Conference Session

Biology and Engineering

Collection

2007 Annual Conference & Exposition

Authors

George Meyer, University of Nebraska-Lincoln; David Jones, University of Nebraska-Lincoln

Tagged Divisions

Biological & Agricultural

relationships is similar to classical methods.2. Fuzzy logic as a modeling tool is flexible. Fuzzy reasoning can be simple or complex to predict a unique numerical value for the consequence or predict a classification category of a fuzzy consequence.3. Fuzzy logic inference can be developed from the experience of a human expert. If the relationships between input and output data are well understood, rules can be readily developed to reflect this a priori knowledge. FL can mimic the human thought process to process and predict imprecise results.4. While fuzzy logic is tolerant of imprecise data, its precepts allow convergence to classical sets. Fuzzy logic can model nonlinear functions of arbitrary complexity. Fuzzy systems can

Conference Session

Innovations in biological and agricultural engineering education

Collection

2007 Annual Conference & Exposition

Authors

Jinglu Tan, University of Missouri

Tagged Divisions

Biological & Agricultural

interpreted in termsof process control and quality assurance. This helps remove the mystifications over anoriginally simple concept and makes the criteria easily understandable to engineers.Application of the representation helped faculty understand the criteria and facilitated theimplementation process.IntroductionThe Engineering Criteria 2000 (EC 2000) represents a major paradigm shift in engineeringprogram assessment and accreditation. The major changes are reflected in Criteria 2 and 3.Criterion 2 requires that an accredited engineering program establish a set of programeducational objectives consistent with the institutional missions and have a process in place toevaluate the objectives and the attainment of them. Criterion 3 calls for an