, ch4, h2s, co2 and o2 measurements were ...
ecological changes resulting from climate conditions can severely affect human societies especially in the area of economy and safety. climate catastrophes may cause social and economic tension. forecasting such changes accurately can help the government to control the disasters and to achieve possible benefits (such as water supply in flood). weather forecasting is the application of science a...
Evaporation is one of the most important components of hydrologic cycle.Accurate estimation of this parameter is used for studies such as water balance,irrigation system design, and water resource management. In order to estimate theevaporation, direct measurement methods or physical and empirical models can beused. Using direct methods require installing meteorological stations andinstruments ...
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