Application of Knowledge Based System for Woody Plant Species Identification
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Date
2009-04
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Addis Ababa University
Abstract
Finding the correct identity of trees is the beginning of any inventory and management
activities as well as any studies regarding the tree species. Identification of plant species in
Ethiopia is conducted only in the National Herbarium. At present, the centre is not supported
by information systems, which makes the identification process and dissemination of
information inefficient and difficult.
The need of KBS for technical information transfer and efficacy in dendrology can be
identified by recognizing the problems in using the current system for technical information
transfer and by proving that KBS can help to overcome the problems addressed, and are
feasible to be developed. This study attempts to design prototype KBS for woody plant species
identification. As compared to existing way of identification we come up with new
knowledge/rules with minimum features that registers comparable performance. By using this
system, users can get access to expert knowledge and will be able to identify woody plant
species like taxonomists do/judge. Using taxonomic KBS in different forestry research
centers, high-paid taxonomists will reduce the costs of scientific research and will allow many
researchers to conduct their research more independently (without going to the National
Herbarium for identification).
This research is conducted in a step-wise manner. After problem selection, knowledge
acquisition process is conducted. In this process, a key informant interview is held with
experts (two taxonomists and one researcher). In addition to the key informant interview,x
manuals and books used in woody plant species identification are also consulted. The
knowledge extracted from the experts’ and relevant documents that uses to solve a problem is
modeled in hierarchical or laddering technique.
Based on the final knowledge modeled in decision laddering, domain knowledge is
represented using production rules in prolog to construct the knowledge base. The system is
developed to load the knowledge base and starts to infer from the knowledge base based on
the users input/ facts. The prolog built in backward inferring mechanism is used for the
identification of the species. The user interface is designed in vb.net. Finally, the system is
tested and evaluated by the users. The result shows that, the system identifies the woody plant
species correctly and can be applicable in woody plant species identification.
Key words: knowledge based system, prolog, tree species identification, knowledge
acquisition, knowledge modeling, and KBS evaluation.
Description
Keywords
knowledge based system, prolog, tree species identification, tree species identification, knowledge acquisition, knowledge modeling, and KBS evaluation