LRS: A Knowledge Based Approach to Launch Resource Scheduling.

Abstract

This work describes a knowledge based prototype launch resource scheduling tool called LRS. The tool was requested by US Space Command for use by planners to evaluate future space launch resource requirements. A knowledge based approach to the lauch resource scheduling problem is used due to its knowledge intensive nature. The LRS prototype is implemented using a knowledge system tool called Insight 2+ on an IBM PC compatible microcomputer. LRS uses menus and explanation screens to make it simple to operate. The code is written in IF THEN ELSE production rule format making it easy to understand and easy to update as policy and needs change. LRS uses dBase II format files for storing the required information on launch vehicle and launch pad resources, and satellite launch requirements. LRS matches launch resources to launch requirements. A launch schedule is produced which shows how the resources meet the launch requirements. At completion of the matching process LRS provides a list of unsatisfied requirements and available resources. This list may be used by the planner to determine how well the planned launch resources meet the estimated launch requirements. The necessary enhancements and improvements to convert the LRS prototype into an operational system are identified. (Author) (Thesis).

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1986
Accession Number
ADA179426

Entities

People

  • Fred H. Koch

Organizations

  • Air Force Institute of Technology

Tags

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Satellites
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Engineering
  • Expert Systems
  • Inference Engines
  • Knowledge Based Systems
  • Launch Vehicles
  • Mainframe Computers
  • Prototypes
  • Scheduling (Production)
  • Test And Evaluation
  • Vehicles
  • Word Processors

Fields of Study

  • Computer science

Readers

  • Aerospace Engineering.
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computer Science.

Technology Areas

  • Space