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Record W2123559998 · doi:10.1109/fuzzy.1998.687534

A fuzzy control system based on the human sensation of thermal comfort

2002· article· en· W2123559998 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsHVACThermal comfortAir conditioningThermal sensationFuzzy control systemComputer scienceFuzzy logicControl (management)Control systemControl engineeringAutomotive engineeringArchitectural engineeringSimulationEngineeringArtificial intelligenceMechanical engineeringMeteorologyElectrical engineering

Abstract

fetched live from OpenAlex

Unlike the majority of the existing residential heating, ventilating and air conditioning (HVAC) control systems which are considered as temperature control problems, this paper presents a new HVAC control technique that is based on the human sensation of thermal comfort. The proposed HVAC control strategy goal is not to maintain a constant indoor air temperature but a constant indoor thermal comfort. This is realized by the implementation of a fuzzy reasoning that takes into account the vagueness and the subjectivity of the human sensation of thermal comfort in the formulation of the control action that should be applied to the HVAC system in order to bring the indoor climate into comfort conditions. Simulation results show that the proposed control strategy makes it possible to maximize both thermal comfort of the occupants and the energy economy of HVAC systems.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score0.161

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.168
Teacher spread0.157 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations92
Published2002
Admission routes1
Has abstractyes

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