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...

This document describes the application of machine learning algorithms to solving the problem of handwriting recognition. Two models were explored, namely Naïve Bays and Artificial Neural Network, and ANN was found to generate more accurate recognitions. By setting up our model and training on the MNIST database of handwritten digits, we were able to achieve recognition of handwritten digits wi...

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...

Nowadays, the increase of human population every year results in increasing of water usage and demand. Saen Saep canal is important canal in Bangkok. The main objective of this study is using Artificial Neural Network (ANN) model to estimate the Chemical Oxygen Demand (COD) on data from 11 sampling sites. The data is obtained from the Department of Drainage and Sewerage, Bangkok Metropolitan Ad...

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 ...