Artificial intelligence systems development

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 ... 

Expert artificial intelligence system/205 are particularly pertinent to the development of robust separations strategies for the RPC isolation of larger synthetic peptides. 

Analysts The above is a formidable barrier. Analysts must use limited and uncertain measurements to operate and control the plant and understand the internal process. Multiple interpretations can result from analyzing limited, sparse, suboptimal data. Both intuitive and complex algorithmic analysis methods add bias. Expert and artificial intelligence systems may ultimately be developed to recognize and handle all of these limitations during the model development. However, the current state-of-the-art requires the intervention of skilled analysts to draw accurate conclusions about plant operation. 

Several instruments have emerged in the marketplace and have been popularly described as electronic noses . In reality, these are volatile chemical sensor arrays. To give them more likeness to the human nose (or, more accurately, olfactory system), they are coupled to artificial intelligence systems that require development. The instruments currently available detect most vapours, odorous and non-odorous, including water vapour (to which they are all highly sensitive). Sensitivity to other volatiles, however, is highly variable, dependent... 

The first symposium, presented at the fall meeting of the American Chemical Society in 1985, was open to any type of artificial intelligence application. The second symposium was restricted to expert systems. This is only a minor restriction because most practical artificial intelligence applications to date have used expert systems in one form or another. Below is a brief overview of expert systems. More information on expert systems for chemistry can be found in reference 2. General expert system information can be found in references 3 and 4. Because artificial intelligence has developed its own vocabulary, a short glossary is also included. 

This paper is a progress report of the initial phase of an effort which is expected to take several years for completion. Given the present rapid rate of evolution of new concepts in the field of expert systems and artificial intelligence, the development of distributed systems and networks, and continued introduction of new machine features, the design outlined in this paper could be modified during the course of development. Nevertheless, we feel that the basic modular concept will be adhered to, and that modifications will be in the nature of implementation details. 

Computer library searching of spectral databases is routinely available. The database is usually a component part of the spectrometer although the search may be undertaken remotely. Several attempts have been made to develop artificial intelligence systems for direct spectral interpretation, but to date these have met with limited success. Advances in computer control have allowed multiexperiment analysis in which the spectrometer will follow a set of experiments sequentially while automatically adjusting operating parameters as directed by the results of the preceding experiment. Further advances in this area are anticipated. 

To construct expert systems, researchers in artificial intelligence must develop methods for mining (extracting) experience. I first encountered the... 

For homogeneous NDT data and repeatable inspection conditions successful automated interpretation systems can relatively easily be developed. They usually use standard techniques from statistical classification or artificial intelligence. Design of successful automated interpretation systems for heterogeneous data coming form non-repeatable, small volume inspections with little a-priori information about the pieces or constructions to be inspected is far more difficult. This paper presents an approach which can be used to develop such systems. 

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. 

The development of expert systems need not be costly. There are several expert system shells commercially available, and an expert in artificial intelligence (AI) is no longer needed to program them. Simple IF-THEN rules can easily be programmed in more commonly used languages like FORTRAN and BASIC. In fact, the McDonnell Aircraft expert system referred to earilier was programmed in FORTRAN. Cost depends on the number of rules and... 

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