Selection of Abandoned Areas for Implantation of Solar Energy Projects Using Artificial Neural Networks

The increasing demand for energy has intensified recently, requiring alternative sources to fossil fuels, which have become economically and environmentally unfeasible. On the other hand, the increasing land occupation in recent centuries is a growing problem, demanding greater efficiency, particularly in the reuse of abandoned areas, which has become an alternative. An interesting alternative would be installing energy facilities like solar, wind, biomass, and geothermal, in these areas. So, in this way, the aim of this work is to classify these abandoned areas to verify which ones would be suitable for solar energy facilities specifically, to reuse those areas. Artificial Neural Networks (ANNs) trained with the Levenberg-Marquardt Algorithm (LMA) were used for the classification task. The main innovation of this work is the optimization of the initial weights of the ANN using the Quantum-behaved Particle Swarm Optimization (QPSO) metaheuristic, through QPSO-LMA proposed algorithm. In terms of Mean Squared Error (MSE), the QPSO-LMA approach achieved a decrease of 19.6% in relation to the classical LMA training with random initial weights. Moreover, the model’s accuracy showed an increase of 7.3% for the QPSO-LMA over the LMA. To validate this new approach, it was also tested on six different datasets available in the UCI Machine Learning Repository and seven classical techniques established in the literature. For the problem of installing photovoltaic plants in abandoned areas, the knowledge acquired with the solar dataset can be extrapolated to other regions. The two-volume set IFIP AICT 639 and 640 constitutes the refereed post-conference proceedings of the 18th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2021, held in Curitiba, Brazil, during July 11-14, 2021. The conference was held virtually due to the COVID-19 crisis. The 107 revised full papers presented in these proceedings were carefully reviewed and selected from 133 submissions. The papers are organized in the following topical sections: Volume I: Sustainability, sustainable development and circular economy; sustainability and information technologies and services; green and blue technologies; AI and blockchain integration with enterprise applications; PLM maturity, PLM implementation and adoption within industry 4.0; and industry 4.0 and emerging technologies: Volume II: Design, education and management; lean, design and innovation technologies; information technology models and design; and models, manufacturing and information technologies and services.