A Fuzzy-Logic Framework for Humidity-Setpoint Sensitivity: Impacts on Latent and Sensible HVAC Energy Loads
Bibliographic record
Abstract
This study investigates how fuzzy-logic humidity thresholds influence HVAC energy of a residencial house. A validated fuzzy controller is embedded in the Vertical City Weather Generator (VCWG v3.0.0) and subjected to a one-at-a-time sensitivity analysis on the four relative-humidity limits—Low-Low, Low, High and High-High—while all other inputs are held constant. Results show that sensible loads remain essentially unchanged regardless of threshold adjustments, whereas humidification and dehumidification respond strongly and in opposite directions to shifts at the dry and humid ends of the comfort band. Widening the allowable humidity range therefore offers a straightforward means to cut latent energy without affecting heating or cooling demand. The findings highlight which fuzzy thresholds matter most and provide practical guidance for tuning rule-based HVAC control in cold, dry climates.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".