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dc.contributor.authorQu, Xia
dc.date.accessioned2014-03-04T16:22:05Z
dc.date.available2014-03-04T16:22:05Z
dc.date.issued2008-12
dc.identifier.otherqu_xia_200812_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/qu_xia_200812_ms
dc.identifier.urihttp://hdl.handle.net/10724/25286
dc.description.abstractNED-2 is a multi-agent, intelligent, goal-driven decision support system for the forest ecosystem management developed by the USDA Forest Service and Institute for Artificial Intelligence at the University of Georgia. It has integrated many different forest management tools and models including vegetation growth and yield models, wildlife models, management models for timber, ecology, water and visual quality goals, GIS reporting tool, HTML report generating tools, etc. This thesis describes recent work on the integration of even-aged red pine, aspen and uneven-aged loblolly pine prescription models into NED-2. These prescription models combine the expert knowledge with the existing growth and yield models to achieve the goal of automatically thinning for timber management.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectblackboard architecture
dc.subjectknowledge-based system
dc.subjectFVS
dc.subjectprescription model
dc.titleThe NED-2 forest ecosystem management DSS
dc.title.alternativethe integration of even-aged red pine, aspen and uneven-aged loblolly pine prescription models
dc.typeThesis
dc.description.degreeMS
dc.description.departmentArtificial Intelligence Center
dc.description.majorArtificial Intelligence
dc.description.advisorWalter D. Potter
dc.description.committeeWalter D. Potter
dc.description.committeeKhaled Rasheed
dc.description.committeeDonald Nute


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