Article ID: | iaor19952109 |
Country: | United States |
Volume: | 12 |
Start Page Number: | 111 |
End Page Number: | 123 |
Publication Date: | Jul 1993 |
Journal: | Aquacultural Engineering |
Authors: | Bourke G., Stagnitti F., Mitchell B. |
Keywords: | artificial intelligence: decision support, decision theory: multiple criteria, analytic hierarchy process |
A decision support system was developed to facilitate the collection, manipulation and analyis of physico-chemical and biological data generated in aquaculture research. The Aquaculture Research and Monitoring System (ARMS) consists of integrated hardware and software packages that facilitate the operational decision making process in aqua-culture research via a user-friendly, visual interactive- modelling interface. ARMS provides a management system for the capture and manipulation of real, online environmental data sampled by a data logger and a modelling system allowing the user to input their own judgments in the analytical decision-making process. These judgments may be qualitative as well as quantitative. The user is able to assign importance values to the various environmental parameters and management practices that constitute variables in experiments and ARMS determines the probability of specific experimental outcomes. Thus, ARMS may be used to examine the validity of the assumptions used in past experiments and, more importantly, to simulate new experiments before actual implementation. ARMS also has a demonstration capacity that may be used to train other managers or students. The software is implemented on an IBM AT using routines written in Turbo Pascal and macros written for Minitab and Microsoft Excel. The design of ARMS stresses modular independence and thus the decision process and data collection and management are not necessarily coupled to specific experimental data and may be modified to suit the requirements of other uses such as day-to-day management of commercial aquaculture operations.