A simple neural network scheduler for real-time machine task scheduling

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The recent development of a new generation of automated radionuclide assay equipment in our facility requires embedded software at each machine for the scheduling of sample assay tasks. The execution time requirements of real-time embedded software limit the complexity of the schedular software. By representing the scheduling problem properly, a simple backpropagation neural network performs the scheduling function within the imposed requirements. Operational tests have demonstrated that the neural network schedular has met all development goals and is superior to the previous approaches. This paper describes the design and development of the neural network task scheduler. In addition, several aspects ... continued below

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Pages: (8 p)

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Gritzo, R.E. January 1, 1992.

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Description

The recent development of a new generation of automated radionuclide assay equipment in our facility requires embedded software at each machine for the scheduling of sample assay tasks. The execution time requirements of real-time embedded software limit the complexity of the schedular software. By representing the scheduling problem properly, a simple backpropagation neural network performs the scheduling function within the imposed requirements. Operational tests have demonstrated that the neural network schedular has met all development goals and is superior to the previous approaches. This paper describes the design and development of the neural network task scheduler. In addition, several aspects of the practical application of neural networks to real-world problems are discussed.

Physical Description

Pages: (8 p)

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OSTI; NTIS; GPO Dep.

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  • Ideas in science and electronics (ISE) symposium, Albuquerque, NM (United States), 14 May 1992

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  • Other: DE92013547
  • Report No.: LA-UR-92-1206
  • Report No.: CONF-9205141--3
  • Grant Number: W-7405-ENG-36
  • Office of Scientific & Technical Information Report Number: 5292113
  • Archival Resource Key: ark:/67531/metadc1065686

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Office of Scientific & Technical Information Technical Reports

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  • January 1, 1992

Added to The UNT Digital Library

  • Feb. 4, 2018, 10:51 a.m.

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  • May 21, 2018, 5:40 p.m.

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Gritzo, R.E. A simple neural network scheduler for real-time machine task scheduling, article, January 1, 1992; New Mexico. (digital.library.unt.edu/ark:/67531/metadc1065686/: accessed October 19, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.