###### Abstract
In addition, dirt due to animal droppings are another cause of fouling and the need for programmed maintenance. The studies looking at this topic have presented multiple conclusions, each related to the conditions occurring at the place and time that each study was carried out [16]. They have studied the importance of the soiling molecule size as well as the optimal inclination angle of the photovoltaic panels. However, the most important and fundamental issue of the work is the relationship between the short-circuit current and soiling accumulation [23; 24]--a very important indicator to consider if the losses caused by fouling are to be predicted [23]. By comparing two photovoltaic panels, with and without maintenance, it can be seen how the value of the short circuit current is greater when maintenance is carried out on the panel. The more radiation reaches the panels, the greater the difference between the two currents [23]. It has been shown that soiling has a very representative effect on the short circuit current, decreasing its value considerably. In the IV curves, this effect can be seen, comparing a curve of a panel with maintenance and another without maintenance. The current is the most affected because it has a linear relationship with the radiation, while the voltage hardly notices any difference. When receiving less radiation, this value will decrease. Therefore, the soiling significantly affects the degradation of the panels, affecting the cost of the plant and avoiding the expected profits. Photovoltaic plants are exposed to episodes of soiling, contamination, or meteorological phenomena that reduce performance (past African) (simulation). Knowing how the accumulation of soiling affects the installation is fundamental when establishing correct maintenance of it [25; 26]. For a correct cleaning, besides the moment in which it is done, it is fundamental how to carry out this task. If manual cleaning is chosen, it is necessary to know that such cleaning can damage the panels, besides allowing the permanence of small particles. The use of detergents presents multiple disadvantages for the environment and the panel itself, in view of the danger of corrosion. All of this leads to a more automatic process to avoid situations of this type [17]. Therefore, it is necessary to have information on the state of soiling of a plant, to determine the ideal time to clean the photovoltaic panels, thus saving natural or economic resources. Therefore, if a maintenance plan for the panels is to be effective, it is essential to be able to know how soiling affects the installation. This maintenance must be optimal, and for this, it is necessary to know the right time to perform it [27]. Given the importance of soiling on performance, this study has estimated the losses due to dust soiling in a photovoltaic plant, using meteorological variables as well as those specific to the installation, such as the short-circuit current (Isc), the module temperature (Tpanel), global irradiation (Iglo), relative humidity (RH), ambient temperature (Tamb), atmospheric pressure (P), and solar altitude (\(\alpha\)). These were then combined with artificial neural networks. In this work, it has been modeled the soiling losses incurred by an experimental pilot plant installed at the Solar Energy Research Center (CIESOL). It has been mainly compared measurements from two panels, one receiving maintenance and the other not. Subsequently, artificial intelligence techniques, such as artificial neural networks, were employed to estimate soiling losses from parameters commonly measured in any photovoltaic plant.