By James Wei, Chonghun Han, George Stephanopoulos, John L. Anderson, Morton M. Denn, John H. Seinfeld
Volumes 21 and 22 of Advances in Chemical Engineering comprise ten prototypical paradigms which combine principles and methodologies from man made intelligence with these from operations learn, estimation andcontrol concept, and facts. every one paradigm has been built round an engineering challenge, e.g. product layout, procedure layout, procedure operations tracking, making plans, scheduling, or keep an eye on. besides the engineering challenge, each one paradigm advances a selected methodological subject matter from AI, reminiscent of: modeling languages; automation in layout; symbolic and quantitative reasoning; inductive and deductive reasoning; looking out areas of discrete strategies; non-monotonic reasoning; analogical learning;empirical studying via neural networks; reasoning in time; and good judgment in numerical computing. jointly the 10 paradigms of the 2 volumes point out how pcs can extend the scope, style, and volume of data that may be articulated and utilized in fixing a vast variety of engineering difficulties. Key gains * units the rules for the advance of computer-aided instruments for fixing a couple of exact engineering difficulties * Exposes the reader to a number of AI ideas in automated modeling, looking out, reasoning, and studying * The fabricated from ten-years event in integrating AI into strategy engineering * deals improved and practical formulations of real-world difficulties
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Additional resources for Intelligent Systems in Process Engineering, Part I: Paradigms from Product and Process Design
Mandelbrot. B. B.. ” W. H. Freeman, New York, NY, 1983. 7. Davis, I? J. and Hersh, R.. ” Harcourt Brace Jovanovich, San Diego, CA, 1986. 8. Stephanopoulos, G. , Artificial Intelligence in Chemical Engineering-Research and Development, Comp. C h m . En,?. 12(9/10), (1988). 9. Stephanopoulos, G . , Artificial Intelligence and Symbolic Computing in Process Engineering Design. In “Foundations of Computer-Aided Process Design” (J. J. Siirola, I. E. Grossmann, and G . ), p. 21, Elsevier, New York, 1989.
7. Davis, I? J. and Hersh, R.. ” Harcourt Brace Jovanovich, San Diego, CA, 1986. 8. Stephanopoulos, G. , Artificial Intelligence in Chemical Engineering-Research and Development, Comp. C h m . En,?. 12(9/10), (1988). 9. Stephanopoulos, G . , Artificial Intelligence and Symbolic Computing in Process Engineering Design. In “Foundations of Computer-Aided Process Design” (J. J. Siirola, I. E. Grossmann, and G . ), p. 21, Elsevier, New York, 1989. 10. Stephanopoulos. G . , Artificial Intelligence: What Will Its Contributions Be to Process Control?
Modeling Elements of LCR B. Semantic Relations among Modeling Elements in LCR C. Syntax of LCR Formal Construction of Representations for Chemicals and Reactions A. Extension of LCRs Modeling Objects B. The “Model Class Decomposition Digraph’ (MCDD) C. Generation and Representation of Reaction Pathways D. Creation of Contextual Reaction Models E. : A Modeling Language for Process Engineering A. Basic Modeling Elements B. Semantic Relationships C. Hierarchies of Modeling Subclasses D. Syntax Phenomena-Based Modeling of Processing Systems A.