Jove
Visualize
Contact Us

Related Experiment Videos

Noise Annoyance Modelling using Fuzzy Rule Based Systems.

D. Botteldooren1, A. Verkeyn, P. Lercher

  • 1Ghent University (INTEC), St-Pietersnieuwstraat 41, B-9000 Ghent, Belgium.

Noise & Health
|April 8, 2003
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A Review of Environmental Noise and Mental Health.

Noise & health·2003
Same journal

The End of NIOSH's Hearing Loss Prevention Program: Setback or Opportunity?

Noise & health·2026
Same journal

Evaluation of Conventional Floor-to-Floor Prediction Models for Train-Induced Noise and Vibration and Their Association with Residents' Depressive Symptoms.

Noise & health·2026
Same journal

Spectral Profile Analysis and Speech-in-Noise Performance in Habitual Earphone Users with Normal Hearing.

Noise & health·2026
Same journal

Annoyance and task performance during a single high-level aircraft noise and multiple lower-level aircraft noises.

Noise & health·2026
Same journal

The Effect of Different Types of Music on Pain and Anxiety during Wound Care Procedures in Patients with Venous Ulcers: A Randomized Controlled Trial.

Noise & health·2026
Same journal

Environmental Noise and Cardiovascular Risk: A Causal Inference Study.

Noise & health·2026
See all related articles
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

This study introduces a fuzzy rule-based model to predict noise annoyance using expert-defined rules and linguistic variables. The model adapts rule certainty for specific surveys, demonstrating clear benefits for understanding noise annoyance determinants.

Area of Science:

  • Environmental Psychology
  • Computational Social Science
  • Human-Computer Interaction

Background:

  • Noise annoyance is a significant public health concern.
  • Predicting noise annoyance accurately is crucial for policy support.
  • Existing models may not fully capture the complexity of annoyance determinants.

Purpose of the Study:

  • To present a novel fuzzy rule-based engine for predicting individual noise annoyance.
  • To adapt the model's rule certainty for specific social survey data.
  • To demonstrate the benefits of this expert-driven approach in annoyance prediction.

Main Methods:

  • Development of a fuzzy rule-based engine.
  • Utilization of linguistic variables and expert-defined rules.

Related Experiment Videos

  • Adaptation of rule sufficiency degree for model tuning.

    • Main Results:

    • The fuzzy rule-based model effectively predicts noise annoyance.
    • The approach demonstrates clear benefits for survey-specific tuning.
    • The model shows potential for improved noise annoyance prediction.

    Conclusions:

    • The fuzzy rule-based engine offers a promising approach to predicting noise annoyance.
    • Further development could incorporate a wider range of variables for enhanced accuracy.
    • Future applications include policy support and knowledge extraction on annoyance constructs.