Abstract
This work presents a novel algorithm, the Mahalanobis Taguchi System- Two Step Optimal algorithm (MTS-TSO), which combines the Mahalanobis Taguchi System (MTS) and Two-Step Optimal (TSO) algorithm for parameter selection of product design, and parameter adjustment under the dynamic service industry environments.
From the results of the confirm experiment, a service industry company is adopted to applies in the methodology, we find that the methodology of the MTS-TSO algorithm can easily solves pattern-recognition problems, and is computationally efficient for constructing a model of a system. The MTS-TSO algorithm is good at pattern-recognition and model construction of a dynamic service industry company system.
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Hsu, TS., Huang, CL. (2010). Modeling a Dynamic Design System Using the Mahalanobis Taguchi System— Two-Step Optimal Algorithm. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6423. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16696-9_36
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DOI: https://doi.org/10.1007/978-3-642-16696-9_36
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