ANS Based Submarine Simulation

Abstract

This report discusses the project background, including the requirements of such a simulation model, and the advantages of an ANS approach. The uniqueness of AWI's Optimal-Entropy Neural Network algorithm is discussed as well as its significance to the success of this project. AWI has developed an ANS to model submarine performance based on the setting of the input parameters to result in a particular performance for the submarine where the ANS specifies the Position and orientation of the submarine sometime in the future. AWI has also developed an algorithm to run the ANS in the inverse mode, namely the algorithm allows the user to specify the desired position and orientation of the submarine at some time in the future, where the ANS will then specify the controlling input parameters to reach that specified objective. The latter specifications have to be within the realm of possible requirements or else the ANS will specify a possible solution close to what was desired. The developed ANS is capable of operating in a PC environment. The results are obtained almost instantaneously on the PC. Artificial neural system, Neural network, Submarine simulation modeling.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1994
Accession Number
ADA286544

Entities

People

  • Hans Vanderveldt
  • Vince Whited
  • Xiaoshu Xu

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Automatic
  • Classification
  • Computer Programming
  • Computers
  • Contracts
  • Control Surfaces
  • Control Systems
  • Data Sets
  • Graphical User Interface
  • Measurement
  • Neural Networks
  • Programming Languages
  • Signal Processing
  • Simulations
  • User Interface

Readers

  • Computer Science.
  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks