In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The...
Solar energy is considered as one of the main sources for renewable energy in the near future. However, solar energy and other renewable energy sources have a drawback related to the difficulty in predicting their availability in the near future. Thi...
Shortwave solar radiation is an important component of the surface energy balance and provides the principal source of energy for terrestrial ecosystems. This paper presents a machine learning approach in the form of a random forest (RF) model for es...
Particle Swarm Optimization (PSO) is widely used in maximum power point tracking (MPPT) of photovoltaic (PV) energy systems. Nevertheless, this technique suffers from two main problems in the case of partial shading conditions (PSCs). The first probl...
This work describes the integration of several data mining and machine learning tools for researching Photovoltaic (PV) solar cells libraries into a unified workflow embedded within a GUI-supported Decision Support System (DSS), named PV Analyzer. Th...
Unmanned aerial vehicles (UAVs) require data-link system to link ground data terminals to the real-time controls of each UAV. Consequently, the ability to predict the health status of a UAV data-link system is vital for safe and efficient operations....
Solar energy is a major type of renewable energy, and its estimation is important for decision-makers. This study introduces a new prediction model for solar radiation based on support vector regression (SVR) and the improved particle swarm optimizat...
Journal of chemical information and modeling
31710212
Convolutional neural network (CNN) is employed to construct generative and prediction models for the design and analysis of non-fullerene acceptors (NFAs) in organic solar cells. It is demonstrated that the dilated causal CNN can be trained as a good...
Neural networks : the official journal of the International Neural Network Society
32339808
The machine vision based methods for micro-cracks detection of solar cells surface have become one of the main research directions with its efficiency and convenience. The existed methods are roughly classified into two categories: current viewing in...
The journal of physical chemistry letters
33417761
Nonradiative electron-hole recombination constitutes a major route for charge and energy losses in copper zinc tin sulfide (CZTS) solar cells. Using a combination of nonadiabatic (NA) molecular dynamics and deep neural networks (DNN), we demonstrated...