Published June 25, 2024
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Figure 2 in Forest yield prediction under different climate change scenarios using data intelligent models in Pakistan
Authors/Creators
- 1. University of Haripur, Department of Forestry and Wildlife Management, Khyber Pakhtunkhwa, Pakistan
- 2. COMSATS University Islamabad - CUI, Lahore Campus, Department of Economics, Lahore, Punjab, Pakistan
- 3. University of Baltistan, Department of Biological Sciences, Skardu, Gilgit-Baltistan, Pakistan
- 4. University of Sargodha, University College of Agriculture, Department of Forestry, Sargodha, Punjab, Pakistan
- 5. Jinnah University for Women, Department of Zoology, Nazimabad, Karachi, Sindh, Pakistan
- 6. University of Swat, Institute of Agriculture Sciences and Forestry, Khyber Pakhtunkhwa, Pakistan
- 7. Shaheed Benazir Bhutto University, Department of Environmental Sciences, Sheringal, Dir (U), KP, Pakistan
- 8. University of Haripur, Department of Psychology, Khyber Pakhtunkhwa, Pakistan
- 9. Planning, Agriculture Research System, Peshawar, Khyber Pakhtunkhwa, Pakistan
Description
Figure 2. Schematic view of Kernel Ridge Regression (KRR) model.
Notes
Published as part of Yousafzai, A., Manzoor, W., Raza, G., Mahmood, T., Rehman, F., Hadi, R., Shah, S., Amin, M., Akhtar, A., Bashir, S., Habiba, U. & Hussain, M., 2024, Forest yield prediction under different climate change scenarios using data intelligent models in Pakistan, pp. 1-20 in Brazilian Journal of Biology (e253106) 84 on page 4, DOI: 10.1590/1519-6984.253106, http://zenodo.org/record/11553147
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- Journal article: 10.1590/1519-6984.253106 (DOI)
- Journal article: urn:lsid:plazi.org:pub:FF8DFFD3FFC7FFB11A76FFF5BB58C77C (LSID)
- Journal article: https://zenodo.org/record/11553147 (URL)