A MACHINE LEARNING LINEAR REGRESSION MODEL TO PREDICT FUTURE GIANT PANDA POPULATION

Authors

  • Kumud Dave Student (B.Sc.), Guru Nanak Girls College, Udaipur, Rajasthan, India
  • Satyendra Barber Assistant Professor, Guru Nanak Girls College, Udaipur, Rajasthan, India
  • Pooja Verma Assistant Professor, Guru Nanak Girls College, Udaipur, Rajasthan, India

Keywords:

Conservation, Giant Panda, Machine Learning, Linear Regression, Deforestation

Abstract

Increasingly used as the insignia of China, the zaftig and enchanting Giant Panda lives on mountains of southwest China. The Giant Panda is on the WWF logo and is known as “National Treasure” in China. In this study, we predict the future Giant Panda population by using machine learning algorithms of the simple linear regression model. We take different variables to predict the next 30 years of the Giant Panda population. Focusing on the factors which affect the Giant Panda population. We take several parameters for this research like Bamboo Population, Annual Rainfall in China, Carbon Stock in Bamboo Stems, Deforestation, and Human Influence and Population of Giant Panda. Despite their peak status and relative deficiency of natural predators, pandas are still at risk and multiple intimidations from human influence have left just over 1,800 Pandas in the forest. To be ready for future troubles it is mandatory to have a pre-look of some conditions so that we can be prepared for that. Substantially, Endangered species at the edge of extinction are kept in extra special conservation. The machine learning algorithms developed with a wide-ranging of training datasets that help to find results faster and accurately.

References

Buchholz, K. (2019). Panda Population in the Wild Rebound. PANDA CONSERVATION. https://www.statista.com/chart/18740/panda-populatins-in-the-wild-and-in-captivity/

Lucas Gutierrez Rodriguez, (2014). From basic raw material goods to cultural and environmental services: the Chinese bamboo sophistication path. Ecology and Society 19(4): 3. https://www.researchgate.net/figure/Evolution-of-bamboo-total-area-in-china-National-Bureau-of-Statistics-of-china_fig1_267641764

Muhammad Tauseef, Lihua Chen, Kaipeng Yang, Yunyao Chen, (2020). “Long-Term Rainfall Trends and Future Projections over Xijiang River Basin, China”, Advances in Meteorology, vol. 2020, Article ID 6852148, 18 pages https://doi.org/10.1155/2020/6852148

Ritchie, H. & Rosser, M. (2021). “Forest and Deforestation”. Published online at OurWorldInData.org. Retrieved from: ‘https://ourworldindata.org/forests-and-deforestation’ [Online Resource] https://ourworldindata.org/deforestation

Thang Muoi mot, (2019). Line chart 3: Population growth and projection.http://fastlearn.edu.vn/2019/11/25/line-chart-3-population-growth-and-projection/

Xinzhuang Chen, G.U.O.M.O... Z.H.O.U. (2020). Changes of carbon stocks in bamboo stands in China during 100 years. Forest ecology and management 258(7):10. https://www.sciencedirect.com/science/article/abs/pii/SO378112709004745

Zhao, J. & Wang, Z. (2020). Future trend of water resources and influences in agriculture in China. https://www.researchgate.net/publication/340725955_Future_trends_of_water_resources_and_influences_on_agriculture_in_China

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Published

2021-11-17

How to Cite

Dave, K., Barber, S., & Verma, P. (2021). A MACHINE LEARNING LINEAR REGRESSION MODEL TO PREDICT FUTURE GIANT PANDA POPULATION. LIFE: International Journal of Health and Life-Sciences, 7(3), 13–20. Retrieved from https://grdspublishing.org/index.php/life/article/view/1894