Knowledge inference mechanism

Knowledge inference mechanism provides solution recommendations for decision makers and problem solvers. 

With the view that a KBS interpreter is a method for mapping from input data in the form of intermediate symbolic state descriptions to labels of interest, four families of approaches are described here, each offering inference mechanisms and related knowledge representations that can be used to solve interpretation problems namely, model-based approaches, digraphs, fault trees, and tables. These methods have been heavily used... 

Most expert systems are developed via specialized software tools called shells. These shells come equipped with an inference mechanism — backward chaining, forward chaining, or both — and require knowledge to be entered according to a specified format. We will have a closer look at several tools for developing expert system in this chapter. 

Facts, rules and quantitative models are the chosen forms of representation for the different areas of knowledge in the field of wool dyeing. But these parts are not independent, they must be tied together, i.e. an inference mechanism is needed. The theoretical concepts of forward and backward chaining in their pure forms turned out to be insufficient to catch fully the expert s knowledge about the connections and interdependencies between the various aspects. Only a careful detailed analysis of the expert s behavior allowed implementation of an adequate inference mechanism, which turned out to be a mixture of several theoretical approaches. 

It was inevitable that computers will be utilised to exploit the similarity of parts and this led to the Variant Method [4], it became the cornerstone of what is we now call Computer Aided Process Planning (CAPP). Variant Method exploits the similarity of parts as well as the similarity of processes. This similarity can be on the basis of individual process or it can be on the basis of group of processes. The main disadvantage of this procedure is that the quality of process design still depends to a considerable extent on the knowledge of the methods engineer. There are no inference mechanisms in the procedure to fine-tune the process design. This is often required because there are tolerances and various levels of stresses involved in the manufacture of parts and this requires experience to create a feasible process plan. 

Schema (RDFS). RDF(S) provides language constructs to formulate simple graphs containing class and property hierarchies as well as property restrictions. With its formal semantics, RDF(S) leaves no room for interpretation of what conclusions can be drawn from a given graph, thereby providing standard inference mechanisms for any RDF(S)-compliant graph. RDF(S) can, hence, be used as a language to model simple ontologies, but provides limited expressive means and is not suitable to formulate more complex knowledge (Hitzler et al. 2010). Examples for knowledge that cannot be formulated in RDF(S) are the phrases Each Module consists of at least one component and Components are either actuators or sensors.

The developed system serves as an aid to the user in decision making. It prepares and selects the most promising solutions while the final choice is made by the user. The system is based on expert system technique within which the engineering knowledge base, inference mechanism and communication interface are integrated. It has been implemented using TURBO PASCAL ver 5.0 on the IBM -PC. 

The applications of this simple measure of surface adsorbate coverage have been quite widespread and diverse. It has been possible, for example, to measure adsorption isothemis in many systems. From these measurements, one may obtain important infomiation such as the adsorption free energy, A G° = -RTln(K ) [21]. One can also monitor tire kinetics of adsorption and desorption to obtain rates. In conjunction with temperature-dependent data, one may frirther infer activation energies and pre-exponential factors [73, 74]. Knowledge of such kinetic parameters is useful for teclmological applications, such as semiconductor growth and synthesis of chemical compounds [75]. Second-order nonlinear optics may also play a role in the investigation of physical kinetics, such as the rates and mechanisms of transport processes across interfaces [76]. 

Consequently the overall reaction is of order 0.5 in [C2H6]. Equation 13.42 only holds for a low conversion at higher conversions of ethane into ethylene and hydrogen, subsequent reactions of these components would have to be considered. Ethane pyrolysis is another example that global parameters can be inferred from knowledge of the detailed chemistry. Global rate measurements can then be used to verify the proposed mechanism. 

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