## 3 Methodology  
The methodology implemented in this study was designed to meet the purpose of the study. The methodology consisted of four phases in 12 sequential steps. The first phase included the literature review and experts' interviews to achieve the first objective, which was identifying the factors influencing the consumption of energy in school buildings in Eastern Province in Saudi Arabia. The second objective was achieved by undertaking the remaining steps in phase one, which were data collection and analysis, while building, training, testing, and validation of the developed model were achieved by taking the steps in phases 2-4. As depicted in Figure 1, to meet the objectives mentioned earlier--which were identifying the factors influencing the consumption of energy in school buildings, identifying the correlation between the identified factors, and developing a prediction model for the consumption of energy in school buildings in Eastern Province in Saudi Arabia--the following methodology sequence was followed, which consisted mainly of four phases. Phase One: Identifying Factors and Data Collection  
1. In the first step of this phase, a comprehensive literature review was conducted regarding previous work done in (1) identifying the factors influencing energy consumption in school buildings and (2) in developing a prediction model for the consumption of energy of this class of buildings. 2. In the second step of this phase, face-to-face meetings with three experts were conducted. The three selected experts were one from the Saudi Ministry of Education in Eastern Province, one from a Saudi electrical company, and one from the academia from Imam Abdulrahman Bin Faisal University (IAU) in Dammam. It should be noted that Eastern Province is the largest of Saudi Arabia's thirteen provinces and the third most populous one, with a population of 4,900,325 as of 2017. The purpose of conducting face-to-face meetings with experts was to agree on the most influential factors (variables) regarding the energy consumption of school facilities s in Saudi Arabia. 3. The third step of this phase involved the collection of the data required to build the model. Therefore, communication was established with the Ministry of Education in Eastern Province, who is the service provider for more than 1600 public schools. 4. The fourth step of this phase involved analyzing the data obtained from the Ministry of Education in Eastern Province for the purpose of data filtering before its use for developing the prediction model. Phase Two: Building the Initial NN Model  
1. In the first step, since the problem at hand was an approximation problem, the initial NN contained a scaling layer, multi perceptron layers, and an unscaling layer. The purpose of the scaling layer is to scale the input variables such that all the inputs have the same proper range. The scaling function acts as a layer that links all inputs that hold some basic statistical analysis, such as means, standard deviations, and minimum and maximum values. The perceptron layers are the most important layers that allow for the NN model to learn. Two activation functions were considered in building the initial NN model and before selecting the optimal model architecture; they are the hyperbolic tangent and linear activation function. In building the initial model, the scaling method was set to the mean standard deviation method since the input variables of the approximation problem had a normal distribution, while the perceptron layer(s) was set to hyperbolic tangent. 2. In the second step of this phase, the training strategy was set. This included setting the loss index, error measuring method, and the algorithm for selecting the optimal model. The purpose of the training is to obtain the minimum loss possible. The mean squared error (MSE) method was utilized to measure the loss index and quasi-Newton method was applied as the optimization algorithm, which is a good method for quickly training a medium-sized volume of data.