Prediction of Carbon Stock Available in Forest Using Naive Bayes Approach

Navjot Kaur Walia, Parul Kalra, D. Mehrotra
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引用次数: 8

Abstract

Carbon plays an essential role in the environment for climate change. The presence and absence of carbon directly affects all living beings. Trees inhale carbon for giving us oxygen. The environmental study of carbon is a major concern these days. Carbon Dioxide is stored in different five carbon pools of forest. Many countries are innolved in the research of environmental factors these days. The focus of this paper is to build a system using Naïve Bayes Approach that trains a model to classify forest on the basis of carbon stock and predict the level of carbon stock in the forest. The model is validated using dataset of the previous year data.
基于朴素贝叶斯方法的森林有效碳储量预测
碳在气候变化的环境中起着至关重要的作用。碳的存在与否直接影响到所有的生物。树木吸入碳为我们提供氧气。碳的环境研究是当今的一个主要问题。二氧化碳被储存在森林的五个不同的碳库中。目前,许多国家都在进行环境因素的研究。本文的重点是利用Naïve贝叶斯方法构建一个系统,该系统训练一个模型,根据碳储量对森林进行分类,并预测森林的碳储量水平。利用前一年的数据集对模型进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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