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An integrated farm machinery selection and management system for personal computers
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An integrated expert system for farm machinery management, titled Farm-machinery Analysis, Research and Management (FARM), was developed I at the Agricultural Engineering Department of Texas A&M University for use on personal computers. QuickBASIC 4.0 and Turbo Prolog 2.0 were used for system development. A stand alone final product was generated. The objective of the proposed farm machinery management model is to determine the most cost effective machinery set using logical relations and predicted machinery information against a calendar of events. Unlike other models, timeliness is seen as a requirement instead of a cost. A novel concept is the use of predicted in-soil tractor performance to determine the effective machinery capabilities for performing operations. Input information is presented in the form of either a database or | a knowledge base. User defined good working day probabilities and | machinery availability are used to reflect farmer risk attitude. Only I machinery combinations which meet the time and physical compatibility criteria are considered for cost evaluation. This dissertation delineates the theory behind the models, the underlying assumptions, and the procedures for developing, verifying, testing and validating the expert system. FARM consists of two database management systems, a tractor analysis and an in-soil performance prediction model, a farm machinery selection, scheduling and cost analysis model, and the support functions and programs for proper system operation. The integrated system was supplemented by an extensive set of databases for immediate program use. The models use input information and traction prediction equations. The inputs to the tractor analysis, the in-soil performance prediction and the farm machinery selection, scheduling and cost analysis models include tractor, implement, self-propelled machinery, tire, soil, farm, crop schedule, weather and economic information. The outputs consist of formatted reports, presented in tabular format. The inference engine of the farm machinery management model was designed to combine independent information in order to determine which machinery sets could perform the designated operations in the time available. The only predefined relations were the valid implements for an operation and the valid tractor types for a crop. The associated costs for owning and operating the aforementioned machinery sets were also calculated. A natural language interface experimental expert system was also developed in order to demonstrate how the FARM expert system can become more intelligent and user friendly. HELP was limited to providing help on system operation.
DescriptionTypescript (photocopy) -- Texas A&M University
SubjectMajor agricultural engineering
Farm managementData processing--Data processing
Expert systems (Computer science)
Kotzabassis, Constantinos (1991). An integrated farm machinery selection and management system for personal computers. Doctoral dissertation, Texas A&M University. Texas A&M University; Texas A&M University; Texas A&M University. Available electronically from
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