Product Configuration Knowledge Modeling Using Extend Object Model

2009 ◽  
Vol 16-19 ◽  
pp. 394-398
Author(s):  
Zhi Wei Xu ◽  
Zhong Qi Sheng ◽  
Hua Long Xie
Keyword(s):  
Product Configuration ◽  
Design System ◽  
Configuration Model ◽  
Configuration Design ◽  
Case Based Reasoning ◽  
Object Model ◽  
Case Representation ◽  
Extended Object ◽  
Extended Object Model ◽  
Case Based

This paper presents an extended object model for case-based reasoning in product configuration design. In the extended object model a few of methods of knowledge expression are adopted such as constraints, rules, objects etc. On the basis of extended object model, case representation model for case-based reasoning is applied to product configuration design system. The product configuration knowledge can be represented by the extended object. The model can support all the processes of case-based reasoning in product configuration design such as case representation, indexing, retrieving and case revising. The model extends traditional object-oriented model by including the relationship class used to express the relation between the cases, constraints class used in the product configuration knowledge representation, index class used in case retrieving, solution class used in case revise. So the product configuration knowledge that used in the product configuration design can be represented by using this model. In the end a Metering pump product configuration design systems is developed on the basis of the proposed product configuration model to support customized products.

Extension Case-Based Reasoning for Product Configuration Design

2009 ◽  
Vol 69-70 ◽  
pp. 616-620 ◽  
Author(s):  
Yan Wei Zhao ◽  
F. Zhang ◽  
M.Y. Zhang ◽  
Jian Chen ◽  
N. Su
Keyword(s):  
Solution Space ◽  
Product Configuration ◽  
Configuration Design ◽  
Prototype System ◽  
Case Based Reasoning ◽  
Final Configuration ◽  
Similarity Calculation ◽  
Overall Evaluation ◽  
Configuration Scheme ◽  
Case Based

The interface was regarded as standard and not considered in traditional configuration design, which made it difficult to apply to the existence product configuration. The paper proposes an extension case-based reasoning for product configuration design. With matter-elements, reasoning model of Extension Case-Based Reasoning (ECBR) is established, and its corresponding algorithm is proposed. During the configuration design, the solution space of configuration schemes is obtained by the similarity calculation, and then the overall evaluation of similarity and compatible degrees is adopted to form the final configuration scheme. A prototype system of reducer configuration design is successfully developed according to the method, and it proves the proposed method that is feasible and effective.

A design-plan-oriented methodology for applying case-based adaptation to engineering design

1998 ◽  
Vol 12 (5) ◽  
pp. 463-478 ◽  
Author(s):  
TALAL AL-SHIHABI ◽  
IBRAHIM ZEID
Keyword(s):  
Engineering Design ◽  
Design Problem ◽  
Structural Engineering ◽  
Design System ◽  
Case Based Reasoning ◽  
Adaptation Process ◽  
Case Representation ◽  
Generic Framework ◽  
Design Plan ◽  
Case Based

Adaptation of design cases is usually the most challenging part in building any case-based reasoning design system. The success of the adaptation process in finding a solution for a new design problem determines the success of the entire case-based reasoning (CBR) system. The techniques used for generating design solutions have many common aspects among the various engineering design classes that make them amenable to be captured in a generic framework for an acceptable level of abstraction. This paper proposes a design-plan-oriented methodology for adapting design cases to produce a solution to a new design problem in the domain of engineering design. The proposed methodology uses multicase adaptation and case built-in adaptation knowledge to produce a design plan for a new design problem. We first define the model of case representation to work with the proposed methodology. We then define the overall structure of the procedural framework of this methodology and its subprocesses. The system is then demonstrated through an application from the structural engineering domain.

Case Representation and Organization Studies on Case-Based Reasoning Maintenance Resources Requirement Analysis

2013 ◽  
Vol 389 ◽  
pp. 698-702
Author(s):  
Xiao Chen ◽  
Ling Chen ◽  
Wo Ye Liu ◽  
Fei Han
Keyword(s):  
Prototype System ◽  
Case Based Reasoning ◽  
Requirement Analysis ◽  
Organization Studies ◽  
Case Representation ◽  
Relation Database ◽  
Analysis Process ◽  
System Perfection ◽  
Analysis System ◽  
Case Based

To improve the efficiency of planning maintenance resources requirement, the artificial intelligent (AI) technology, especially Case-Based Reasoning (CBR) is applied into maintenance resources requirement analysis process, the process is introduced, and the critical techniques of which, such as case representation and organization etc, are discussed in detail, according to the case characteristics, analyzed the cases main ingredient, cases representation and organization which is based on Relation Database and Object Oriented are detailed discussed, the development of case-based maintenance resources requirement analysis prototype system proved the validity of the technique, formed the foundation for the case-based maintenance resources requirement analysis system perfection.

A Case Representation and Similarity Measurement Model with Experience-Grounded Semantics

2020 ◽  
Vol 30 (01) ◽  
pp. 119-146
Author(s):  
Nady Slam ◽  
Wushour Slamu ◽  
Pei Wang
Keyword(s):  
Semantic Similarity ◽  
Measurement Model ◽  
Similarity Measurement ◽  
Case Based Reasoning ◽  
Case Representation ◽  
Proposed Model ◽  
Semantic Similarity Measurement ◽  
Intelligent Decision Support ◽  
Grounded Semantics ◽  
Case Based

Case-based reasoning heavily depends on the structure and content of the cases, and semantics is essential to effectively represent cases. In the field of structured case representation, most of the works regarding case representation and measurement of semantic similarity between cases are based on model-theoretic semantics and their extensions. The purpose of this study is to explore the potential of experienced-grounded semantics in case representation and semantic similarity measurement. The main contents in this study are as follows: (i) a case representation model based on experience-grounded semantic is proposed, (ii) a novel semantic similarity measurement method with multi-strategy reasoning is introduced, and (iii) a case-based reasoning software for urban firefighting field based on the proposed model is designed and implemented. Theoretically, compared with traditional structured case representation methods, the proposed model not only represents case in a fully formalized way, but also provides a novel metric for computing the strength of the semantic relationship between cases. The proposed model has been applied in an intelligent decision-support software for urban firefighting.

scholarly journals An Associated Representation Method for Defining Agricultural Cases in a Case-Based Reasoning System for Fast Case Retrieval

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5118 ◽  
Author(s):  
Zhai ◽  
Martínez Ortega ◽  
Beltran ◽  
Lucas Martínez
Keyword(s):  
Intelligent Systems ◽  
Case Based Reasoning ◽  
Case Retrieval ◽  
Traditional Methods ◽  
Case Representation ◽  
Reasoning System ◽  
Case Base ◽  
Representation Method ◽  
Associated Representation ◽  
Case Based

As an artificial intelligence technique, case-based reasoning has considerable potential to build intelligent systems for smart agriculture, providing farmers with advice about farming operation management. A proper case representation method plays a crucial role in case-based reasoning systems. Some methods like textual, attribute-value pair, and ontological representations have been well explored by researchers. However, these methods may lead to inefficient case retrieval when a large volume of data is stored in the case base. Thus, an associated representation method is proposed in this paper for fast case retrieval. Each case is interconnected with several similar and dissimilar ones. Once a new case is reported, its features are compared with historical data by similarity measurements for identifying a relative similar past case. The similarity of associated cases is measured preferentially, instead of comparing all the cases in the case base. Experiments on case retrieval were performed between the associated case representation and traditional methods, following two criteria: the number of visited cases and retrieval accuracy. The result demonstrates that our proposal enables fast case retrieval with promising accuracy by visiting fewer past cases. In conclusion, the associated case representation method outperforms traditional methods in the aspect of retrieval efficiency.

Soft case-based reasoning

2005 ◽  
Vol 20 (3) ◽  
pp. 267-269 ◽  
Author(s):  
WILLIAM CHEETHAM ◽  
SIMON SHIU ◽  
ROSINA O. WEBER
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Network Theory ◽  
Probabilistic Reasoning ◽  
Case Based Reasoning ◽  
Case Representation ◽  
Soft Computing Techniques ◽  
Neural Network Theory ◽  
Case Based

The aim of this commentary is to discuss the contribution of soft computing—a consortium of fuzzy logic, neural network theory, evolutionary computing, and probabilistic reasoning—to the development of case-based reasoning (CBR) systems. We will describe how soft computing has been used in case representation, retrieval, adaptation, reuse, and case-base maintenance, and then present a brief summary of six CBR applications that use soft computing techniques.

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