نتایج جستجو برای: artificial neural network
تعداد نتایج: 1026358 فیلتر نتایج به سال:
Bedload transport is an essential component of river dynamics and estimation of its rate is important to many aspects of river management. In this study, measured bedload by Helley- Smith sampler was used to estimate the bedload transport of Kurau River in Malaysia. An artificial neural network, genetic programming and a combination of genetic programming and a neural network were used to estim...
Most of existing researches for multi response optimization are based on regression analysis. However, the artificial neural network can be applied for the problem. In this paper, two approaches are proposed by consideration of both methods. In the first approach, regression model of the controllable factors and S/N ratio of each response has been achieved, then a fuzzy programming has been app...
In this study, an artificial neural network was used to predict the minimum force required to single point incremental forming (SPIF) of thin sheets of Aluminium AA3003-O and calamine brass Cu67Zn33 alloy. Accordingly, the parameters for processing, i.e., step depth, the feed rate of the tool, spindle speed, wall angle, thickness of metal sheets and type of material were selected as input and t...
In the present research, the climate change effect on variation of surface runoff of Zarrinehrud located in the Miandoab plain was investigated. In this direction, the scenarios including A1B, A2 and B1 via LARS-WG downscaling model and with applying the HadCM3 general circulation model and artificial neural network model in two different periods (2046-2065, 2080 -2099) were studied. For thi...
the main objective of this paper is to introduce a new intelligent optimization technique that uses a predictioncorrectionstrategy supported by a recurrent neural network for finding a near optimal solution of a givenobjective function. recently there have been attempts for using artificial neural networks (anns) in optimizationproblems and some types of anns such as hopfield network and boltzm...
In recent decades artificial neural networks (ANNs) have shown great ability in modeling and forecasting non-linear and non-stationary time series and in most of the cases especially in prediction of phenomena have showed very good performance. This paper presents the application of artificial neural networks to predict drought in Yazd meteorological station. In this research, different archite...
Common methods to determine the soil infiltration need extensive time and are expensive. However, the existence of non-linear behaviors in soil infiltration makes it difficult to be modeled. With regards to the difficulties of direct measurement of soil infiltration, the use of indirect methods toestimate this parameter has received attention in recent years. Despite the existence of various th...
in arid and semi-arid environments, groundwater plays a significant role in the ecosystem. in the last decades, groundwater levels have decreased due to the increasing demand for water, weak irrigation management and soil damage. for the effective management of groundwater, it is important to model and predict fluctuations in groundwater levels. in this study, groundwater table in kashan plain ...
soil hydraulic properties such as saturated and unsaturated hydraulic conductivity play an important role in environmental research. since direct measurement of these soil hydraulic properties is time-consuming and costly, indirect methods such as pedotransfer functions and artificial neural networks (ann) were developed based on readily available parameters. in this study, the use of ann to pr...
in a closed die forging process, it is impossible to form complex shapes in one stage, and thus it becomes necessary to use preform dies. in the present study, backward deformation method and fe simulation via abaqus software has been used in order to design preform die of the h-shaped parts. in the backward deformation method, the final shape of the part is considered as a starting point and u...
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