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Record W2087401022 · doi:10.1109/wcica.2010.5554353

A fuzzy based approach to effective relative humidity tracking in industrial systems

2010· article· en· W2087401022 on OpenAlexaff
Wei Zhang, Simon X. Yang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicFuzzy Logic and Control Systems
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsRelative humidityControl theory (sociology)Controller (irrigation)Relative velocityFuzzy control systemProcess (computing)Approximation errorPID controllerControl systemComputer scienceFuzzy logicTemperature controlControl engineeringControl (management)EngineeringArtificial intelligenceAlgorithmMeteorologyElectrical engineering

Abstract

fetched live from OpenAlex

This paper presents a relative humidity control scheme to reduce variable fluctuations and improve process control precision, thus increasing production quality and energy saving in industrial applications. The influence of absolute temperature on the closed-loop process control of relative humidity is discussed. Based on the relative humidity measurement principle, this effect of modifying the input measurement signal on the relative humidity control system is analyzed, and a fuzzy control model in conjunction with the existing PID control algorithm is developed to eliminate the influence of room temperature on relative humidity control. Simulation results using the proposed relative humidity controller confirm the improvement in controller performance.

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.

How this classification was reachedexpand

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.245
Teacher spread0.212 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2010
Admission routes1
Has abstractyes

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