Intelligent system

If improvements should be achieved by an automation of the inspection process this requires a control of the process parameters of the whole equipment by an integrated "intelligent" system and not by displays still being controlled by the human inspector. This integrated control-system ensures that the inspection conditions are at the highest reproduction level. 

BE-740S The development of a PC artificial intelligence system for the diagnosis and oroanosis of machine condition usina acoustic emission and acceleration Mr. A. Aurrecoechea gBKWS ... 

M. Realff, n A.naljsis of the Chemical Patch Production Problem and a Detailed Methodologyfor Schedulings technical report no. LISPE-88-054, Laboratory for Intelligent Systems in Process Engineering, MIT, Cambridge, Mass., 1989. 

James F DaviS/ Ph D / Professor of Chemical Engineering, Ohio State University (Intelligent Systems)... 

Duhois, D., H. Prade, and R. R. Yager (eds.) Readings in Fuzzy Sets for Intelligent Systems, Morgan Kaufmann (1993). 

Stephanopoulos, G., and H. Chonghun. Intelligent Systems in Process Engineering A Review, Proceedings ofPSE 94. Korea (1994). 

M Brown, R Hughey, A Krogh, IS Mian, K Sjolander, D Haussler. Using Dirichlet mixture priors to derive hidden Markov models for protein families. Intelligent Systems in Molecular Biology 1 47-55, 1993. 

K Karplus. Evaluating regularizers for estimating distributions of ammo acids. Intelligent Systems in Molecular Biology 3 188-196, 1995. 

TL Bailey, M Grihskov. The megaprior heuristic for discovering protein sequence patterns. Intelligent Systems in Molecular Biology 4 15-24, 1996. 

AL Delcher, S Kasif, HR Goldberg, WH Hsu. Protein secondary structure modelling with probabilistic networks. Intelligent Systems m Molecular Biology 1 109-117, 1993. 

Yan, J., Ryan, M. and Power, J. (1994) Using fuzzy logic - Towards intelligent systems, Prentice-Hall International (UK), Hemel Hempstead, UK. 

Saraiva, P.M., 1995. Inductive and analogical learning Data-driven improvement of Process operation. In Intelligent Systems in Process Engineering. Eds. G. Stepha-nopoulos and C. Han, Advances in Chemical Engineering, 22, 377. 

Utilization of intelligent systems in chiral chromatography starts with an original project called CHIRULE developed by Stauffer and Dessy [36], who combined similarity searching and an expert system application for CSP prediction. This issue has recently been reconsidered by Bryant and co-workers with the first development of an expert system for the choice of Pirkle-type CSPs [37]. 

George Stephanopoulos, Laboratory for Intelligent Systems in Process Engineering, Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (1,43, 187, 257)... 

Indeed, whenever you focus your attention on any of the so-called intelligent systems, and you take the time to leam the mechanisms they use to generate their marvelous and wondrous behavior, you come up with the anti-climactic realization that everything is quite ordinary and perfectly expectable with no surprises or mystical insights. Such reaction reminds us of how Sherlock Holmes reacted when a man questioned the brilliance of his deductive reasoning in solving one of his cases ... 

It is this integrative attitude that today characterizes most of the work in the area of intelligent systems for process engineering, as the editors of this volume have indicated in a recent review article. (4) It is this need for integrative approaches that has moved the applications of artificial intelligence into the mainstream of engineering activities. This is certainly the pivotal feature that characterizes the ten paradigms discussed in the subsequent chapters. 

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