rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Development and implementation of an artificially intelligent search algorithm for sensor fault detection using neural networks
  name:
    name part: Singh, Harkirat
    name part: 1978-
    role:
      role term: creator
  name:
    name part: Langari, Reza
    role:
      role term: thesis advisor.
  name:
    name part: Culp, Charles H.
    role:
      role term: thesis advisor.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: txu
    date issued: 2004
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  abstract: This work is aimed towards the development of an artificially intelligent search algorithm used in conjunction with an Auto Associative Neural Network (AANN) to help locate and reconstruct faulty sensor inputs in control systems. The AANN can be trained to detect when sensors go faulty but the problem of locating the faulty sensor still remains. The search algorithm aids the AANN to help locate the faulty sensors and reconstruct their actual values. The algorithm uses domain specific heuristics based on the inherent behavior of the AANN to achieve its task. Common sensor errors such as drift, shift and random errors and the algorithms response to them have been studied. The issue of noise has also been investigated. These areas cover the first part of this work. The second part focuses on the development of a web interface that implements and displays the working of the algorithm. The interface allows any client on the World Wide Web to connect to the engineering software called MATLAB. The client can then simulate a drift, shift or random error using the graphical user interface and observe the response of the algorithm.
  note: by Harkirat Singh.
  note: "Major Subject: Mechanical Engineering"
  note: Title from author supplied metadata (record created on Nov. 30, 2005.)
  note: Vita.
  note: Abstract.
  note: Electronic resource.
  note: System requirements: Adobe Acrobat Reader.
  note: M. S. Texas A&M University 2004
  note: Includes bibliographical references.
  note: Text (Thesis).
  subject:
    topic: Major mechanical engineering
  subject:
    topic: Sensor Faults
  subject:
    topic: Artificial Intelligence
  subject:
    topic: Neural Networks
  subject:
    topic: Search Algorithm
  identifier: http://hdl.handle.net/1969.1/116
  record info:
    record content source: TXA
    record creation date: 110308
    record change date: 20151202115709.0
    record identifier: in00002659325