Using fuzzy cognitive map for the relationship management in airline service

Inwon, Kang; Lee, Sangjae; Choi, Jiho

doi:10.1016/j.eswa.2003.10.012

Cited by 94 publications

(38 citation statements)

References 64 publications

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“…FCMs have been also used for modelling political and crisis situations and supporting the decision making process for the Cyprus issue (Mateou et al 2003). More recently, research reports for applying FCMs have been proposed to support the process esthetic analysis of urban areas (Xirogiannis et al 2004), and for the management of relationships among organizational members in airline service (Kang and Lee 2004). Summarizing, FCMs can contribute to the construction of more intelligent systems since a more intelligent a system becomes, the more symbolic and fuzzy representations it utilizes.…”

Section: Introductionmentioning

confidence: 99%

A weight adaptation method for fuzzy cognitive map learning

Papageorgiou

Groumpos

2005

Soft Comput

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Fuzzy cognitive maps (FCMs) constitute an attractive modeling approach that encompasses advantageous features. The most pronounces are the flexibility in system design, model and control, the comprehensive operation and the abstractive representation of complex systems. The main deficiencies of FCMs are the critical dependence on the initial expert's beliefs, the recalculation of the weights corresponding to each concept every time a new strategy is adopted and the potential convergence to undesired equilibrium states. In order to update the initial knowledge of human experts and to combine the human experts' structural knowledge with the training from data, a learning methodology for FCMs is proposed. This learning method, based on nonlinear Hebbian-type learning algorithm, is used to adapt the cause-effect relationships of the FCM model improving the efficiency and robustness of FCMs. A process control problem is presented and its process is investigated using the proposed weight adaptation technique.

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Section: Introductionmentioning

confidence: 99%

A weight adaptation method for fuzzy cognitive map learning

Papageorgiou

Groumpos

2005

Soft Comput

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“…For example, a threshold of (+/-0.5) implies that if the resulting value is greater than (+0.5) or lower than (-0.5) then the value is set to (+1) or (-1) respectively. FCMs have been used in many applications such as in modelling complex dynamic, which are characterized by strong non linearity [33], in personalised recommendations [17], [25], in managing relations in airline services [13], in systems modelling and decision making [14], in EDI design [18] and in EDI performance evaluation [19].…”

Section: Fuzzy Cognitive Mapsmentioning

confidence: 99%

An Approach to Hotel Services Dynamic Pricing Based on the Delphi Method and Fuzzy Cognitive Maps

Kardaras

Mamakou

Karakostas³

et al. 2013

IFIP Advances in Information and Communication Technology

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Abstract. E-tourism services open up new opportunities for businesses to expand and when possible to gain completive advantage. Dynamic pricing is an area of interest for both researchers and professionals. It's the process of price specification in a way that best suits a tourism organization under certain circumstances that reflect its competitive environment. Many research studies have addressed dynamic pricing from different perspectives. This study suggests that the use of a hybrid approach that combines Delphi method and fuzzy cognitive maps is suitable for it introduces fuzzy logic in order to capture the subjectivity and vagueness involved into evaluating the business settings, but it also provides for the necessary flexibility in analyzing the assumptions and the implications of different pricing scenarios.

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“…They are also important equipment for the road construction, water conservancy construction and farmland improvement, etc [3]. Product configuration is a kind of process that the model of product configuration is instantiated according to customer demands [4,5]. Whether the customer is satisfied with the instance of product configuration, it needs to establish the perfect evaluation model of product configuration to evaluate.…”

Section: Introductionmentioning

confidence: 99%

The Evaluation Model of Product Configuration Based on F-AHP

Wang¹,

Xi²,

Wu³

et al. 2018

dtcse

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Abstract.To help customers to estimate the result of product configuration during design, a new evaluation model was developed. Combining advantages of AHP and FCEM, the model took CSR as the goal, based on F-AHP. Dividing customer demands into different groups, the model had multiple structural layers. It took customer demands as target layers, evaluation indexes as criterion layers, and satisfactions as scheme layers. Triangular fuzzy membership function helped to define the relationship between the upper and lower level of structural layers. Then the method of weighted distance minimum integrated the weight of all experts for each criterion layer as the fuzzy weight of each layer. Linear weight integrated all expert evaluation. Finally, total utility of each evaluation was calculated from bottom to top, namely total satisfaction. So the maximum total utility was the evaluation result. Through analyzing the configuration result of grader, it verifies the feasibility of evaluation methods, and the rationality of the evaluation model.

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Using fuzzy cognitive map for the relationship management in airline service

Cited by 94 publications

References 64 publications

A weight adaptation method for fuzzy cognitive map learning

A weight adaptation method for fuzzy cognitive map learning

An Approach to Hotel Services Dynamic Pricing Based on the Delphi Method and Fuzzy Cognitive Maps

The Evaluation Model of Product Configuration Based on F-AHP

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