Web Based Decision Support System for Management of Grevillea Robusta Tree Species in Kenya
Forestry research and development decision making critically depends upon availability of integrated information and knowledge organized and presented to forest stakeholders in timely and easily understood manner. Decision Support Systems (DSS) have emerged to meet this need. This project describes the design of a web based DSS for Grevillea robusta. The Internet has created great opportunities to develop new approaches to solve technology transfer problems. DSS have been used in forestry to identify insect and damage they cause to trees, advising on herbicides, making silviculture decisions, supporting land use in agroforestry, providing useful and scientific information, tree and shrub selection etc. however, very little has been done to compile a comprehensive knowledge for development and management of G. robusta tree in Kenya. In this project, the author has managed to build a web based DSS system for Grevillea robusta tree. The system has three components, the data manager, the model and the expert system components. The database manager is used to manage scientific data while the model is used to calculate and predict tree growth and yield. The expert module employs a rule-based method for representation of knowledge. The user interface prepares the input data and parameters, executes the program and integrates the DSS software into a seamless system.
School of Computing and Informatics