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Initiative #75

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Study on the use of Artificial Neural Networks to Predict the Return Timing and Northern Diversion Rate for Migrating Fraser River Sockeye Salmon

Listed in the registry Ideation Original language : English

About the initiative

Description of the initiative

The Machine Learning feasibility study compliments the statistical approach by asking whether Artificial Intelligence (AI) methods can be developed to predict salmon behaviour as functions of ocean conditions. classical machine learning models, including linear regression, Ridge regression, and Random Forest

AI family

Automation and Decision Support

Bucket rationale

Uses data analysis to automate and optimize ecological prediction—decision support.

Lifecycle

  1. Ideation

    Stage status : In progress

    May 29, 2025

  2. Assessment

    Stage status : Upcoming

  3. Approved

    Stage status : Upcoming

  4. Development

    Stage status : Upcoming

  5. Pilot

    Stage status : Upcoming

  6. Production

    Stage status : Upcoming

  7. Archived

    Stage status : Upcoming

Schedule for this initiative

  • Completed
  • In progress
  • Planned
  • Not applicable
  • Today
2025 May Jun Jul Aug Sep Oct Nov Dec 2026 Jan Feb Mar Apr May Jun Jul Aug Sep

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Contacts

Requester
Quan, Eric
Sector contact
Thomson, Richard
Subject matter expert
Thomson, Richard

Data and tools

Sector
Ecosystems and Oceans Science
Region
Pacific
Submitted on
May 29, 2025