## 2 Experimental Setup and Data Collection  
The rooftop system is installed at the Hashemite University (HU) in Zarqa, Jordan, at latitude of 32.1022\({}^{\circ}\) N, longitude of 36.1850\({}^{\circ}\) E and an altitude of 575 m. The system is grid-connected, consisting of 28 modules of a nominal power of 285 Wp (STP285-24/Vd) [54] wired in two strings with a nominal system power of 7.98 kWp, as pictured in Figure 1[55]. The tilt angle of the system is 26\({}^{\circ}\), which is equivalent to 0\({}^{\circ}\) azimuth angle. The two strings are connected to a 3-phase 8 kW invertor (PVI-8.0-TL-OUTD, ABB) [55]. The system is integrated to a data acquisition system to collect several inputs and outputs at different time intervals, which was set to one minute. The data was collected from 17 March 2014 to 24 September 2014. The system was cleaned by rainfall on 17 March and 8 May, whereas manual cleaning was performed on 12 July and 24 September. However, it was found that 9 data points out of 192 were outliers, with excessive efficiency values traced to sensor malfunctions. In addition, the four cleaning days were excluded from further analysis because cleaning was done during the day, which implies that the data collected during these days is not reliable (part of the day has dust accumulated on the PV modules, and the other part is clean). Thus, 179 data points were used for further analysis. The system outputs and climatic data are collected every minute, displayed in real-time, and stored and accessed by authorized persons. However, the data was manipulated on an hourly average basis, as shown later in the analysis section. In this work, we consider that the rain and manual cleaning result in the same cleanness for the PV system. This is due to the fact that the manual cleaning was done with water and special brushes, and the rainfall cleaning was done in heavy rain with the same special brushes. In both cases, the visual inspection after cleaning revealed that the cleanness was the same. This would justify the appropriateness of this assumption. In other words, although the details of cleaning are not mentioned in this manuscript, the level of cleanness was controlled by applying brushing to the PV panels right after heavy rain and with manual water cleaning. The performance of the 7.98 kWp PV system is evaluated based on IEC 61724 (1998) [56]. The system conversion efficiency, \(\eta\), is defined as the ratio of the net AC output energy, \(E_{out}\), to the input solar energy. It is important to mention here that all the energy losses due to cables, inverters, orientation, etc. are taken into consideration in the definition of the system conversion efficiency. The system conversion efficiency is mathematically defined as  
\[\eta=\ E_{out}/(H\times A), \tag{1}\]  
where \(A\) is the total area of the modules, which is 49.061 m\({}^{2}\), and \(H\) is the total daily global incident irradiance. For clarification purposes, Figure 2 shows the dust accumulation (represented in terms of exposure days) (Figure 2 (top)), the calculated average daily ambient temperature (Figure 2 (middle)), and the calculated system daily conversion efficiency based on the daily AC electric output and the total daily global incident irradiance (Figure 2 (bottom)), for the whole study period, with \(n=179\) data points. Looking at Figure 2, one can see the sudden rises in the system conversion efficiency, which are due to the cleaning effect of the PV modules; i.e., at these times, the PV system had been cleaned. For the prediction purposes of the system's daily conversion efficiency using the proposed models, the overall collected data are divided into two sets of data:  
* Training and validation sets of data: 80% of the overall data (i.e., 143 data points) is selected randomly for the purpose of building the prediction models.