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A Hybrid Approach to Tea Crop Yield Prediction Using Simulation Models and Machine Learning.
Batool, Dania; Shahbaz, Muhammad; Shahzad Asif, Hafiz; Shaukat, Kamran; Alam, Talha Mahboob; Hameed, Ibrahim A; Ramzan, Zeeshan; Waheed, Abdul; Aljuaid, Hanan; Luo, Suhuai.
Afiliação
  • Batool D; Department of Computer Engineering, University of Engineering and Technology, Lahore 58590, Pakistan.
  • Shahbaz M; Department of Computer Engineering, University of Engineering and Technology, Lahore 58590, Pakistan.
  • Shahzad Asif H; Department of Computer Science, New Campus, University of Engineering and Technology, Lahore 58590, Pakistan.
  • Shaukat K; School of Information and Physical Sciences, The University of Newcastle, Newcastle 2308, Australia.
  • Alam TM; Department of Data Science, University of the Punjab, Lahore 54890, Pakistan.
  • Hameed IA; Department of Computer Science and Information Technology, Virtual University of Pakistan, Lahore 58590, Pakistan.
  • Ramzan Z; Department of ICT and Natural Sciences, Norwegian University of Science and Technology, 7034 Trondheim, Norway.
  • Waheed A; Department of Computer Science, New Campus, University of Engineering and Technology, Lahore 58590, Pakistan.
  • Aljuaid H; National Tea and High-Value Crops Research Institute, Shinkiari, Mansehra 21300, Pakistan.
  • Luo S; Computer Sciences Department, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University (PNU), P.O. Box 84428, Riyadh 11671, Saudi Arabia.
Plants (Basel) ; 11(15)2022 Jul 25.
Article em En | MEDLINE | ID: mdl-35893629
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Plants (Basel) Ano de publicação: 2022 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Plants (Basel) Ano de publicação: 2022 Tipo de documento: Article