The substitution of conventional mathematical models with fast and accurate modeling tools
can result in the further development of desalination technologies and tackling the need for …

In this study, product variety has been taken into account and sales forecasting has been
performed by using artificial intelligence to minimize error rate, in the retail garment industry …

Artificial neural networks are applied in many situations. neuralnet is built to train multi-layer
perceptrons in the context of regression analyses, ie to approximate functional relationships …

Physical composition of municipal solid waste (PCMSW) is the fundamental parameter in
domestic waste management; however, high fidelity, wide coverage, upscaling, and year …

Neural networks are important standard machine learning procedures for classification and
regression. We describe the R package RSNNS that provides a convenient interface to the …

Conventional model-based data processing methods are computationally expensive and
require experts' knowledge for the modelling of a system. Neural networks are a model-free …

Forests play a vital role in maintaining the global carbon balance. However, globally, forest
ecosystems are increasingly threatened by climate change and deforestation in recent …

There is growing interest in the use of automated psychological profiling systems,
specifically applying machine learning to the field of deception detection. Several …

Copper (Cu) ion in wastewater is considered as one of the crucial hazardous elements to be
quantified. This research is established to predict copper ions adsorption (Ad) by Attapulgite …

Classification is one of the most important task in application areas of artificial neural
networks (ANN). Training neural networks is a complex task in the supervised learning field …