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- W3089475624 abstract "Considering the multi-feature fusion via information synergy entropy (ISE) based interval intuitionistic fuzzy (IIF) technique for order preference by similarity to ideal solution, the paper propose a method to identify the operating condition identification in a complex environment. In this method, the evaluation information contained in the decision matrices is characterized by an IIF number, and the related attribute weights are incompletely known. First, the ISE concept is proposed to calculate the weight of each attribute value which is used to construct a weighted collective decision matrix. Both intuitionistic and fuzzy information are incorporated into the matrix to describe the uncertainty in the IIF sets to improve the decision accuracy. Next, an improved Euclidean distance is used to calculate the degree of relative closeness so as to rank the decision alternatives, which can overcome the drawback of division by zero. Then the superheat identification is used as a case study to illustrate optimal operating condition determination of aluminium electrolysis cell. Experimental results have demonstrated the validity and applicability of the proposed operating condition determination algorithm." @default.
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- W3089475624 date "2021-02-01" @default.
- W3089475624 modified "2023-10-16" @default.
- W3089475624 title "Information synergy entropy based multi-feature information fusion for the operating condition identification in aluminium electrolysis" @default.
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- W3089475624 doi "https://doi.org/10.1016/j.ins.2020.07.031" @default.
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