## 1 Introduction  
With consistent economic growth and industrial development, energy usage and greenhouse gas emissions continue to increase in all sectors, and buildings account for the largest share in this regard. To save energy, the government of South Korea is promoting energy conservation standards for buildings, a housing performance labeling system, a building-specific energy efficiency rating system, and a green building certification system [1]. Of the total energy consumption in buildings, more than 45% is consumed by heating, ventilation, and air conditioning (HVAC) systems [2]. The function of the mixing chamber installed in the air handling unit (AHU) is to mix outdoor air (OA) and return air (RA). While the mixing of the two types of airs is generally assumed to be perfect, in reality, incomplete mixing occurs inside the mixing chamber [3]. This causes errors in the mixing temperature measurement. Most mixing chambers have only one mixing temperature sensor inside them, which makes it difficult to measure the exact mixing temperature [4]. Therefore, we conducted a preliminary experiment to check the mixing temperature errors that occur during the operation of the AHU. For this, 15 thermocouple sensors were equally spaced and installed inside the mixing chamber to check the mixing temperature errors obtained with the existing mixing temperature sensor found inside the mixing chamber. The thermocouple-measured mixing temperature shown in Figure 1 indicates the average temperature measured by the 15 thermocouples. The average error between the average thermocouple-measured mixing temperature and the temperature measured by the building automation system's (BAS) mixing temperature sensor was about 2.438 \({}^{\circ}\)C.  
As demonstrated by the results of the preliminary experiments, if the mixing temperature sensor is installed at a specific location inside the mixing chamber, the mixing temperature reading is based on the temperature at that location, resulting in a difference from the actual mixing temperature. In addition, it is not economically viable to install and operate multiple sensors to increase the accuracy of the mixing temperature measurement [5]. Thus, mixing temperature measurement errors are caused based on the installation location and number of mixing temperature measurement sensors inside the AHU. These errors can affect the automatic operation of the AHU system and the annual energy usage of the cooling and heating coils. Recently, various studies have been conducted to improve the energy efficiency and energy saving of buildings through efficient operation of HVAC systems, and it is an important topic. [PERSON] presented a method for predicting an AHU's supply air temperature using machine learning-based automation algorithms (AutoML). By optimizing various machine learning models through AutoML (Auto-Sklearn) and comparing them with existing artificial neural network (ANN) models, [PERSON] found a 0.03% to 1.16% higher accuracy [6]. [PERSON] used TRNSYS to analyze the impact of mixing temperature sensor error in AHU on cooling energy requirements during economizer control. The error of the existing mixing temperature sensor measured through experiments was about \(-\)0.3-0.5 \({}^{\circ}\)C and it was found that up to about 10,000 MJ of additional cooling energy was required depending on the mixing temperature setting. The mixing temperature correction improved the measurement performance of the existing mixing temperature sensor, and the comparison of the amount of outdoor airflow input confirmed that up to 400 CMH of additional outside air input was required, so further research is needed, including on the optimal installation location of the mixing temperature sensor and the development of a virtual mixing temperature sensor [7].