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Comparison Of Neural Network And Differential Evolution In Estimation Of Air Quality Using Mean Square Error
2014
IOSR Journal of Computer Engineering
Softcomputing techniques are fast becoming reliable and efficient means of prediction and estimation. This has made their application more wide spread in recent years. With the growing need for intelligent devices and systems comes the need to explore these techniques even further. This paper applies neural networks and differential evolution (two of the most effective softcomputing algorithms) to the estimation of air quality and compares the accuracy of their results using the mean square
doi:10.9790/0661-1618124129
fatcat:5olkwmbyh5bopdgiweojqvph3m