Abstract
This academic paper put forward the transformation formula and new similarity measure formula from single value data to vague data, and makes it the basis of vague integrative optimization evaluation methods. And make use of vague sets to optimize and evaluate four natural rubber species which planted widely in Hainan synthetically. Finally request to protect the natural rubber species of all kinds, breeding and promotion of new breed of high productivity and high resisting adversity property through science and technology innovation, and ultimately promote yield of natural rubber.
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References
Gau, W.L., Buehrer, D.J.: Vague sets. IEEE Transaction on Systems, Man, and Cybernetics 23(2), 610–614 (1993)
Zadeh, L.A.: Fuzzy sets. Information and Control (8), 338–356 (1965)
Hua-wen, L., Feng-ying, W.: Transformation and similarity measures of vague sets. Computer Engineering and Applications 40(32), 79–81, 84 (2004)
Zhen, Z., Qi-zong, W., Fu-xiang, L., Gui-xia, G.: New similarity measures on vague sets based on score function. Transactions of Beijing Institute of Technology 26(7), 655–658 (2006)
Hua-wen, L.: Similarity measures are basis of fuzzy pattern recognition. In: Pattern Recognition and Artificial Intelligence, Hefei, China, vol. 17(2), pp. 141–145 (2004)
South China Academy of Tropical Crops and Crops Genetic Resources Institute of CAAS: Germplasm resources investigation corpus of crops (plants) on Hainan island, pp. 39–47. China Agricultural Press, Beijing (1992)
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© 2010 Springer-Verlag Berlin Heidelberg
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Jun, J., Zhuang, L., Hongxu, W., Jianchun, G. (2010). Vague Sets Based Researches on Natural Rubber Species Optimization Evaluation. In: Cao, By., Wang, Gj., Guo, Sz., Chen, Sl. (eds) Fuzzy Information and Engineering 2010. Advances in Intelligent and Soft Computing, vol 78. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14880-4_48
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DOI: https://doi.org/10.1007/978-3-642-14880-4_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14879-8
Online ISBN: 978-3-642-14880-4
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