Abstract
The experimental design can be generated by using the replicated measures of responses in multi-response experiments. In the modeling of this kind of designs, observed response values, which are obtained differently in each replication of the experiment, cannot be correctly represented with a single numerical quantity. In this case, it will be more proper to define a quantity which expresses the vagueness and complexity on the responses. Fuzzy numbers can be employed to represent the repeated responses. In this work, fuzzy modeling is performed by considering observed repeated response values as triangular fuzzy numbers in the case of the input values are crisp. Triangular fuzzy model parameters are estimated by using fuzzy least squares (FLS) method. The proposed fuzzy modeling approach is implemented on a data set defined in the literature.
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Türkşen, Ö., Apaydın, A. (2014). A Modeling Approach Based on Fuzzy Least Squares Method for Multi-Response Experiments with Replicated Measures. In: Banerjee, S., Erçetin, Ş. (eds) Chaos, Complexity and Leadership 2012. Springer Proceedings in Complexity. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7362-2_19
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DOI: https://doi.org/10.1007/978-94-007-7362-2_19
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