Computer methods expert system

Hansch QSAR and related approaches belong to the world of numbers conceptually, knowledge-based expert system approaches do not. Three areas of debate about expert systems have arisen from the distinction. Can you devise ways to generate qualified output from computer-based expert systems without hiding quantitative methods inside them Assuming you can, how do you validate an expert system How can you usefully combine output from different systems—some quantitative and some qualitative—to make predictions more reliable The first of the questions is more a historical than a current one some of the systems described earlier in this chapter demonstrate... 

Woodruff and co-workers introduced the expert system PAIRS [67], a program that is able to analyze IR spectra in the same manner as a spectroscopist would. Chalmers and co-workers [68] used an approach for automated interpretation of Fourier Transform Raman spectra of complex polymers. Andreev and Argirov developed the expert system EXPIRS [69] for the interpretation of IR spectra. EXPIRS provides a hierarchical organization of the characteristic groups that are recognized by peak detection in discrete ames. Penchev et al. [70] recently introduced a computer system that performs searches in spectral libraries and systematic analysis of mixture spectra. It is able to classify IR spectra with the aid of linear discriminant analysis, artificial neural networks, and the method of fe-nearest neighbors. 

The quahty of an analytical result also depends on the vaUdity of the sample utilized and the method chosen for data analysis. There are articles describiag Sampling and automated sample preparation (see Automated instrumentation) as well as articles emphasizing data treatment (see Chemometrics Computer technology), data iaterpretation (see Databases Imaging technology), and the communication of data within the laboratory or process system (see Expert systems Laboratory information managet nt systems). 

As computing capabiUty has improved, the need for automated methods of determining connectivity indexes, as well as group compositions and other stmctural parameters, for existing databases of chemical species has increased in importance. New naming techniques, such as SMILES, have been proposed which can be easily translated to these indexes and parameters by computer algorithms. Discussions of the more recent work in this area are available (281,282). SMILES has been used to input Contaminant stmctures into an expert system for aquatic toxicity prediction by generating LSER parameter values (243,258). 

Uses raw data from field tests to compute hydraulic conductivity computed value is evaluated by the expert system for its correctness with regard to these considerations site-specific geological characteristics, validity of test procedures, accuracy of the raw data, and the computational method. System is written in Arity-Prolog on a PC. 

The relevant calculations are commonly handled poorly, because the equilibrium equations involved are difficult to solve manually (but not with computers). The few calculations that are actually reported in the biochemical literature use simplified methods of limited and frequently unknown validity. Large excesses of magnesium ion are frequently used in experiments, perhaps in an attempt to avoid such calculations. The relevant theory is well worked out and there are excellent reviews. The limitation appears to involve diffusion to the (mathematically) inexpert user, which is one of the motivations of building expert systems. 

There is some disagreement within the AI community as to what qualifies a computer program to be called an "expert system". We use the term to describe a program which has the following characteristics 1) The program performs some task (e.g., HPLC methods design) which requires specialized human expertise. This human expertise often takes the form of heuristics (empirical rules of... 

Alternative methods include (1) computer-based methods (mathematical models and expert systems) (2) physicochemical methods, in which physical or chemical effects are assessed in systems lacking cells and, most typically, (3) in vitro methods, in which biological effects are observed in cell cultures, tissues, or organs. 

Section 2.2.1 briefly addresses the possibility to incorporate a scheme for the selection of chromatographic methods in a computer program, a so-called expert system. This is a relatively recent proposition, and progress may be expected in this area. 

The other method is a computer- or statistically-based expert system, for which a large training data set of compounds with known toxicity is needed to derive structural features that are highly correlated to the specified toxicity (Durham and Pearl 2001). An example of a typical computer- or statistically-based expert system is MultiCASE, which will also be described later. 

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