Systematic causal knowledge acquisition using FCM Constructor for product design decision support

Cheah, Wooi Ping; Kim, Yun Seon; Kim, Kyoung-Yun; Yang, Hyung-Jeong

doi:10.1016/j.eswa.2011.06.032

Cited by 35 publications

(18 citation statements)

References 21 publications

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“…Lee et al [29] proposed feedback-based FCM for feedback design in product problem and also indicated "feedback" applied into FCM evaluation. Cheah et al [12] proposed FCM constructor to verify product design decision making problems for modelling, representing, and reasoning about causal design knowledge [19]. According to the above-mentioned, the FCM was adopted to evaluating value of engineering design perspectives for product design process.…”

Section: Fuzzy Cognitive Mapsmentioning

confidence: 99%

Fuzzy dual experience-based design evaluation model for integrating engineering design into customer responses

Chen

2016

Int J Interact Des Manuf

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Experience-based design is a recently emerging method used to capture the emotional content of customer experiences. Both the engineer's experiences and customer's experiences for dual experiences are important in delivering high quality user-centred product design. To assess dual experiential design optimization, fuzzy decision tree and fuzzy cognitive map are integrated in engineering design perspectives. This study aims at optimizing complex interactions and experiential design system with imprecise relationships while quantifying the performance impact of engineering design efficiency on customer satisfaction. The experiment is conducted by utilizing sensitivity analysis of the three degrees of fuzzy membership function using a product mix-experience problem. The evaluation results show that this dual experience-based design approach can help R&D design, deliver high quality product development experiences and co-create value with customers to yield a high performance engineering design.

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Section: Fuzzy Cognitive Mapsmentioning

confidence: 99%

Fuzzy dual experience-based design evaluation model for integrating engineering design into customer responses

Chen

2016

Int J Interact Des Manuf

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“…The Fuzzy cognitive map uses experts' knowledge for modeling construction and has been implemented on the same case study problem of pneumonia severity (Papageorgiou, ). In a recent work, Cheah and his co‐workers () presented the advantages and limitations of FCMs and BNs and proposed an FCM‐BN conversion process. In their suggested methodology, BN were constructed by FCM that acquires knowledge from domain experts.…”

Section: Introductionmentioning

confidence: 99%

Bayesian network construction using a fuzzy rule based approach for medical decision support

2014

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This study proposes a novel method for the construction of efficient and convenient Bayesian networks (BNs) and influence diagrams regarding medical problems based on fuzzy rules. The general methodology that was developed is able to address decisions based on fuzzy medical rules that connect symptoms with the severity/rating scale of a disease. These fuzzy rules are rich enough to cover a large variety of medical decisions. The method overcomes the major disadvantage of Bayesian nets, that is, the need of a vast amount of subjective probabilities. Instead of filling conditional probability tables in BNs, physicians report their knowledge in the form of fuzzy rules. The knowledge of these rules after defuzzification is transformed according to certain equations into probabilities. This becomes possible, categorizing the rules into certain types. For each type of rule, a mathematical expression is determined, which sets correctly the conditional probabilities that relate a symptom with its child severity. A particular example of assessing pulmonary infections and making decisions on severity degree was explored, implementing a decision support system (DSS) to show the functionality of the proposed methodology. The developed front-end DSS was evaluated and proved capable to drive fair decisions close to those obtained by physicians.

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“…Although the usefulness of using neural networks and support machines has been reported in the literature, the obstacles are in model building and use of model in which the correlation between all the variables are difficulty to be inferred and understood. Recently, cognitive map [2] has been applied in many scientific areas, such as political science [3], organization and strategy planning [4] [5], analysis of business performance indicators [6], software project management [7], supply chain management [8]- [9], medical diagnosis [10]- [12], engineering design [13], etc. When a fuzzy cognitive map (FCM) has been constructed, it becomes a very usefully tool for supporting decision making [14].…”

Section: Introductionmentioning

confidence: 99%

Using FCM Based Hybrid Computational Approach for Diseases Diagnosis in Traditional Chinese Medicine

Chen¹,

You²,

Wu³

et al. 2014

IJMLC

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Abstract-Fuzzy cognitive map (FCM) belongs to one of the soft computing technique for modeling complex systems, which utilize the advantages from the synergistic theories of neural networks and fuzzy logic. The development of FCM highly relies on the human expert experience and knowledge. So, without those from expert(s), the FCM is hard to be constructed successfully. In this study, a self-adaptive FCM without any involvement of experts by using hybrid evolutionary computation approach is proposed. It includes the genetic algorithm (GA) and particle swarm optimization (PSO). The purpose of GA is to decide the significant variables. Based on those variables selected by GA, the most appropriate cognitive map can be constructed by PSO, i.e., the relationship matrix for the set of variables. The purpose of the research is to find the minimum subset of cognitive variables and the corresponding correlation matrix from historical numerical dataset so as to construct the optimal FCM decision model. In this study, the diagnosis of traditional Chinese medicines has been investigated base on twelve-meridian data obtained by meridian energy analysis device. The computational results show that the proposed approach is able to provide higher classification accuracy than those of the approaches in literature or by using commercial software.Index Terms-Fuzzy cognitive map, genetic algorithm, particle swarm optimization, traditional Chinese medicine, twelve-meridian. I. INTRODUCTIONTraditional Chinese medicine (TCM) has been one of the the primary forms of healthcare. Although Western medicine remains the mainstream of the healthcare system, TCM enjoys considerable popularity as a complementary form of healthcare to the Chinese population [1]. In TCM, the meridian energy analysis device (MEAD) is developed by medical experts to objectively measure and acquire the physiological data on the body meridian energy. The integration of the MEAD data with results from Western medical instruments (ex. hematological testing, endoscope, ultrasound, CI scanner and magnetic resonance imaging, etc.) is currently widely employed in TCM clinical practice in order to construct an objectively modern diagnosis. Manuscript received April 7, 2014; revised May 19, 2014. This work was supported in part by the National Science Council, Taiwan under Grant NSC 101-2221-E-150-058.T. In real world, the medical diagnosis is highly complicated in nature so that it's not easy to form a comprehensive model taking into account all the significant variables through the conventional statistical methods. Machine learning methods such as neural networks and support vector machines have been displayed to be with more dependable than other conventional approaches. Although the usefulness of using neural networks and support machines has been reported in the literature, the obstacles are in model building and use of model in which the correlation between all the variables are difficulty to be inferred and understood. Recently, cognitive map [2] When a fuzzy cognitiv...

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Systematic causal knowledge acquisition using FCM Constructor for product design decision support

Cited by 35 publications

References 21 publications

Fuzzy dual experience-based design evaluation model for integrating engineering design into customer responses

Fuzzy dual experience-based design evaluation model for integrating engineering design into customer responses

Bayesian network construction using a fuzzy rule based approach for medical decision support

Using FCM Based Hybrid Computational Approach for Diseases Diagnosis in Traditional Chinese Medicine

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