This paper presents the development artificial neural network (ANN) models for three steady state chemical engineering systems, which are 1) a crude oil distillation column for use in real time optimisation, 2) physical properties of palm oil components, and 3) pore size determination for membrane characterization. Although studies on ANN applications in chemical engineering in the literature a...

This article presents numerical studies on semi-active seismic response control of structures equipped with Magneto-Rheological (MR) dampers. A multi-layer artificial neural network (ANN) was employed to mitigate the influence of time delay, This ANN was trained using data from the El-Centro earthquake. The inputs of ANN are the seismic responses of the structure in the current step, and the ou...

Rainfall is very important parameter in hydrological model. Many techniques and models have been developed for rainfall time series prediction. In this study an artificial neural network (ANN) based model was developed for rainfall time series forecasting. Proposed model used Multilayer perceptron (MLP) network with back propagation algorithm for training. Discharge and rainfall data are took a...

energy management is one of the main ways of the efficient use of energy resources. the prediction of crop yields based on energy inputs can help farmers and policymakers to estimate the level of production. required data for study were randomly collected from 70 broiler farms in north west of iran. the input energies were included human labour, machinery, fuel, feed and electricity and the out...

River water salinity is a significant concern in many countries, considering agricultural and drinking usages. Therefore, prediction of amount of salinity is a necessary tool for planning and management of water resources. Since Achechay River Basin in East Azerbaijan province in Iran passes through saline zones, use of the water for irrigation has become problematic. In this regard, prediction...

This paper describes the development of an Intellectual Property (IP) core in VHDL able to implement a Multilayer Perceptron (MLP) artificial neural network (ANN) topology with up to 2 hidden layers, 128 neurons, and 31 inputs per neuron. Neural network models are usually developed by using programming languages, such as Matlab®. However, their implementation in configurable logic hardware requ...

In this paper, the grouting ability of sandy soils is investigated by artificial neural networks based on the results of chemical grout injection tests. In order to evaluate the soil grouting potential, experimental samples were prepared and then injected. The sand samples with three different particle sizes (medium, fine, and silty) and three relative densities (%30, %50, and %90) were injecte...

abstract process of evapotranspiration (eto) is a major component of the hydrologic cycle that its accurate estimation plays an important role to achieve sustainable development in water balance, irrigation system design and planning and management of water resources. being a function of different metrological parameters and their interactions, evapotranspiration is a complex, nonlinear phenome...

To judge about the performance of designed support system for tunnels, structural forces i.e. peak values of axial and shear forces and moments are critical parameters. So in this study, at first a complete database using finite element method was prepared. Then, a model of artificial neural network (ANN) using multi-layer perceptron was developed to estimate lining structural forces. Sensitivi...