Case Based Reasoning: Case Representation Methodologies

El–Sappagh, Shaker; Elmogy, Mohammed

doi:10.14569/ijacsa.2015.061126

Cited by 14 publications

(2 citation statements)

References 83 publications

(72 reference statements)

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“…CBR cases are usually expressed in the form of binary eigenvectors, i.e., <problem description, solution description> [2] . The case set can be expressed as CaseSet = {C1, C2, C3, ……, Cn} [3] . The cases in the case set can be expressed as Ci = {Fi, Si}.…”

Section: Related Workmentioning

confidence: 99%

Adaptive method of process flow parameter values setting based on remote sensing image metadata

Zhou

Zuo

2023

International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022)

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Remote sensing data processing involves many steps. This paper uses process flow to represent these processing steps. This paper combines remote sensing image metadata (RSIM) with case based reasoning (CBR) technology, proposes a parameter value adaptive method based on RSIM, and constructs a remote RSIM case model. It makes the representation of RSIM more intuitive and convenient. This method consists of two parts: case building and case similarity measurement. Case building refers to building RSIM into RSIM cases according to case models, and then classifying and saving each case. Case similarity measurement refers to the similarity measurement of metadata in the production process and each case under the flow. Finally, the parameter values will be configured according to the highest similarity. The method is tested in an actual remote sensing production system, and the experimental results show that the method has good applicability in the parameter value adaptation of remote sensing process production.

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Section: Related Workmentioning

confidence: 99%

Adaptive method of process flow parameter values setting based on remote sensing image metadata

Zhou

Zuo

2023

International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022)

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“…Case representation is important in CBR as the rulebased reasoning capability of CBR depends primarily on the structure and content of cases (El-Sappagh & Elmogy, 2015). Cases can be diversely represented either in simple attributes vector, or complex object-oriented and tree representations (Richter & Weber, 2013).…”

Section: Case Representationmentioning

confidence: 99%

A Novel Decision-Making Model for Selecting a Construction Project Delivery System

Zhu

Meng

Chen

2020

Journal of Civil Engineering and Management

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It is crucial for the owner of a construction project to select an appropriate project delivery system (PDS) during early decision-making stages of the project. Due to project uncertainty or a lack of project information, the parameters of a PDS are difficult to measure and quantify. Therefore, there are still major challenges to the objective selection of PDSs. This research proposes a novel systematic decision-making model to select the appropriate PDS by using the combination of case-based reasoning (CBR) and robust nonparametric production frontier method. The Bayesian-Structural Equation Modeling (SEM) supported Z-order-m method is interpreted into the case retrieves process of traditional CBR method in order to eliminate the deteriorative internal and external influence for PDS selection. The case study was based on questionnaire survey conducted in China and used to test the validation of the proposed model. The findings reveal that the systematic decision-making model can overcome some problems of the traditional methods and improve the accuracy of PDS selection. As a result, this research has both theoretical and practical implications for the construction industry.

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