Case-based

Case-Based Reasoning. Case-Based Reasoning (CBR) systems base their solutions on previously solved problems (cases) which are stored in a case-base [Watson Marir, 1994]. When a new problem is presented to a CBR system a similar case(s) is/are retrieved from the case-base. Depending on the differences between the retrieved and the presented problem the retrieved solution may have to be more or less adapted to obtain a solution to the new problem. The solved problem may be retained in the case base if deemed useful. 

Case-based reasoning. The main advantage of CBR systems for NDT data interpretation is that they can cope with data coming from inspection of varying constructions under varying conditions with various system settings due to their ability to learn from the data classified by the operator. In such situations no reliahle statistical classifier can be designed, and the rule-hased classifiers would be either very inefficient or unpractically complex. 

Because the system is meant to be used for a variety of heat exchangers we could not use a simple (ANN) classifier, but we chose for a CBR type system. The case-base stores signal shapes with corresponding classifications or actions to be taken (e.g. signal mixing). Beftxe each inspection the case-base is filled with data from calibration pipes oc a case-base from a previous similar inspection can be used. For each new possible defect signal a search is done in the case base for the most similar case. 

The end users of CBR systems should in principle be able to maintain the case-bases themselves and use the systems for varying inspection types (within certain limits). Adaptation of neural-network based systems, though possible by end-users, is difficult to be done reliably. Adaptation of rule-based systems usually has to be done by the rule-base designer. 

Case-based reasoning CA. See Cyanuric acid Case-hardened steels Case hardening... 

Eor a number of cognitive or interpretive tasks, there are alternatives to mainstream knowledge-based systems that may be more appropriate, especially if adaptive behavior and learning capabihty are important to system performance. Two approaches that embody these characteristics are neural networks (nets) and case-based reasoning. 

C. Riesbeck and R. C. Schank, Inside Case-Based Keasoning, Lawrence Erlbaum, Hillsdale, N.J., 1989. 

K. Sycara, "Using Case-Based Reasoning for Plan Adaptation and Repair," in Proceedings of the DARPA Workshop on Case-Based Reasoning, Morgan... 

D. Navinchandra, "Case-Based Reasoning in CYCLOPS, A Design Problem Solver," in Ref. 82. 

P. Koton, "SMARTPLAN A Case-Based Resource Allocation and Scheduling System," in Proceedings of a Workshop on Case-Based Reasoning, Morgan Kaufman, San Mateo, Calif., 1989. 

W. Mark, "Case-Based Reasoning for Autoclave Management," in Ref. 85. 

Note The estimates were in some cases based on different sublets of samples for the different failure modes. This results from tests of statistical consistence among samples, see sect 3.4. 

Case-based reasoning is very much dependent on the structure and content of its cases and their representation because case retrieval involves identifying those features in the problem that best match those in the case base. The dynamic addition of new cases means that CBR is intrinsically a learning methodology such that the performance of an expert system based on this approach will improve with time [9]. Systems may be developed with conventional computer languages or shells [7]. 

Goodall A. Preface. In Althoff KD, A review of industrial case-based reasoning tools. Oxford AI Intelligence, 1995. 

Aamodt A, Plaza E. Case-based reasoning—foundational issues, methodological variations and system approaches. AI Commun 1994 7 39-59. 

Watson I. Applying case-based reasoning techniques for enterprising systems. San Francisco Morgan Kaufmann, 1997. 

Rowe RC, Craw S, Wiratunga N. Case-based reasoning—a new approach to tablet formulation. Pharm Tech Eur 1999 ll(2) 36-40. 

In such a case, based on the results of a collaborative study, a content is assigned to the corresponding reference substance which is method specific, i.e. it is only to be used with the method described in the monograph. The establishment of these substances is described in more detail later in the Chapter. 

Most of the constrained parameter estimation problems belong to this case. Based on scientific considerations, we arrive quite often at constraints that the parameters of the mathematical model should satisfy. Most of the time these are of the form,... 

Kimura K, Hasegawa M, Matsubara K, et al. 1994. A fatal disaster case based on exposure to hydrogen sulfide - an estimation of the hydrogen sulfide concentration at the scene. Forensic Sci Int 66 111-116. 

West, J.B., Pulmonary Physiology and Pathophysiology, an Integrated, Case-Based Approach, Lippincott/Williams Wilkins, Philadelphia, 2001. 

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