Rule-based techniques

Most approaches use context-sensitive rewrite rules of the type introduced in Section 5.2.4. Recall that these are of the form 

Grapheme-to-phoneme conversion by rule is perhaps the classic application of traditional knowledge based rules in TTS. Indeed, in the past it was thought that this was how humans performed the task when presented with an unknown word they would apply a set of rules to find the pronunciation. The most common approach is to process the character sequence left-to-right, and for each character apply one or more rules in order to generate a phoneme. It should be clear that these rules can t operate in isolation, otherwise a t character would always result in a /t/ phoneme. Rather the character context of the character is used and in this was we can generate /th/ when t is followed by h. 

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In this case, systematic methods for generation of feasible molecular and mixture candidates have been reported for the design of functional chemical products [see Achenie et al (2003)]. Methods based on database search, total enumeration of feasible candidates (rule-based techniques that avoid a combinatorial explosion), mathematical programming, genetic algorithm, and,... 

Approach I indicates statistical automated algorithms not dependent on prior expert judgment. Approach II indicates a rule-based technique that requires prior expert judgment. 

These techniques span the entire field from multiple linear regression (MLR)-type methods and various forms of neural network architectures to rule-based techniques of different kinds. These approaches also span from single models to multiple models, that is, consensus or ensemble modeling. Terms like machine learning and data or information fusion are also frequently encountered in this area of research, as well as the concepts of applicability domain and validation. 

Fig. 8 Performance comparison between the proposed fuzzy based technique and the crisp rule based technique under vtuying zooming conditions at 4 1 compression ratio a flower, b Stefan...

Hybrid systems. Depending on the problem to be solved, use can also be made of a combination of techniques leading to a hybrid system. For example, a rule-based system may use neural networks for solving classification subproblems (as is described in [Hopgood, 1993]), or a combination of a rule-based and a CBR system can be used as in the system for URS data interpretation described later in this paper. 

Ihe rule-based approach to protein structure prediction is obviously very reliant on th quality of the initial secondary structure prediction, which may not be particularly accurate The method tends to work best if it is known to which structural class the protein belongs this can sometimes be deduced from experimental techniques such as circular dichroism... 

Chen et al. [24] provide a good review of Al techniques used for modeling environmental systems. Pongracz et al. [25] presents the application of a fuzzy-rule based modeling technique to predict regional drought. Artificial neural networks model have been applied for mountainous water-resources management in Cyprus [26] and to forecast raw-water quality parameters for the North Saskatchewan River [27]. 

Pongracz R, Bogardi I, Duckstein L (1999) Application of fuzzy rule-based modelling technique to regional drought. J Hydrol 224 100-114... 

Thus, besides being sensitive to absorbing species on the electrode surface as well as in the solution in the region very close to the surface, it is possible to obtain potential dependent behavior in fine detail. We have applied these techniques to examine the interaction of simple ions such as CN and Ny with polycrystalline electrodes of silver, gold and copper. The observed vibrational spectra can be interpreted with the help of selection rules based on symmetry and analysis of ab-initio SCF wavefunctions of clusters. The results of these studies will be reviewed. 

Rule-based structure generation techniques, 16 751-752 Rule of 5, in diversity analysis, 6 18 Rules... 

A potentially much more adaptable technique is force-field vibrational modeling. In this method, the effective force constants related to distortions of a molecule (such as bond stretching) are used to estimate unknown vibrahonal frequencies. The great advantage of this approach is that it can be applied to any material, provided a suitable set of force constants is known. For small molecules and complexes, approximate force constants can often be determined using known (if incomplete) vibrational specha. These empirical force-field models, in effect, represent a more sophisticated way of exhapolating known frequencies than the rule-based method. A simple type of empirical molecular force field, the modified Urey-Bradley force field (MUBFF), is introduced below. 

Section 9.2 will review traditional statistical process control/statistical quality control (SPC/SQC) techniques used in quality control. Section 9.3 will follow this review with a discussion of techniques based primarily on an experiential rule base and expert system technology. Section 9.4 will discuss control strategies that use an on-line process model a variety of models can be used in such model predictive control. Section 9.5 will discuss this variety of models. Section 9.6 will summarize this chapter and discusses future trends in the field. 

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