A neural network mode inference engine for the advisory system for training and safety /
accomplish.
| Main Author: | |
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| Format: | Thesis eBook |
| Language: | English |
| Published: |
[Place of publication not identified] :
[publisher not identified] ;
1996.
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| Subjects: | |
| Online Access: | Link to OAKTrust copy |
| Summary: | accomplish. configuring the aircraft for different phases of the flight. correct mode inferences which were slightly more accurate Engineering Flight Simulator (EFS). The ANNSR returned In order to perform this task, the ASTRAS system is endowed infer the correct flight mode even when the aircraft was off information to the pilot, assisting him in properly membership functions. Although functional, the limitations neural network based SR (ANNSR). The goal of the ANNSR was nominal conditions, a task which the fuzzy logic SR failed to of this method have prompted the development of an artificial off nominal flight conditions. The ANNSR performed better Recognizer (SR) which is able to discern the flight mode from sector, the Advisory System for Training and Safety (ASTRAS) sensor readings. The current SR is based on fuzzy logic than the fuzzy logic based SR in flight tests on the than the fuzzy logic SR during nominal flight conditions. The most important result was that the AN-NSR was able to To improve the safety record of the private general aviation to provide more accurate mode inferences, particularly during was conceived. The ASTRAS software provides timely with an artificial intelligence engine or Situation |
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| Item Description: | "Major subject: Aerospace Engineering". Vita. |
| Physical Description: | xiii, 94 leaves : illustrations ; 28 cm. Also available online. Issued also on microfiche from Lange Micrographics. |
| Bibliography: | Includes bibliographical references: pages 73-74. |