In this paper a new black box approach for rainfall-runoff modelling at a daily scale is presented. The considered black box model is non-linear regression based on Parzen probability density function. When using only measured rainfall as an input to any black box model there is a serious problem with building in the necessary memory. A standard approach to tackle this issue is to force a black...

In this paper an application of ANN models are presented to estimate the roughness of a given finishing operation. The approach uses the acoustic emission sensor as an information source to improve the estimation capability of the ANN model. Building up the ANN model to avoid the problem of overlapping and noninvertable dependencies used a new approach. The model was built up and the roughness ...

This study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ANN) in broiler chicken. Artificial neural networks (ANNs) are powerful tools for modeling systems in a wide range of applications. The ANN model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kca...

Over the last decades or so, artificial neural networks (ANNs) have become one of the most promising tools for modelling hydrological processes such as rainfall-runoff processes. In most studies, ANNs have been demonstrated to show superior result compared to the traditional modelling approaches. They are able to map underlying relationships between input and output data without detailed knowle...

Background: Changes in temperature and precipitation pattern seriously affect the amount of river runoff coming into Dam Lake. These changes could influence the operating conditions of reservoir systems such as Jor hydropower reservoir system (Malaysia) with the total capacity of 150 MW. So, it is necessary to analyze the effect of changes in weather parameters on the river runoff and consequen...