Reasoning based on belief functions and cause-effect hierarchies are combined to create a methodology for enhanced evidential reasoning. A description of the methodology is given as well as examples of the utilization of a complete system. The method provides reasoning about belief among alternatives, is extensible, and can be easily scaled up to large problems. It is asserted that belief manipulation coupled with information about fault history, events, and symptoms is sufficient to secure good diagnostic results.>

A parallel tree search procedure and multilevel array architectures are presented for scene labeling problems. In the scene labeling problem, when the number of variables is not large, e.g. less than 100, its solutions and search space are not expected to greatly increase with problem size. The multilevel arrays only use a polynomial number of processors at each level and a bus or mesh connection for interlevel communication. This approach is very efficient compared to the binary-tree machine if the number of nodes in the search tree of labeling problem increases polynomially with the number of variables. Because of its regular structure, the multilevel array is particularly suitable for VLSI implementation.>

This paper presents an application of rule-based expert systems to thermal and structural analysis, part of mechanical engineering design, in electronic system design. The purpose of these expert systems is to serve as a consultant or design reviewer. These design expert systems are capable of performing both symbolic reasoning and numeric computation. The advantages of expert systems over conventional systems such as user friendliness, explanation and help facilities, and easy development and maintenance are also shown in this paper. Using system-subsystem tree structure several interrelated expert systems can be integrated into one system, and it is flexible for future expansion or modification. Object-oriented approach is also discussed, which with its unique representation of object could be a useful tool for engineering design.

The nearest-neighbor decision rule for syntactic patterns is applied to seismic pattern classification. Each pattern is represented by a string. The string-to-string distance is used as a similarity measure. Another method using finite-state grammars inferred from the training samples and error-correcting parsers is also implemented. Both methods show equal recognition accuracy; however, the nearest-neighbor rule is much faster in computation speed. The classification results of real earthquake/explosion data are presented.