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Artificial Intelligence in an Ecological Application

Artificial Intelligence in an Ecological Application
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Author(s): M. L. Hines (University of Missouri-Kansas City, USA), J. Pang (University of Missouri-Kansas City, USA)and C. Butterfield (Chadron State College, USA)
Copyright: 2000
Pages: 4
Source title: Challenges of Information Technology Management in the 21st Century
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-878289-84-1.ch026
ISBN13: 9781878289841
EISBN13: 9781466665316

Abstract

The Range Ecology group of the Department of Agronomy at the University of Nebraska, Lincoln, has been investigating the natural re-vegetation of an area previously grazed by cattle. The primary focus has been how the plants will change and how long re-vegetation will take. For the purpose of that research, the area has been fenced for fifteen years since 1981, so cattle cannot get into the area. During the research, fifteen-year plant community data were recorded. A tool was needed to enable predictive analysis. This research evaluated two artificial intelligence approaches for the predication of ecological plant community succession: artificial neural networks and knowledge based systems, two of the most widely used and commercially successful applications of artificial intelligence. A base prototype for predicting plant community succession model was then built. Section two overviews the two AI approaches evaluated. Section three describes the ecological application that prompted this work and the rationale to determine which AI approach to use. Section four presents a high-level overview of the prototype developed and the results from training. Section five outlines the work yet to be done and summarizes the potential impact of this research.

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