Research on Case Retrieval of Case-Based Reasoning of Motorcycle Intelligent Design

2009 ◽  
pp. 759-768
Author(s):  
Fanglan Ma ◽  
Yulin He ◽  
Shangping Li ◽  
Yuanling Chen ◽  
Shi Liang
Keyword(s):  
Intelligent Design ◽  
Case Based Reasoning ◽  
Case Retrieval ◽  
Case Based

scholarly journals Development of Ground Special Vehicle PHM with Case-Based Reason Model

2021 ◽  
Vol 11 (10) ◽  
pp. 4494
Author(s):  
Qicai Wu ◽  
Haiwen Yuan ◽  
Haibin Yuan
Keyword(s):  
Cross Validation ◽  
Optimization Methods ◽  
Engineering Practice ◽  
Case Based Reasoning ◽  
Case Retrieval ◽  
Data Set ◽  
Attribute Weights ◽  
Special Vehicle ◽  
Weight Allocation ◽  
Case Based

The case-based reasoning (CBR) method can effectively predict the future health condition of the system based on past and present operating data records, so it can be applied to the prognostic and health management (PHM) framework, which is a type of data-driven problem-solving. The establishment of a CBR model for practical application of the Ground Special Vehicle (GSV) PHM framework is in great demand. Since many CBR algorithms are too complicated in weight optimization methods, and are difficult to establish effective knowledge and reasoning models for engineering practice, an application development using a CBR model that includes case representation, case retrieval, case reuse, and simulated annealing algorithm is introduced in this paper. The purpose is to solve the problem of normal/abnormal determination and the degree of health performance prediction. Based on the proposed CBR model, optimization methods for attribute weights are described. State classification accuracy rate and root mean square error are adopted to setup objective functions. According to the reasoning steps, attribute weights are trained and put into case retrieval; after that, different rules of case reuse are established for these two kinds of problems. To validate the model performance of the application, a cross-validation test is carried on a historical data set. Comparative analysis of even weight allocation CBR (EW-CBR) method, correlation coefficient weight allocation CBR (CW-CBR) method, and SA weight allocation CBR (SA-CBR) method is carried out. Cross-validation results show that the proposed method can reach better results compared with the EW-CBR model and CW-CBR model. The developed PHM framework is applied to practical usage for over three years, and the proposed CBR model is an effective approach toward the best PHM framework solutions in practical applications.

scholarly journals Text Case-Based Reasoning Framework for Fault Diagnosis and Predication by Cloud Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Zhiwang Zhong ◽  
Tianhua Xu ◽  
Feng Wang ◽  
Tao Tang
Keyword(s):  
Cloud Computing ◽  
Fault Diagnosis ◽  
Rough Set ◽  
Best Practice ◽  
Discrete Event ◽  
Scale Up ◽  
Case Based Reasoning ◽  
Case Retrieval ◽  
Fault Features ◽  
Case Based

In Discrete Event System, such as railway onboard system, overwhelming volume of textual data is recorded in the form of repair verbatim collected during the fault diagnosis process. Efficient text mining of such maintenance data plays an important role in discovering the best-practice repair knowledge from millions of repair verbatims, which help to conduct accurate fault diagnosis and predication. This paper presents a text case-based reasoning framework by cloud computing, which uses the diagnosis ontology for annotating fault features recorded in the repair verbatim. The extracted fault features are further reduced by rough set theory. Finally, the case retrieval is employed to search the best-practice repair actions for fixing faulty parts. By cloud computing, rough set-based attribute reduction and case retrieval are able to scale up the Big Data records and improve the efficiency of fault diagnosis and predication. The effectiveness of the proposed method is validated through a fault diagnosis of train onboard equipment.

Survey on structure-based case retrieval

1997 ◽  
Vol 12 (01) ◽  
pp. 41-58 ◽  
Author(s):  
FRIEDRICH GEBHARDT
Keyword(s):  
Structural Properties ◽  
Case Based Reasoning ◽  
Case Retrieval ◽  
Model Based ◽  
Main Components ◽  
Case Based

The main components of case-based reasoning are case retrieval and case reuse. While case retrieval mostly uses attribute comparisons, many other possibilities exist. The case similarity concepts described in the literature that are based on more elaborate structural properties are classified here into five groups: restricted geometric relationships; graphs; semantic nets; model-based similarities; hierarchically structured similarities. Some general topics conclude this survey on structure-based case retrieval methods and systems.

Classification Algorithm of Case Retrieval Based on Granularity Calculation of Quotient Space

2020 ◽  
pp. 2150003
Author(s):  
Jiaxing Lu ◽  
Jiang Qing ◽  
Huang He ◽  
Zhang Zhengyong ◽  
Wang Rujing
Keyword(s):  
Quotient Space ◽  
Inner Product ◽  
Retrieval Algorithm ◽  
Case Based Reasoning ◽  
Case Retrieval ◽  
Current Case ◽  
Quotient Spaces ◽  
Similarity Calculation ◽  
Key Steps ◽  
Case Based

Case retrieval is one of the key steps of case-based reasoning. The quality of case retrieval determines the effectiveness of the system. The common similarity calculation methods based on attributes include distance and inner product. Different similarity calculations have different influences on the effect of case retrieval. How to combine different similarity calculation results to get a more widely used and better retrieval algorithm is a hot issue in the current case-based reasoning research. In this paper, the granularity of quotient space is introduced into the similarity calculation based on attribute, and a case retrieval algorithm based on granularity synthesis theory is proposed. This method first uses similarity calculation of different attributes to get different results of case retrieval, and considers that these classification results constitute different quotient spaces, and then organizes these quotient spaces according to granularity synthesis theory to get the classification results of case retrieval. The experimental results verify the validity and correctness of this method and the application potential of granularity calculation of quotient space in case-based reasoning.

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.

Research of Case Retrieval Strategy in Case-Based Reasoning

2013 ◽  
Vol 278-280 ◽  
pp. 2016-2019 ◽  
Author(s):  
Jian Hua Song ◽  
Zheng Wang ◽  
Lei Zhang
Keyword(s):  
Case Based Reasoning ◽  
Retrieval Strategy ◽  
Case Retrieval ◽  
Matching Algorithm ◽  
Field Matching ◽  
The Times ◽  
The Impact ◽  
Case Based

This paper put forward a new retrieval strategy which combines character field matching algorithm with the NNH in Case-Based Reasoning. The new retrieval strategy can reduce the times of symptoms match while streamlining retrieved result, and lower the impact of large symptom value difference in the result. The superiority of the strategy is verified by three target cases.

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.

A Similarity Measure Based on Extension Distance and Its Application in CBR

2008 ◽  
Author(s):  
Yanwei Zhao ◽  
Feng Zhang ◽  
Nan Su ◽  
Huijun Tang ◽  
Jian Chen
Keyword(s):  
Standard Deviation ◽  
Similar Case ◽  
Similarity Measures ◽  
Case Based Reasoning ◽  
Case Retrieval ◽  
Similarity Model ◽  
Electric Drill ◽  
Classical Distance ◽  
Case Based

Case-based reasoning (CBR) is an effective method that integrates reasoning methodology and represents related knowledge in a domain. The success of a CBR system largely depends on case retrieval, and the similarity and determination of weight for each case features have a significant influence on the efficiency and accuracy of case retrieval. The aim of the research is to improve the efficiency and accuracy of case retrieval. Analyzing the deficiency of similarity measures based on the classical distance, different similarity measures are proposed for different kinds of attribute values based on the extension distance, especially the similarity model between numerical and set considered the customer’s preference. The standard deviation related with the similarity is introduced to distribute the dynamic attribute’s weights which also considered the customer’s interest, but not the traditional methods that the weight is a constant if determined. The presented methods will enable the system to retrieve the more similar case correctly so that reducing case adaptation. In this study, an electric drill is used as a case to verify the usefulness and effectiveness of the similarity measurements and weight assignments. It is demonstrated that this method is more beneficial to case retrieval compared with other methods.

scholarly journals A Dynamic Emergency Decision-Making Method Based on Group Decision Making with Uncertainty Information

2020 ◽  
Vol 11 (5) ◽  
pp. 667-679
Author(s):  
Jing Zheng ◽  
Yingming Wang ◽  
Kai Zhang ◽  
Juan Liang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Case Based Reasoning ◽  
Case Retrieval ◽  
Gas Explosion ◽  
Historical Case ◽  
Emergency Decision Making ◽  
Emergency Decision ◽  
Case Based

Abstract In emergency decision making (EDM), it is necessary to generate an effective alternative quickly. Case-based reasoning (CBR) has been applied to EDM; however, choosing the most suitable case from a set of similar cases after case retrieval remains challenging. This study proposes a dynamic method based on case retrieval and group decision making (GDM), called dynamic case-based reasoning group decision making (CBRGDM), for emergency alternative generation. In the proposed method, first, similar historical cases are identified through case similarity measurement. Then, evaluation information provided by group decision makers for similar cases is aggregated based on regret theory, and comprehensive perceived utilities for the similar cases are obtained. Finally, the most suitable historical case is obtained from the case similarities and the comprehensive perceived utilities for similar historical cases. The method is then applied to an example of a gas explosion in a coal company in China. The results show that the proposed method is feasible and effective in EDM. The advantages of the proposed method are verified based on comparisons with existing methods. In particular, dynamic CBRGDM can adjust the emergency alternative according to changing emergencies. The results of application of dynamic CBRGDM to a gas explosion and comparison with existing methods verify its feasibility and practicability.

Sign in / Sign up

Export Citation Format

Share Document