F&forward artificial neural networks (ANNs) that are tralned with the back-propagation algorithm are a useful tool for modelling environmental systems. They have almady been successfully used to model salinity, nutrient concentrations, air pollution, and algal growth. These successes, coupled with their suitability for modellmg complex systems, have resulted in an increase in their popularity a...

determining the distribution of heavy metals in groundwater is important in developing appropriate management strategies at mine sites. in this paper, the application of artificial intelligence (ai) methods to data analysis,namely artificial neural network (ann), hybrid ann with biogeography-based optimization (ann-bbo), and multi-output adaptive neural fuzzy inference system (manfis) to estima...

This paper utilizes artificial neural networks for temperature forecasting. Our study based on back propagation neural network which is trained and tested based on dataset provided. In formulating the ANN-based predictive model; three-layer network has been constructed. Suitable air temperature predictions can provide farmers and producers with valuable information when they face decisions rega...

An artificial neural network (ANN) model and rule extraction from a trained ANN using genetic algorithm (GA) are applied to predict and advise on the rules for optimal product form design for a particular customer feeling. To map design elements and the affected impressions, principal component analysis (PCA) is employed to determine the essential dimensions for data analysis. By using ANN to e...

Generative models for sequential data based on directed graphs of Restricted Boltzmann Machines (RBMs) are able to accurately model high dimensional sequences as recently shown. In these models, temporal dependencies in the input are discovered by either buffering previous visible variables or by recurrent connections of the hidden variables. Here we propose a modification of these models, the ...

Truncated sharp crested weirs are used to measure flow rate and control upstream water surface in irrigation canals and laboratory flumes. The main advantages of such weirs are ease of construction and capability of measuring a wide range of flows with sufficient accuracy. Artificial neural networks (ANNs) and genetic programming (GP) have recently been used for estimation of hydraulic data. In...

Ensemble learning methods have received remarkable attention in the recent years and led to considerable advancement in the performance of the regression and classification problems. Bagging and boosting are among the most popular ensemble learning techniques proposed to reduce the prediction error of learning machines. In this study, bagging and gradient boosting algorithms are incorporated in...