A New Algorithm of Similarity Measuring for Multi-experts’ Qualitative Knowledge Based on Outranking Relations in Case-Based Reasoning Methodology

2006 ◽  
pp. 637-644
Author(s):  
Hui Li ◽  
Xiang-Yang Li ◽  
Jie Gu
Keyword(s):  
Case Based Reasoning ◽  
Knowledge Based ◽  
Outranking Relations ◽  
Qualitative Knowledge ◽  
Similarity Measuring ◽  
Case Based

scholarly journals Knowledge Service Technology for Supporting Intelligent Product Design

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Haiqiao Wang ◽  
Ruikun Niu
Keyword(s):  
Decision Making ◽  
Intelligent Design ◽  
Measurement Method ◽  
Numerical Control ◽  
Similarity Measurement ◽  
Case Based Reasoning ◽  
Knowledge Service ◽  
Knowledge Based ◽  
Weight Coefficients ◽  
Case Based

In this paper, a knowledge service method that supports the intelligent design of products is investigated. The proposed method provides the solutions to computational problems and reasoning and decision-making problems in the field of intelligent design. The requirement analysis of a knowledge-based intelligent design system integrates design knowledge into case-based reasoning activities through scheme analysis, scheme evaluation, and scheme adjustment, thus achieving knowledge-based intelligent reasoning and decision-making. During the similarity matching, a new hybrid similarity measurement method is proposed to calculate the similarity of crisp and fuzzy sets. This method integrates the fuzzy set similarity theory based on the traditional similarity measurement method. A method of attribute level classification is proposed to assign weight coefficients. The attributes are divided into the primary matching and auxiliary matching levels according to the decisiveness of case matching, and the set of weight coefficients is continuously and dynamically updated through case-based reasoning learning. Then, the weighted global similarity measure is used to obtain the set of similar cases from the case database. Finally, a design example of a computer numerical control tool holder product is studied to present the practicability and effectiveness of the proposed method.

scholarly journals Implementasi Metode Case Based Reasoning Untuk Mendeteksi Kerusakan Televisi

2021 ◽  
Vol 5 (2) ◽  
pp. 624
Author(s):  
Sursih Wulandari ◽  
Marnis Nasution ◽  
Mustafa Haris Munandar
Keyword(s):  
High Weight ◽  
Study Data ◽  
Design System ◽  
Case Based Reasoning ◽  
Collection System ◽  
Literature Study ◽  
Knowledge Based ◽  
Testing Case ◽  
Case Based ◽  
System Program

The process of deteriorating television should indeed be done by an expert who is a television expert himself, but because television is a tool that is no longer common for people to know him, many people also have television in their respective homes. Even for television repairs, it is quite expensive, so some people who have televisions can do television maintenance at home. The lack of knowledge possessed by the community can lead to wrong handling of television maintenance / maintenance and this has a fatal impact. Hopefully the existence of this system can help the community in diagnosing the damage to their televisions. In that case they need not bother to call for repairmen or bring in a television repair shop. Here the authors provide solutions to solve the problems that often arise on television. In this study, it discusses how to care for television officers. The research objective is to analyze a desktop-based expert system program that contains the knowledge of an expert / doctor whose truth is believed to have the ability to be able to diagnose the disease from the symptoms of damage that has been damaged by television damage quickly and precisely. The stages of research carried out in this study include literature study, data collection, system design, system creation, system testing. Case Based Reasoning is a method used to build a knowledge-based system. The source of system knowledge is obtained by collecting the handling of cases by an expert / expert. Therefore, many problems in television damage are usually due to the negligence of the television owner himself. The first step in solving a problem is by first identifying the scope of the problem to be resolved, this also applies to any Artificial Intelligence (AI) programming. The results obtained in the study for the diagnosis of conjunctivitis were the value of old cases and new cases which obtained a high weight value, namely 1 from the third case

Knowledge-Based Systems

2011 ◽  
pp. 989-995 ◽  
Author(s):  
Adrian A. Hopgood
Keyword(s):  
Computational Intelligence ◽  
Early Research ◽  
Computer Hardware ◽  
Case Based Reasoning ◽  
Major Theme ◽  
Knowledge Based Systems ◽  
Rule Based ◽  
Knowledge Based ◽  
Explicit Representations ◽  
Case Based

The tools of artificial intelligence (AI) can be divided into two broad types: knowledge-based systems (KBSs) and computational intelligence (CI). KBSs use explicit representations of knowledge in the form of words and symbols. This explicit representation makes the knowledge more easily read and understood by a human than the numerically derived implicit models in computational intelligence. KBSs include techniques such as rule-based, modelbased, and case-based reasoning. They were among the first forms of investigation into AI and remain a major theme. Early research focused on specialist applications in areas such as chemistry, medicine, and computer hardware. These early successes generated great optimism in AI, but more broad-based representations of human intelligence have remained difficult to achieve (Hopgood, 2003; Hopgood, 2005).

Applying design-dependent knowledge in structural engineering design

1989 ◽  
Vol 3 (2) ◽  
pp. 111-123 ◽  
Author(s):  
H. Craig Howard ◽  
Jenmu Wang ◽  
Francois Daube ◽  
Taufiq Rafiq
Keyword(s):  
Engineering Design ◽  
Structural Engineering ◽  
Digital Data ◽  
Long Term Results ◽  
Design System ◽  
Case Based Reasoning ◽  
Knowledge Based ◽  
Component Design ◽  
Structural Engineers ◽  
Case Based

Recent knowledge-based expert systems for structural engineering design have focused on design-independent knowledge (abstract reasoning rules for designing), and while great strides have been made in that area, there is still a significant need to develop systems to take advantage of the wealth of knowledge contained in every substantial structural design. On the other hand, previous database-oriented design efforts have focused primarily on knowledge-poor databases of solutions, in which the traditional engineering handbook of solutions has simply been replaced by digital data. The challenge is to find a way to capture and apply the kind of case-based, design-dependent knowledge that structural engineers have traditionally used. The long-term results will be better structural designs and better structural designers. This paper discusses the character of the design-dependent knowledge in a structural engineering context, describes two initial applications of case-based reasoning to component design, and presents a general paradigm for a knowledge-based design system integrating rule-based and case-based reasoning.

A Flat Composite Panel Design Advisory System Using Knowledge Based and Case Based Reasoning

1996 ◽  
Vol 118 (4) ◽  
pp. 461-469 ◽  
Author(s):  
J. P. Lambright ◽  
C. Ume
Keyword(s):  
Composite Structures ◽  
Composite Panel ◽  
Case Based Reasoning ◽  
Advisory System ◽  
Knowledge Based ◽  
Reasoning System ◽  
Design Cycle ◽  
Design And Manufacture ◽  
Prototype Design ◽  
Case Based

A method of cooperatively using Knowledge Based and Case Based Reasoning is proposed to assist designers in the design of flat composite panel structures. A Prototype Design Advisory system is constructed of heuristic and experiential rules which are acquired from composites design experts, and published text which is implemented in the CLIPS Knowledge Based System shell. The system includes design cases of previous composites design scenarios implemented in a Case Based Reasoning System using DesignMUSE. The cases all depict design of composites applied to commercial and military aircraft. The application of heuristic rules and prior similar design cases is focused upon the early stages of the design process. It is believed that such a design advisory system can aid in preventing unforeseen mistakes during the design and manufacture of composite structures, can assist in predicting the results of candidate designs, and can ultimately reduce the design cycle time.

Semantic Web Services Composition with Case Based Reasoning

2011 ◽  
pp. 36-63
Author(s):  
Dhavalkumar Thakker ◽  
Taha Osman ◽  
David Al-Dabass
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Web Service ◽  
Constraint Satisfaction Problem ◽  
Service Development ◽  
Case Based Reasoning ◽  
Web Services Composition ◽  
Services Composition ◽  
Knowledge Based ◽  
Case Based

Web service development is encouraging scenarios where individual or integrated application services can be seamlessly and securely published on the Web without the need to expose their implementation details. However, as Web services proliferate, it becomes difficult to matchmake and integrate them in response to users requests. The goal of our research is to investigate the utilization of the Semantic Web in building a developer-transparent framework facilitating the automatic discovery and composition of Web services. In this chapter, we present a Semantic Case Based Reasoner (SCBR) framework that utilizes the case based reasoning methodology for modelling dynamic Web service discovery and composition. Our approach is original as it considers the runtime behaviour of a service resulting from its execution. Moreover, we demonstrate that the accuracy of automatic matchmaking of Web services can be further improved by taking into account the adequacy of past matchmaking experiences for the requested task. To facilitate Web services composition, we extend our fundamental discovery and matchmaking algorithm using a light-weight knowledge-based substitution approach to adapt the candidate service experiences to the requested solution before suggesting more complex and computationally taxing AI-based planning-based transformations. The inconsistency problem that occurs while adapting existing service composition solutions is addressed with a novel methodology based on the Constraint Satisfaction Problem (CSP).

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