Improving the quality of technical data for developing case based reasoning diagnostic software for aircraft maintenance

1997 ◽  
Author(s):  
R. Heider
Keyword(s):  
Case Based Reasoning ◽  
Aircraft Maintenance ◽  
Technical Data ◽  
Diagnostic Software ◽  
Case Based

Intelligent Tool for Decision Making Associated With Hospitalization and Sandstorms for the Optimization of Ambulances

2019 ◽  
pp. 50-61
Author(s):  
Estrella D. Molina-Herrera ◽  
Luis Ernesto Cervera-Gómez ◽  
Carlos Herrera
Keyword(s):  
United States ◽  
Decision Making ◽  
El Paso ◽  
Future Research ◽  
Case Based Reasoning ◽  
Dijkstra Algorithm ◽  
Postgraduate Students ◽  
Innovative Model ◽  
Case Based

The shortest path problem is a typical problem of optimization. This chapter presents an innovative model associated with the use of case-based reasoning to solve a problem of routing vehicles in a Hospital of El Paso, United States. In this chapter, diverse components are described to characterize this problem through the use of a knowledge system. The algorithm was developed in Java, thus obtaining a tool which determines the best tracks to the vehicles associated with ambulances. An experiment was realized to probe the validations; the results were used to compare it with the Dijkstra algorithm and determine the quality of the results. The future research of this intelligent tool is to determine an innovative perspective related to episodic knowledge applied to resolution of diverse ambulances, and as this topic is determinative to find and remember the best solutions quickly, additionally the authors compare it with a code from other postgraduate students trying to implement an algorithm similar to logistics but using a shuffled frog leap algorithm.

Overview of Machine Learning Approaches

2017 ◽  
pp. 19-33
Keyword(s):  
Machine Learning ◽  
Software Quality ◽  
Fault Prediction ◽  
Machine Learning Techniques ◽  
Case Based Reasoning ◽  
Learning Approaches ◽  
Software Module ◽  
Learning Techniques ◽  
Case Based

This chapter enlists and presents an overview of various machine learning approaches. It also explains the machine learning techniques used in the area of software engineering domain especially case-based reasoning method. Case-based reasoning is used to predict software quality of the system by examining a software module and predicting whether it is faulty or non-faulty. In this chapter an attempt has been made to propose a model with the help of previous data which is used for prediction. In this chapter, how machine learning technique such as case-based reasoning has been used for error estimation or fault prediction. Apart from case-based reasoning, some other types of learning methods have been discussed in detail.

Customized Recommendation Mechanism Based on Web Data Mining and Case-Based Reasoning

2008 ◽  
pp. 2659-2672
Author(s):  
Jin Sung Kim
Keyword(s):  
Data Mining ◽  
Shopping Mall ◽  
Case Based Reasoning ◽  
Web Data ◽  
Web Data Mining ◽  
Web Based ◽  
Additional Information ◽  
Hybrid Recommendation ◽  
Case Based

One of the attractive topics in the field of Internet business is blending Artificial Intelligence (AI) techniques with the business process. In this research, we suggest a web-based, customized hybrid recommendation mechanism using Case-Based Reasoning (CBR) and web data mining. CBR mechanisms are normally used in problems for which it is difficult to define rules. In web databases, features called attributes are often selected first for mining the association knowledge between related products. Therefore, data mining is used as an efficient mechanism for predicting the relationship between goods, customers’ preference, and future behavior. If there are some goods, however, which are not retrieved by data mining, we can’t recommend additional information or a product. In this case, we can use CBR as a supplementary AI tool to recommend the similar purchase case. Web log data gathered in a real-world Internet shopping mall was given to illustrate the quality of the proposed mechanism. The results showed that the CBR and web data mining-based hybrid recommendation mechanism could reflect both association knowledge and purchase information about our former customers.

Customized Recommendation Mechanism Based on Web Data Mining and Case-Based Reasoning

2004 ◽  
pp. 47-64 ◽  
Author(s):  
Jin Sung Kim
Keyword(s):  
Data Mining ◽  
Shopping Mall ◽  
Case Based Reasoning ◽  
Web Data ◽  
Web Data Mining ◽  
Web Based ◽  
Additional Information ◽  
Hybrid Recommendation ◽  
Case Based

One of the attractive topics in the field of Internet business is blending Artificial Intelligence (AI) techniques with the business process. In this research, we suggest a web-based, customized hybrid recommendation mechanism using Case-Based Reasoning (CBR) and web data mining. CBR mechanisms are normally used in problems for which it is difficult to define rules. In web databases, features called attributes are often selected first for mining the association knowledge between related products. Therefore, data mining is used as an efficient mechanism for predicting the relationship between goods, customers’ preference, and future behavior. If there are some goods, however, which are not retrieved by data mining, we can’t recommend additional information or a product. In this case, we can use CBR as a supplementary AI tool to recommend the similar purchase case. Web log data gathered in a real-world Internet shopping mall was given to illustrate the quality of the proposed mechanism. The results showed that the CBR and web data mining-based hybrid recommendation mechanism could reflect both association knowledge and purchase information about our former customers.

Knowledge and Case-Based Reasoning for Customization of Software Processes — A Hybrid Approach

2003 ◽  
Vol 13 (03) ◽  
pp. 293-312 ◽  
Author(s):  
Yu Whoan Ahn ◽  
Hyung Jun Ahn ◽  
Sung Joo Park
Keyword(s):  
Hybrid Approach ◽  
Case Based Reasoning ◽  
Software Products ◽  
Types Of Knowledge ◽  
Knowledge Based ◽  
Project Characteristics ◽  
Software Processes ◽  
Past Experiences ◽  
Case Based

Software processes must be properly designed according to various project characteristics, past experiences, and improvement initiatives in order to ensure the quality of software products. Because various types of knowledge are required for designing software processes, many parts of the designs depend on the knowledge of experts and manual activities. Consequently, design processes can be time-consuming and error prone. To overcome this problem, this paper proposes a mechanism that supports the customization of software processes. Since integration of various types of knowledge is required in the customization process, the proposed approach uses a hybrid method combining CBR (Case Based Reasoning) and knowledge-based technique. CBR is used to facilitate re-use of past experiences; knowledge-based technique is used to derive process components using knowledge-based inferencing and to resolve conflicts that may occur during customization. To support the two approaches in a seamless manner, an organizational process library (PL) is designed which defines and shares various types of process knowledge and reusable objects throughout the whole customization procedure. An illustrative example is presented to show how the hybrid approach can be used to design actual software processes.

Building the CBR-Based Identification System Framework for Construction Accident Precursors

2011 ◽  
Vol 255-260 ◽  
pp. 546-550 ◽  
Author(s):  
Xian Zhi Liu ◽  
Ting Sheng Zhao ◽  
Kai Xiao
Keyword(s):  
Safety Management ◽  
Identification System ◽  
Case Based Reasoning ◽  
Construction Sites ◽  
System Framework ◽  
Accident Case ◽  
Case Based ◽  
Historical Accident

Construction accident precursors(CAPs) are potential upcoming accident signals and offer the possibility for improving safety management performance. Case-based reasoning (CBR) as an artificial intelligence(AI) tools can be used to improve the efficiency and quality of CAPs identification. This paper developed a system framework for identifying CAPs on construction sites using CBR. There were ten indicators, including six problem indicators and four solution indicators were identified to describe the CAPs case between the accident characteristics and corresponding precursors. Especially, a technique case-based adaptation was implemented in the adaptation stage of CBR called inner CBR and three indicators were identified to describe the adaptation case. Eventually, the CAPs identification system framework was presented and a case study based on actual accident case from US Department of OSHA was used to illustrate how to seek CAPs.This research provides a new way to acquire more useful information from historical accident records in order to improve safety on construction sites for future ongoing project.

Case Based Reasoning for Customizing Treatment Processes

2009 ◽  
pp. 351-366
Author(s):  
Carolin Kaiser
Keyword(s):  
Outpatient Treatment ◽  
Treatment Quality ◽  
Medical Decision ◽  
Case Based Reasoning ◽  
Treatment Processes ◽  
Valuable Treatment ◽  
New Treatment ◽  
Heath Care ◽  
Case Based

This chapter introduces a case based reasoning (CBR) system for customizing treatment processes. The CBR system enables the generating of inpatient and outpatient treatment processes and the supporting of e-services in heath care networks individually customized to the patients’ needs. According to the CBR paradigm, which solves problems based on past experience, the proposed system uses old treatment processes of similar former patients and modifies them for new patients. In general, CBR is an established and well suited artificial intelligence method to support medical decision making. However, CBR systems capable of planning treatment processes by adapting old treatment processes to fit new patients are rare. The aim of this system is to increase the treatment quality of the patient by providing physicians with valuable treatment propositions and to contribute to the development of medical CBR Systems by introducing procedures enabling the generating of new treatment processes by modifying former treatment processes.

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