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Full-Text Articles in Databases and Information Systems

Data Warehouse Techniques To Support Global On-Demand Weather Forecast Metrics, Meriellen C. Joga Mar 2000

Data Warehouse Techniques To Support Global On-Demand Weather Forecast Metrics, Meriellen C. Joga

Theses and Dissertations

Air Force pilots and other operators make crucial mission planning decisions based on weather forecasts; therefore, the ability to forecast the weather accurately is a critical issue to Air Force Weather (AFW) and its customers. The goal of this research is to provide Air Force Weather with a methodology to automate statistical data analysis for the purpose of providing on-demand metrics. A data warehousing methodology is developed and applied to the weather metrics problem in order to present an option that will facilitate on-demand metrics. On-line analytical processing (OLAP) and data mining solutions are also discussed.


The Ups Prototype: An Experimental End-User Service Across E-Print Archives, Herbert Van De Sompel, Thomas Krichel, Michael L. Nelson, Patrick Hochstenbach, Victor Lyapunov, Kurt Maly, Mohammad Zubair, Mohamed Kholief, Xiaoming Liu, Heath O'Connell Jan 2000

The Ups Prototype: An Experimental End-User Service Across E-Print Archives, Herbert Van De Sompel, Thomas Krichel, Michael L. Nelson, Patrick Hochstenbach, Victor Lyapunov, Kurt Maly, Mohammad Zubair, Mohamed Kholief, Xiaoming Liu, Heath O'Connell

Computer Science Faculty Publications

A meeting was held in Santa Fe, New Mexico, October 21-22, 1999, to generate discussion and consensus about interoperability of publicly available scholarly information archives. The invitees represented several well known e-print and report archive initiatives, as well as organizations with interests in digital libraries and the transformation of scholarly communication. The central goal of the meeting was to agree on recommendations that would make the creation of end-user services -- such as scientific search engines and linking systems -- for data originating from distributed and dissimilar archives easier. The Universal Preprint Service (UPS) Prototype was developed in preparation for …


Supervised Adaptive Resonance Theory And Rules, Ah-Hwee Tan Jan 2000

Supervised Adaptive Resonance Theory And Rules, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Supervised Adaptive Resonance Theory is a family of neural networks that performs incremental supervised learning of recognition categories (pattern classes) and multidimensional maps of both binary and analog patterns. This chapter highlights that the supervised ART architecture is compatible with IF-THEN rule-based symbolic representation. Specifi­cally, the knowledge learned by a supervised ART system can be readily translated into rules for interpretation. Similarly, a priori domain knowl­edge in the form of IF-THEN rules can be converted into a supervised ART architecture. Not only does initializing networks with prior knowl­edge improve predictive accuracy and learning efficiency, the inserted symbolic knowledge can also …