Application of machine learning and genetic optimization algorithms for modeling and optimizing soybean yield using its component traits.
作者： Mohsen Yoosefzadeh-Najafabadi , Dan Tulpan , Milad Eskandari
DOI: 10.1371/JOURNAL.PONE.0250665
关键词:
摘要: … in the number of pods per plant [81–84]. A negative correlation between the total soybean seed yield … It is in agreement with previous studies claimed that increasing the number of non-…
sci-hub.st 参考文章(107)
Yanjun Qi, Random Forest for Bioinformatics Springer, Boston, MA. pp. 307- 323 ,(2012) , 10.1007/978-1-4419-9326-7_11
Susan R. Homack, Understanding What ANOVA Post Hoc Tests Are, Really. ,(2001)
Matthew Wiener, Andy Liaw, Classification and Regression by randomForest ,(2007)
Kjell Johnson, Max Kuhn, Applied Predictive Modeling ,(2013)
Thomas G. Dietterich, Ensemble Methods in Machine Learning Multiple Classifier Systems. pp. 1- 15 ,(2000) , 10.1007/3-540-45014-9_1
A. E. Slinkard, M. B. Solh, A. Vandenberg, Breeding for yield: The direct approach Linking research and marketing opportunities for pulses in the 21st Century. Proceedings of the Third International Food Legumes Research Conference, Adelaide, Australia, 22-26 September 1997.. pp. 183- 190 ,(2000) , 10.1007/978-94-011-4385-1_16
John H. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence Ann Arbor: University of Michigan Press. ,(1992) , 10.7551/MITPRESS/1090.001.0001
Bastian Siegmann, Thomas Jarmer, Comparison of different regression models and validation techniques for the assessment of wheat leaf area index from hyperspectral data Journal of remote sensing. ,vol. 36, pp. 4519- 4534 ,(2015) , 10.1080/01431161.2015.1084438
J. E. Specht, D. J. Hume, S. V. Kumudini, Soybean yield potential: A genetic and physiological perspective Crop Science. ,vol. 39, pp. 1560- 1570 ,(1999) , 10.2135/CROPSCI1999.3961560X
John R. Taylor, William Thompson, An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements Physics Today. ,vol. 51, pp. 57- 58 ,(1998) , 10.1063/1.882103