An application of multi-criteria decision aids models for Case-Based Reasoning

Armaghan, Negar; Renaud, Jean

doi:10.1016/j.ins.2012.04.033

Cited by 37 publications

(18 citation statements)

References 14 publications

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“…A metric has to be specific for an industry and an objective, but if there are different objectives to take into consideration to facilitate trade-offs between different points of view (disciplines, designers, services), the metric building process is the same for each metric, and a lot of multi-objective optimization techniques [48][49] [50], or techniques based on weighting considerations can be used to achieve an optimal global metric.…”

Section: Discussion and Future Workmentioning

confidence: 99%

Metrics Generation Process for Mechatronics

Warniez¹,

Penas²,

Choley³

et al. 2016

J. Robot. Mechatron.

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[abstFig src='/00280001/05.jpg' width=""300"" text='Metrics generation process overview' ]Due to the complexity of designing mechatronic systems, providers of these systems need to precisely evaluate their products, design processes and projects all along the design phase and beyond. We propose a metrics generation process and then define related specifications to develop an evaluation tool to build customized metrics for the mechatronic industry with respect to its specific process and expectations. The proposed process has been experimented on the modularity measure of two generations of vacuum cleaner robots.

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Section: Discussion and Future Workmentioning

confidence: 99%

Metrics Generation Process for Mechatronics

Warniez¹,

Penas²,

Choley³

et al. 2016

J. Robot. Mechatron.

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show abstract

“…In order to determine these concepts, we can search these concepts using FAST or, in the case the concepts does not sufficiently fit the specifications, case-based reasoning can be used to define these concepts [42] by adding an adapting step, so as to modify and combine concepts from a solution base to obtain a better concept. The second option relies on the development of new concepts in the conceptual design phase, using inventive design techniques, like the Theory for Inventive Problem Solving (TRIZ) [1].…”

Section: Step 21: Concept Definitionmentioning

confidence: 99%

An Optimization-Based Embodiment Design Approach for Mechatronic Product Development

Casner¹,

Houssin²,

Renaud³

et al. 2017

Open Autom. Control Syst. J.

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Abstract:Objective:This paper deals with the design and the optimization of mechatronic devices. Introduction:Comparing with existing works, the design approach presented in this paper aims to integrate optimization in the design phase of complex mechatronic systems in order to increase the efficiency of this method. Methods:To solve this problem, a novel mechatronic system design approach has been developed in order to take the multidisciplinary aspect and to consider optimization as a tool that can be used within the embodiment design process to build mechatronic solutions from a set of solution concepts designed with innovative or routine design methods. Conclusions:This approach has then been applied to the design and optimization of a wind turbine system that can be implemented to autonomously supply a mountain cottage.

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“…Li and Sun hybridized multi-criteria and CBR to enhance a data mining process for improving detection of disease [27]. Armaghan and Renaud used also combination of CBR and multi-criteria to study diabetes [5]. Angehrn and Dutta used also this combination to study diabetes [28].…”

Section: Combining Cbr With Other Approachesmentioning

confidence: 99%

“…After construction of case base Ω N , we subdivide it on a learning case base Ω L (80 % of Ω N ) and a test case base Ω T (20 % of Ω N ) by separating the population Ω N as follows in Table 3. Pelvic tilt X 3 Lumbar lordosis angle X 4 Sacral slope X 5 Pelvic radius X 6 Grade of spondylolisthesis Y Diagnosis Table 2 Ω …”

Section: Construction Of Case Base ω N and Partialmentioning

confidence: 99%

“…A major drawback is that if process found several similar cases and consequently several solutions which involve looking for a strategy to choose the best solution. Several works were conducted to overcome this drawbacks [2,[4][5][6][7][8] by using different strategies with the aim to impact positively the CBR process. In this work, we experiment collaboration between CBR and clustering.…”

Section: Introductionmentioning

confidence: 99%

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Clustering to Enhance Case-Based Reasoning

Mansoul

Atmani

2016

Modelling and Implementation of Complex Systems

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In this article, we propose an approach to improve CBR processing mainly in its retrieval task. A major difficulty arise when founding several similar cases and consequently several solutions, hence a choice must be done involving an appropriate strategy focusing the best solution. This main difficulty has a direct impact on the adaptation task. To overcome this limitation many works related to the retrieval task were conducted as hybridizing CBR with data mining methods. Through this study, we provide a combining approach using CBR and clustering to reduce the search space in the retrieval step. The objective is to consider only the most interesting cases and the most interesting solution to support decision and provide an intelligent strategy that enables decision makers to have the best decision aid. We also present some preliminary results and suggestions to extend our approach.

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An application of multi-criteria decision aids models for Case-Based Reasoning

Cited by 37 publications

References 14 publications

Metrics Generation Process for Mechatronics

Metrics Generation Process for Mechatronics

An Optimization-Based Embodiment Design Approach for Mechatronic Product Development

Clustering to Enhance Case-Based Reasoning

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