Establishing the relationship matrix in QFD based on fuzzy regression models with optimized \(h\) values
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Publication:1800321
DOI10.1007/s00500-017-2533-7zbMath1398.62205OpenAlexW2598357318MaRDI QIDQ1800321
Publication date: 23 October 2018
Published in: Soft Computing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00500-017-2533-7
fuzzy linear regressionquality function deploymentasymmetric triangular fuzzy numberoptimized \(h\) valuerelationship matrix
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Cites Work
- A systematic approach to optimizing \(h\) value for fuzzy linear regression with symmetric triangular fuzzy numbers
- Estimating the functional relationships for quality function deployment under uncertainties
- Multi-criteria decision making approaches for supplier evaluation and selection: a literature review
- Fuzzy versus statistical linear regression
- On assessing the \(H\) value in fuzzy linear regression
- Technical attributes ratings in fuzzy QFD by integrating interval-valued intuitionistic fuzzy sets and Choquet integral
- Fuzzy multicriteria models for quality function deployment
- Rating technical attributes in fuzzy QFD by integrating fuzzy weighted average method and fuzzy expected value operator
- A Fuzzy Quality Function Deployment (FQFD) model for deriving optimum targets
- Fuzzy expected value modelling approach for determining target values of engineering characteristics in QFD
- Linear Regression Analysis with Fuzzy Model
- An intelligent hybrid system for customer requirements analysis and product attribute targets determination
- Fuzzy regression-based mathematical programming model for quality function deployment
- Robot selection using an integrated approach based on quality function deployment and fuzzy regression
- Fuzzy regression using asymmetric fuzzy coefficients and fuzzified neural networks
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