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Scheduling astronomy observations for the Stratospheric Observatory for Infrared Astronomy (SOFIA) requires assessing tradeoffs between the percentage of scheduled observations, the Line Of Sight Water Vapor (LOS-WV) achieved on those observations, and fuel consumption. This trade space is complex, depending on time of year and specific mixes of(More)
We describe the problem of scheduling astronomy observations for the Stratospheric Observatory for Infrared Astronomy, an airborne telescope. The problem requires maximizing the number of requested observations scheduled subject to a mixture of discrete and continuous constraints relating the feasibility of an astronomical observation to the position and(More)
We describe an innovative solution to the problem of scheduling astronomy observations for the Stratospheric Observatory for Infrared Astronomy, an airborne observatory. The problem contains complex constraints relating the feasibility of an astronomical observation to the position and time at which the observation begins, telescope elevation limits and(More)
Managing the International Space Station (ISS) solar arrays requires flight controllers to constantly balance multiple complex constraints against power needs. The complexity not only impacts planning activities, but has an even more acute effect on real-time operations, in particular when handling unexpected events or changes in operations plans. The Solar(More)
This paper describes the initial stage of an effort the goal of which is to demonstrate the effectiveness of automated data mining, learning and planning for the daily management of Earth Science missions. Currently, data mining and machine learning technologies are being used by scientists at research labs for validating Earth science models. However, few(More)
This paper describes a method and system for integrating machine learning with planning and data visualization for the management of mobile sensors for Earth science investigations. Data mining identifies discrepancies between previous observations and predictions made by Earth science models. Locations of these discrepancies become interesting targets for(More)
This is a progress report on an effort in which our goal is to demonstrate the effectiveness of automated data mining and planning for the daily management of Earth Science missions. Currently, data mining and machine learning technologies are being used by scientists at research labs for validating Earth science models. However, few if any of these(More)
In previous work we describe the problem of scheduling flights for SOFIA, an airborne observatory. Scheduling in this domain requires solving many Initial Value Problems (IVPs) and Boundary Value Problems (BVPs) to evaluate constraints on the observatory’s ground track and telescope elevation limits. These are costly operations, and become more so when(More)
This paper is a progress report of an effort whose goal is to demonstrate the effectiveness of automated data mining and planning for the daily management of Earth Science missions. Currently, data mining and machine learning technologies are being used by scientists at research labs for validating Earth science models. However, few if any of these advanced(More)