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The Scientific World Journal
Volume 2014, Article ID 509429, 10 pages
http://dx.doi.org/10.1155/2014/509429
Review Article

Attribute Selection Impact on Linear and Nonlinear Regression Models for Crop Yield Prediction

1IMTA, Boulevard Cuauhnáhuac 8532, Colonia Progreso, 62550 Jiutepec, MOR, Mexico
2UPEMOR, Boulevard Cuauhnáhuac 566, Colonia Lomas del Texcal, 62550 Jiutepec, MOR, Mexico

Received 6 December 2013; Accepted 10 February 2014; Published 26 May 2014

Academic Editors: S. Balochian and Y. Zhang

Copyright © 2014 Alberto Gonzalez-Sanchez et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [5 citations]

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  • Yared Assefa, Mark Hinds, Gaurav Bhalla, Mark Jeschke, Vara Prasad, Paul Carter, Ryan Schon, Steve Paszkiewicz, and Ignacio A. Ciampitti, “Yield responses to planting density for US modern corn hybrids: A synthesis-analysis,” Crop Science, vol. 56, no. 5, pp. 2802–2817, 2016. View at Publisher · View at Google Scholar
  • Maryam Mokhtarzad, Farzad Eskandari, Nima Jamshidi Vanjani, and Alireza Arabasadi, “Drought forecasting by ANN, ANFIS, and SVM and comparison of the models,” Environmental Earth Sciences, vol. 76, no. 21, 2017. View at Publisher · View at Google Scholar
  • Reyhaneh Loni, E. Askari Asli-Ardeh, B. Ghobadian, M.H. Ahmadi, and Evangelos Bellos, “GMDH modeling and experimental investigation of thermal performance enhancement of hemispherical cavity receiver using MWCNT/oil nanofluid,” Solar Energy, vol. 171, pp. 790–803, 2018. View at Publisher · View at Google Scholar
  • Phusanisa Charoen-Ung, and Pradit Mittrapiyanuruk, “Sugarcane Yield Grade Prediction Using Random Forest with Forward Feature Selection and Hyper-parameter Tuning,” Recent Advances in Information and Communication Technology 2018, vol. 769, pp. 33–42, 2018. View at Publisher · View at Google Scholar