Dear Colleagues,

The Significance of clean energy development technologies has increased in recent years due to the emergence of environmental issues related to the utilization of fossil fuels. In this regard, considerable progress has been achieved in the development of various clean energy systems, including wind turbines, solar thermal, geothermal, etc. Depending on the type of energy source and utilized technology, different factors influence the performance of such systems. Due to the variety of parameters that play a role in the process and performance of clean energy technologies, the complexity of modeling such systems is usually high. Intelligent techniques such as artificial neural networks (ANNs) and support vector machines (SVMs) are powerful tools for the performance prediction and modeling of these systems. These techniques are applicable to various systems and subsystems used in clean energy technologies. In addition to the technical aspects, other aspects of clean energy technologies such as their environmental and economic impacts and requirements can be modeled and analyzed by employing intelligent techniques. The present Special Issue aims to gather high quality original and review articles that consider the utilization of intelligent techniques for modeling and predicting the performance of various clean energy technologies and tackling their problems. The main topics of interest for the present issue are as follows:

• Renewable energy systems, modeling, and optimization;
• Using intelligent techniques to predict weather data that is relevant to the performance of clean energy systems;
• Prediction of the emissions of clean energy technologies throughout their lifecycle by means of intelligent methods;
• Modeling and forecasting the properties of the materials with the potential to enhance the performance of clean energy technologies;
• Trend prediction of clean energy systems with respect to their environmental impact, market effects, utilization, etc.

Dr. Mohammad Alhuyi Nazari
Dr. Arman Haghighi
Dr. Ali Shahhoseini
Guest Editors

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• intelligent methods
• artificial neural network
• support vector machines
• regression
• clean energy
• solar systems
• wind turbines
• weather data