A review on state-of-the-art applications of data-driven methods in desalination systems
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 …
can result in the further development of desalination technologies and tackling the need for …
Demand forecasting with color parameter in retail apparel industry using artificial neural networks (ANN) and support vector machines (SVM) methods
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 …
performed by using artificial intelligence to minimize error rate, in the retail garment industry …
[PDF][PDF] Neuralnet: training of neural networks.
F Günther, S Fritsch - R J., 2010 - svn.r-project.org
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 …
perceptrons in the context of regression analyses, ie to approximate functional relationships …
Estimating physical composition of municipal solid waste in China by applying artificial neural network method
Physical composition of municipal solid waste (PCMSW) is the fundamental parameter in
domestic waste management; however, high fidelity, wide coverage, upscaling, and year …
domestic waste management; however, high fidelity, wide coverage, upscaling, and year …
Neural networks in R using the Stuttgart neural network simulator: RSNNS
CN Bergmeir, JM Benítez Sánchez - 2012 - digibug.ugr.es
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 …
regression. We describe the R package RSNNS that provides a convenient interface to the …
Remote sensing-based biomass estimation of dry deciduous tropical forest using machine learning and ensemble analysis
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 …
ecosystems are increasingly threatened by climate change and deforestation in recent …
[HTML][HTML] Deception in the eyes of deceiver: A computer vision and machine learning based automated deception detection
There is growing interest in the use of automated psychological profiling systems,
specifically applying machine learning to the field of deception detection. Several …
specifically applying machine learning to the field of deception detection. Several …
Prediction of copper ions adsorption by attapulgite adsorbent using tuned-artificial intelligence model
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 …
quantified. This research is established to predict copper ions adsorption (Ad) by Attapulgite …
[PDF][PDF] Comparison of neural network training functions for hematoma classification in brain CT images
B Sharma, K Venugopalan - IOSR Journal of Computer …, 2014 - researchgate.net
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 …
networks (ANN). Training neural networks is a complex task in the supervised learning field …