The integration of Photovoltaic (PV) systems requires the implementation potential PV power forecasting techniques to deal with high intermittency weather parameters. In prediction process, Genetic Programming (GP) based on Symbolic Regression (SR) model has a widespread deployment since it provides an effective solution for nonlinear problems. However, during training SR models might miss opti...

Abstract Food instability has been linked to infertility, health issues, accelerated aging, incorrect insulin regulation, and more. Innovative approaches increased food availability quality. Agriculture environment monitoring systems need IoT machine learning. sensors provide all necessary data for agriculture production forecast, fertilizer management, smart irrigation, crop monitoring, diseas...

The advanced design of an analog mixed-signal circuit is not simple enough to meet the requirements performance matrix as well robust operations under process-voltage-temperature (PVT) changes. Even commercial products demand stringent specifications while maintaining system’s performance. main objectives this study are increase efficiency optimization process by configuring in multiple regress...

This paper studies the application of principal component analysis, multiple polynomial regression, and artificial neural network ANN techniques to the quantitative analysis of binary mixture of dye solution. The binary mixtures of three textile dyes including blue, red and yellow colors were analyzed by PCA-Multiple polynomial Regression and PCA-Artificial Neural network PCA-ANN methods. The o...