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Record W2085527333 · doi:10.1109/isie.2006.295601

Intelligent Fuzzy Control for Biogas in Hydrophobic Polymer System

2006· article· en· W2085527333 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Analytical Chemistry Studies
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFuzzy logicBiogasFuzzy control systemController (irrigation)Control engineeringComputer scienceMATLABWorkspaceBlock (permutation group theory)Adaptive neuro fuzzy inference systemControl theory (sociology)EngineeringControl (management)Artificial intelligenceRobotMathematicsWaste management

Abstract

fetched live from OpenAlex

In this paper, intelligent Fuzzy control system has been applied for biogas processes in a hydrophobic permeable polymer that is proposed to be used in landfills as a medium for biogas collection. Once having experimental information about biogas transport in the polymer within different variables, the information could be modeled by fuzzy system. When fuzzy controller is built with its fuzzy rules and operators, then the work is saved with its specifications in the Matlab workspace. The fuzzy controller is then available to be used in the fuzzy controller block in a Simulink diagram and then using it in a simulation for control. Fuzzy logic controls collection processes by adapting valve for required gas outflow with time at the collection ports

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.522

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 head0.005
GPT teacher head0.192
Teacher spread0.187 · 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