A logical approach to case-based reasoning using fuzzy similarity relations

In order to rapidly identify internal damage levels accurately in ancient wood components, stress wave detection technology was used to perform simulated damage tests on pine specimens. Based on the detected wave velocity data, the diameter of the specimen, the attenuation coefficient, and the ratio of the wave velocities on the four paths were selected as the discriminant factors for identifying the level of internal damage in the specimens. A case-based reasoning method for discriminating internal damage levels in ancient wood components based on fuzzy similarity priority was proposed. A fuzzy similarity priority relationship between the target case and the source case was established. By introducing the idea of variable weights, the weight of each discriminant factor was determined via the “penalize-excitation” variable weight function. The comprehensive similarity sequences between the target case and the source case were obtained. The source case that was most similar to the target case was used to determine the damage level of the target case. The results showed that this method can quickly and accurately identify the damage levels in ancient wood components, which provides a new method for the safe evaluation of ancient wood buildings.

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Fuzzy similarity-based models in case-based reasoning

2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291) ◽

10.1109/fuzz.2002.1006700 ◽

2003 ◽

Cited By ~ 3

Author(s):

F. Esteva ◽

P. Garcia-Calves ◽

L. Godo

Keyword(s):

Case Based Reasoning ◽

Fuzzy Similarity ◽

Case Based

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INCREMENTAL CASE-BASED PLAN RECOGNITION WITH LOCAL PREDICTIONS

International Journal of Artificial Intelligence Tools ◽

10.1142/s0218213003001307 ◽

2003 ◽

Vol 12 (04) ◽

pp. 413-463 ◽

Cited By ~ 7

Author(s):

BORIS KERKEZ ◽

MICHAEL T. COX

Keyword(s):

Prediction Accuracy ◽

Evaluation Criteria ◽

Plan Recognition ◽

Case Based Reasoning ◽

Recognition Method ◽

Case Library ◽

Similarity Relations ◽

Case Base ◽

Multiple Domains ◽

Case Based

We present a novel case-based plan recognition method that interprets observations of plan behavior using an incrementally constructed case library of past observations. The technique is novel in several ways. It combines plan recognition with case-based reasoning and leverages the strengths of both. The representation of a plan is a sequence of action-state pairs rather than only the actions. The technique compensates for the additional complexity with a unique abstraction scheme augmented by pseudo-isomorphic similarity relations to represent indices into the case base. Past cases are used to predict subsequent actions by adapting old actions and their arguments. Moreover, the technique makes predictions despite observations of unknown actions. This paper evaluates the algorithms and their implementation both analytically and empirically. The evaluation criteria include prediction accuracy at both an abstract and a concrete level and across multiple domains with and without case-adaptation. In each domain the system starts with an empty case base that grows to include thousands of past observations. Results demonstrate that this new method is accurate, robust, scalable, and general across domains.

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THE MODULAR CONFIGURATION SYSTEM BASED ON CASE-BASED REASONING

Journal of Advanced Manufacturing Systems ◽

10.1142/s0219686712500126 ◽

2012 ◽

Vol 11 (02) ◽

pp. 135-142

Author(s):

CHANGCHUN LIU ◽

ZHONGQI SHENG ◽

LIKE WU ◽

CHAOBIAO ZHANG

Keyword(s):

Machine Tools ◽

Modular Design ◽

Numerical Control ◽

Product Configuration ◽

Cnc Machine Tools ◽

Case Based Reasoning ◽

Cnc Machine ◽

Fuzzy Similarity ◽

Configuration System ◽

Case Based

Product configuration technology is the core of the modular design of computer numerical control (CNC) machine tools. Combined with modular design technology and case-based reasoning (CBR) technology, this paper proposed a modular configuration design method based on CBR for CNC machine tools. Using the fuzzy similarity priority ratio and gray correlation analysis algorithm, respectively, the calculation of case priority and the case evaluation are realized and the best match case of the user needs is selected. The module configuration system was developed using MATLAB/gui. By designing the example and analyzing the result, the configuration system is more rapid and accurate than conventional methods in the process to find the best match instance.

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