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書目名稱Granular, Soft and Fuzzy Approaches for Intelligent Systems影響因子(影響力)




書目名稱Granular, Soft and Fuzzy Approaches for Intelligent Systems影響因子(影響力)學(xué)科排名




書目名稱Granular, Soft and Fuzzy Approaches for Intelligent Systems網(wǎng)絡(luò)公開度




書目名稱Granular, Soft and Fuzzy Approaches for Intelligent Systems網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Granular, Soft and Fuzzy Approaches for Intelligent Systems被引頻次




書目名稱Granular, Soft and Fuzzy Approaches for Intelligent Systems被引頻次學(xué)科排名




書目名稱Granular, Soft and Fuzzy Approaches for Intelligent Systems年度引用




書目名稱Granular, Soft and Fuzzy Approaches for Intelligent Systems年度引用學(xué)科排名




書目名稱Granular, Soft and Fuzzy Approaches for Intelligent Systems讀者反饋




書目名稱Granular, Soft and Fuzzy Approaches for Intelligent Systems讀者反饋學(xué)科排名

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Evolving Possibilistic Fuzzy Modeling and?Application in Value-at-Risk Estimationmarket risk. Computational experiments are conducted to evaluate ePFM for value-at-risk estimation using data of the main equity market indexes of United States (S&P 500) and Brazil (Ibovespa) from January 2000 to December 2012. Econometric models benchmarks such as GARCH and EWMA, and state of the

Agronomy

Using Similarity and Dissimilarity Measures of Binary Patterns for the Comparison of Voting Procedurby the particular voting procedures are represented as binary vectors. We use the Jaccard–Needham, Dice, Correlation, Yule, Russell–Rao, Sockal–Michener, Rodgers–Tanimoto, and Kulczyński measures of similarity and dissimilarity. This makes it possible to gain much insight into the similarity/dissimi

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