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Related Experiment Videos

Test case based risk predictions using artificial neural network.

S T Ung1, V Williams, S Bonsall

  • 1Marine, Offshore and Transport Research Group, School of Engineering, Liverpool John Moores University, Liverpool, L3 3AF, UK.

Journal of Safety Research
|July 6, 2006
PubMed
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This study introduces a novel risk prediction model using fuzzy set theory and Artificial Neural Networks (ANNs) to overcome limitations in traditional fuzzy-rule-based risk assessment. The model enhances accuracy for complex scenarios with multiple parameters, improving navigational safety assessments.

Area of Science:

  • Engineering
  • Computer Science
  • Maritime Safety

Background:

  • Traditional fuzzy-rule-based risk assessment effectively combines parameters but struggles with multiple linguistic terms.
  • Existing methods face challenges in complex risk evaluations with numerous variables.

Purpose of the Study:

  • To propose an advanced risk prediction model integrating fuzzy set theory and Artificial Neural Networks (ANNs).
  • To develop a method for converting fuzzy risk attributes to crisp values for enhanced analysis.
  • To address limitations in traditional fuzzy risk assessment for multi-parameter evaluations.

Main Methods:

  • Developed a hybrid model combining fuzzy set theory and Artificial Neural Networks (ANNs).
  • Created an algorithm to convert fuzzy risk parameters and levels into crisp-valued attributes.

Related Experiment Videos

  • Applied and demonstrated the model using a case study on navigational safety in port areas.

    • Main Results:

    • The Artificial Neural Network (ANN) model demonstrated capability in generating reliable risk predictions.
    • Model performance is contingent on comprehensive training data covering diverse potential circumstances.
    • The developed algorithm successfully converted fuzzy risk data into usable crisp values.

    Conclusions:

    • Presents a flexible framework for risk modeling using fuzzy-rule-based techniques, suitable for complex scenarios.
    • The proposed model offers a novel approach for safety assessment practitioners.
    • Enables rational management of navigational safety, particularly within the port industry.