Memory-Based Computational Intelligence for Materials Processing and Design.
Abstract
The work reported in this document is concerned with the efficient use of computers in materials research and in applications of the results of that research. Emphasis is on the development of computational methodologies which can facilitate the innovative design of materials and of materials processing, for high performance materials and for composite materials structures. Basic advances have been made in three areas of adaptive computing: in establishing the practice of functional-link neural-net computing for learning models of material behavior, in developing a parallel processing evolutionary search paradigm for optimization and in exploring various of establishing and using associative memories. This report also describes how these ovations in conceptual and theoretical matters can be used to effect in dealing with materials processing and design tasks. Applications include in-situ - real-time interpretation of ellipsometry data, optimal formulation of material composition, control of nonlinear dynamic systems, memory-based design and the implementation of visual displays for multi-dimensional data.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 01, 1996
- Accession Number
- ADA310373
Entities
People
- Y. H. Pao
Organizations
- Case Western Reserve University