Applications artificial intelligence systems

In the lab, future expansion plans include the use of optical scanners for reading sample labels, operation of robots to relieve some of the manual operations and an artificial intelligence system to track quality control. In other areas, there will be an increase in the number of real time monitors, not necessarily because real time data is needed, but the cost can be small compared to sending out a field team. There will be some applications of direct monitoring by satellites such as LANDSAT D. Both of these will be incorporated into water quality models which will allow more intelligent choices of where to send a field team to collect samples for detailed analysis. 

KUBiAK, A., KUTZBACH, H. D., The application of an artificial intelligence system in the automatic recognition of wheat by the nonlinear approximation technique, 12th International Congress of Chemical and Process Engineering CHISA, Praha, Czech Republic, 25-30th August, 1996. P9.55 [490]. 

There are many other examples of applications of ANNs in pharmaceutical technology, dted in Sun et al. [ 16]. It has been shown that many artificial intelligence systems, especially neural networks, can be applied to the fundamental investigations of the effects of formulation and process variables on the delivery system. 

Burns, R.S. (1997) The Application of Artificial Intelligence Techniques to Modelling and Control of Surface Ships. In Proc. 11th Ship Control Systems Symposium, Southampton UK, April, 1, 77-83. 

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. 

R. Forsyth and R. Rada, Machine Learning Applications in Expert Systems and Information Retrieval. Ellis Horwood Series in Artificial Intelligence. Ellis Horwood, Wiley, Chichester, 1986. 

Myers, D. R., Hurley, C. E. and Davis, J. F. A diagnostic expert system for a sequential, PLC controlled operation, in Artificial Intelligence Applications in Process Engineering. (M. Mavrovoumolis, (ed.). Academic Press, New York, 1990. 

Expert systems appear in some ways to be the "classic" application of Artificial Intelligence. An expert system is a kind of personal advisor that engages the user in a conversation with the aim of providing help on a specialist topic. In sophisticated systems, the interaction between the expert system (ES) software and the user may be so natural that the user almost forgets that it is a computer rather than a human that is holding up the other end of the conversation. As developers of an ES usually do their best to create software that can participate in "intelligent" conversations, in order to enhance the user s confidence in the system, expert systems can seem the most human and friendly side of AI. 

Lanzi, P.L., Stolzmann, W., and Wilson, S.W., (Eds.) Learning classifier systems From foundations to applications, Lecture Notes in Artificial Intelligence 1813, Springer, Berlin, 2000. 

Expert systems represent a branch of artificial intelligence that has received enormous publicity in the last two to three years. Many companies have been formed to produce computer software for what is predicted to be a substantial market. This paper describes what is meant by the term expert system and the kinds of problems that currently appear amenable to solution by such systems. The physical sciences and engineering disciplines are areas for application that are receiving considerable attention. The reasons for this and several examples of recent applications are discussed. The synergism of scientists and engineers with machines supporting expert systems has important implications for the conduct of chemical research in the future some of these implications are described. 

Until recently, most expert system building took place in the research departments of universities and a few major corporations. The primary emphasis was investigation of artificial intelligence principles, and the application was of secondary importance. The expert systems tools used reflect this interest. They are typically stand-alone AI computer systems, using special hardware and software environments (usually Lispr-based) not commonly fo md in scientific and engineering organizations. 

Expert systems, and artificial intelligence in general, are new fields whose breadth of application, and indeed, whose exact definitions, are not yet completely settled. It is sometimes claimed that no two experts on artificial intelligence agree exactly on what its definition is. Definitions of expert systems at least agree on the necessity for expertise, but even here there are differences in emphasis and in priority. 

Most of the applications of artificial intelligence in chemistry so far have not involved numerical computation as a primary goal. Yet there are aspects of the AI approach to problem-solving which have relevance to computation. In scientific computation, one could view the knowledge base as the set of equations, input variable values, and unit conversions relevant to the problem, and the inference engine the numerical method used to solve the equations. This paper describes such a software system,... 

Holland JH 1992 Adaptation in natural and artificial systems an introductory analysis with applications to biology, control, and artificial intelligence. The MIT Press, Cambridge, Massachusetts. 

Technology is one of many trends constantly affecting computer validation. One area requiring special attention is the introduction of expert systems into the FDA-regulated environment. The simplest form of artificial intelligence generally used in applications (such as mortgages, credit card authorization, fraud detection, e-commerce, personalization) is the rule-based system, also known as the expert system (ES). 

C. Rojas-Guzman and M.A. Kramer. Comparison of belief networks and rule-based expert systems for fault diagnosis of chemical processes. Engineering Application of Artificial Intelligence, 6 191, 1993. 

The types of computer programs which have been applied in corrosion engineering and science fall into categories such as (i) conventional software systems (ii) artificial intelligence and expert systems applications (iii) object-oriented software systems ... 

A very important role in the proliferation and practical use of mathematical chemistry has been played by computers, especially in the last two decades, when the use of computers was extended from numerical computations and data handling to decision-making and logical problem-solving processes. The DENDRAL project, started at Stanford in the 1960s, may serve as an illustrative example [3], It was fairly successful, and strongly influenced the collaboration between chemists, computer scientists, and mathematicians. Many applications of artificial intelligence in chemistry, and especially the construction of expert systems, are natural consequences of this collaboration [4],... 

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