## 4 Discussion
### Psychometric Chart: Visualization of Thermal Comfort Across Floors
Atmospheric pressure annotations were included for each floor, aligning with the pressure profile in Figure 5, which compares:  
* Standard sea level pressure (101,325 Pa);
* Average sea level pressure in the Philippines (101,000 Pa);
* APC's ground-level pressure (100,928 Pa). \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Room Type**} & **Clothing** & **Radiant Temp Adjustment, Tr [\({}^{\circ}\)C]** & **Air Velocity** & **Comfort Zone Adjustment** \\  & **[\({}^{\circ}\)C]** & **[\({}^{\circ}\)C]** & **[m/s]** & **Comfort Zone Adjustment** \\ \hline Classroom & 0.5–0.7 & \(Tr=Ta\) & 0.1–0.2 &
\begin{tabular}{c} Minimal adjustment; typical \\ comfort range of 20–25\({}^{\circ}\)C with \\ balanced humidity levels. \\ slightly higher radiant \\ temperature due to \\ heat-generating equipment. \\ Increased air movement; narrower \\ comfort range (19–23 \({}^{\circ}\)C). \\ Typical sedentary office setting \\ with minimal radiant heat. \\ Variable conditions based on \\ activities (sedentary to active). \\ Sedentary, low air movement; \\ comfort range adjusted to \\ 18–26 \({}^{\circ}\)C. \\ Typical comfort range adjusted for \\ sleeping conditions (22–26 \({}^{\circ}\)C). \\ Accounts for heat from stage \\ lighting and activity on stage. \\ \hline \hline \end{tabular}
\end{table} 
Table 18: Assumed environmental and clothing parameters influencing thermal comfort by room type. Figure 5 enables a thorough understanding of the thermal conditions across the building, thus informing climate control strategies for ensuring thermal comfort while maintaining energy efficiency. For example, the pressure profile plot illustrates how atmospheric pressure decreases with elevation, which impacts air properties and, consequently, ACU settings. Comparative Performance of RST-FIS-Based Fuzzy Logic Control vs. Other Machine Learning Techniques Applied in Cooling System Control  
The RST-based approach to defining a FIS for the control of cooling system setpoints for different types of rooms according to their usage distinguishes itself from those proposed in previous studies, as highlighted in Tables 1-4. This method significantly optimizes the rule  
Figure 5: Pressure profile across floors of APC. \begin{table}
\begin{tabular}{c c} \hline
**Floor** & **Rooms Included** \\ \hline
1 & Shared Office, Solo Office, Multi-purpose Hall \\
2 & Multi-purpose Hall, Classroom, Computer Room, Laboratory \\
3 & Classroom, Computer Room \\
4 & Classroom, Shared Office, Solo Office, Faculty Area \\
5 & Classroom, Computer Room, Shared Office, Solo Office, Laboratory \\
6 & Classroom, Computer Room, Shared Office \\
7 & Library, Solo Office \\
8 & Classroom, Computer Room, Laboratory, Shared Office, Solo Office \\
9 & Dormitory \\
10–11 & Classroom, Laboratory, Shared Office, Solo Office \\
12 & Auditorium \\ \hline \end{tabular}
\end{table} 
Table 19: Room types in the APC building. complexity of the FIS, thus enhancing its computational efficiency. Unlike traditional fuzzy systems, which often rely on exhaustive rule sets and require high processing times, the proposed FIS achieved a significant reduction in the number of rules for both instructional rooms (from 3357 to nine rules) and office spaces (from 550 to four rules). This optimization was achieved while maintaining high accuracy levels of 98.94% for historical data and 88.57% for all possible input values. Furthermore, the system's execution speed was dramatically improved, with a 96.40% improvement for instructional rooms and 86.48% for office spaces, thus enabling real-time decision-making capabilities (e.g., a decision can be made in 1.06 s for instructional rooms). These fuzzy performance metrics have not been presented nor discussed in detail in other studies. Due to these advancements, the proposed approach surpasses traditional fuzzy systems such as those proposed in [23; 54], which used unoptimized rule sets, resulting in slower processing times and less adaptable systems.