Application of an Artificial Neural Network to Predict Tidal Currents in an Inlet

Abstract

This Coastal and Hydraulics Engineering Technical Note (ERDC/CHL CHETN-IV-58) describes application of an Artificial Neural Network (ANN) that can be trained to predict currents at an inlet located within a larger regional system, based on water level measurements at a different and possibly distant location. Once developed, ANNs reduce the need for field gauging, and information may be hindcast for sites where data do not exist or which have gaps in the historical record.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2003
Accession Number
ADA592255

Entities

People

  • Catherine Murray
  • Wenrui Huang

Organizations

  • Engineer Research and Development Center

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Coastal Engineering
  • Coastal Regions
  • Data Sets
  • Engineering
  • Engineers
  • Hydraulics
  • Measurement
  • Monitoring
  • Neural Networks
  • Programming Languages
  • Tidal Currents
  • Time Intervals
  • Topography
  • Transfer Functions
  • Underwater Acoustics
  • Verification

Fields of Study

  • Environmental science

Readers

  • Coastal and Marine Engineering/Sediment Transport/Hydraulic Engineering
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Neural Networks