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A hybrid artificial intelligence and Internet of Things model for generation of renewable resource of energy
Faculty
Computer Science
Year:
2019
Type of Publication:
ZU Hosted
Pages:
Authors:
Mohammed Abdel Basset Metwally Attia
Staff Zu Site
Abstract In Staff Site
Journal:
IEEE Access IEEE
Volume:
Keywords :
, hybrid artificial intelligence , Internet , Things model
Abstract:
The world is consuming large amounts of energy in various forms like electric energy and mechanical energy. Since the electrical energy is an important factor for the development of the world, many researchers tried to generate electricity from renewable energy sources collected by sensors in order to overcome the shortage of electrical energy for household appliances and industrial areas. In this paper, we develop Internet-of-Things (IoT) based system to generate electrical energy from multiple sensors for household appliances and industrial areas. Different sensors namely piezoelectric sensor, body heat to electric converter and solar panel are utilized and connected to the power storage circuit for generation of electrical energy. Two different Artificial Intelligence (AI) models such as Artificial Neural Network (ANN), Adaptive Network based Fuzzy Inference System (ANFIS) are utilized for the total power generated from renewable energy resources. Validation is done through the statistical parameters such as Root Mean Square Error (RMSE) and R2 coefficient of correlation. Result outcome from the models shows that ANN performance is better than ANFIS.
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Saber Mohamed, "Training and Testing a Self-Adaptive Multi-Operator Evolutionary Algorithm for Constrained Optimization", ELSEVEIR, 2015
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Saber Mohamed, "An Improved Self-Adaptive Differential Evolution Algorithm for Optimization Problems", IEEE, 2013
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