Using Neural Networks for Estimating Cruise Missile Reliability
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ACC believes its current methodology for predicting the reliability of its Air Launched Cruise Missile (ALCM) and Advanced Cruise Missile (ACM) stockpiles could be improved. They require a predictive model that delivers the best possible 24-month projection of cruise missile reliability using existing data sources, collection methods and software. It should be easily maintainable and developed to allow a layperson to enter updated data and receive an accurate reliability prediction. The focus of this thesis is to improve upon free flight reliability, although the techniques could also be appli...
ACC believes its current methodology for predicting the reliability of its Air Launched Cruise Missile (ALCM) and Advanced Cruise Missile (ACM) stockpiles could be improved. They require a predictive model that delivers the best possible 24-month projection of cruise missile reliability using existing data sources, collection methods and software. It should be easily maintainable and developed to allow a layperson to enter updated data and receive an accurate reliability prediction. The focus of this thesis is to improve upon free flight reliability, although the techniques could also be applied to the captive carry portion of the missile reliability equation. The following steps were taken to ensure maximum accuracy in model results. 1. Add more detail to flight test reliability calculation. 2. Convert the ground test data into a usable form (reduce). 3. Engage in an exercise in feature selection. 4. Develop a Matlab model prototype. 5. Validate the model via problems with known solutions. 6. Apply an appropriate data fusion technique to the different network outputs (logistic regression, feed-forward and radial basis function). 7. Put the model into the form of a usable tool for the end-user. The end product is the ALCM/ACM Reliability Estimation System (AARES), a VBA-based model that meets all user criteria. This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
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