An object-parameter approach to predicting unknown data in incomplete fuzzy soft sets

Deng, Tingquan; Wang, Xiaofei

doi:10.1016/j.apm.2012.09.010

Cited by 55 publications

(40 citation statements)

References 24 publications

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“…In this short paper, we point out the object-parameter method proposed in [1] is not always effective under some incomplete circumstances, sometimes, the predicted data obtained by this method are greater than one, this result does not satisfy what is required in the definition of membership degree of fuzzy sets.…”

Section: Introductionmentioning

confidence: 70%

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Comments on “An object-parameter approach to predicting unknown data in incomplete fuzzy soft sets” [Appl. Math. Modell. 37 (2013) 4139–4146]

Yang

Song

Peng

2015

Applied Mathematical Modelling

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Section: Introductionmentioning

confidence: 70%

“…(8) in [1]), where x 1 and x 2 stand for the weights of objects and parameters on the impacts on unknown data, respectively. …”

Section: Introductionmentioning

confidence: 99%

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Comments on “An object-parameter approach to predicting unknown data in incomplete fuzzy soft sets” [Appl. Math. Modell. 37 (2013) 4139–4146]

Yang

Song

Peng

2015

Applied Mathematical Modelling

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“…Different from some traditional mathematical tools, such as probability theory, fuzzy set theory, and rough set theory, to deal with uncertain data, a soft set model requires no prior knowledge of data-sets [25,69]. The fuzzy set was first proposed by Zadeh [67] to describe fuzzy phenomena under a specific attribute.…”

Section: Introductionmentioning

confidence: 99%

A novel general risk assessment method using the soft TOPSIS approach

Chang

2015

Journal of Industrial and Production Engineering

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Risk assessment is a systematic method of identifying and preventing product design and production planning process problems. It is a critical step in the risk management procedure. Most current risk assessment tools use failure mode, effects, and criticality analysis (FMECA) to evaluate the risk of failure. The traditional FMECA method uses linguistic terms to represent the severity, occurrence, and detection on a numerical scale from 1 to 10. It cannot deal with the incomplete information of attribute data. In a high technology industry, in order to meet the market's real demand and provide a suitable product, an original design manufacture (ODM) company offers customized design, production, and integration service to satisfied clients' needs. However, there are many uncertainties, imprecise, vague, and subjective information in the process of collecting data of an ODM company that will increase the difficulty of risk assessment. It cannot be fully solved by the traditional FMECA method. Therefore, considering both tangible and intangible criteria, this paper proposes a soft technique for order preference by similarity to ideal solution (TOPSIS) approach to solve the risk assessment problem. At last, a case study of ODM notebook module development is provided to demonstrate this practicability and rationality of the proposed method under incomplete information. Compared with existing traditional RPN and TOPSIS methods, the proposed method can deal with group decision-making problems in a more efficient manner.

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“…In recent years, soft set theory has drawn considerable attention [4][5][6][7][8]. By integrating soft set theory with other classical mathematical models, a lot of extensions of soft set model have also been made [9][10][11], fuzzy soft sets, generalized fuzzy soft sets [12], interval-valued fuzzy soft sets, vague soft sets [13], and intuitionistic fuzzy soft sets are all the models of soft set. At the same time, some approaches of decision making to these extended fuzzy soft sets have also been rendered.…”

Section: Introductionmentioning

confidence: 99%

The Application of Intuitionistic Fuzzy Soft Opeations to Medical Diagnosis

Zhang¹,

Gao²,

Gao³

2015

Proceedings of the 2015 International Conference on Education, Management, Information and Medicine

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Abstract. Molodtsov first proposed the soft set theory, which can be utilized as a general mathematical tool for dealing with fuzzy and uncertain information. As a generalization of soft set, intuitionistic fuzzy soft set is another soft set structure, it is a combination of an interval-valued fuzzy set and a soft set. The aim of this paper is to explore the decision making based on interval-valued fuzzy soft sets, the operations are carried out to integrate the medical information and expert information together, the optimcal choice is calculated to choose the disease which the patient most likely to suffer, a numberical example shows that the approach is reasonable..

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An object-parameter approach to predicting unknown data in incomplete fuzzy soft sets

Cited by 55 publications

References 24 publications

Comments on “An object-parameter approach to predicting unknown data in incomplete fuzzy soft sets” [Appl. Math. Modell. 37 (2013) 4139–4146]

Comments on “An object-parameter approach to predicting unknown data in incomplete fuzzy soft sets” [Appl. Math. Modell. 37 (2013) 4139–4146]

A novel general risk assessment method using the soft TOPSIS approach

The Application of Intuitionistic Fuzzy Soft Opeations to Medical Diagnosis

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