Prediction of Carbon Stock Available in Forest using Naive Bayes Approach

被引：2
|
作者：
Walia, Navjot Kaur [1 ]
Kalra, Parul [1 ]
Mehrotra, Deepti [1 ]
机构：
[1] Amity Univ Uttar Pradesh, ASET, Noida, UP, India
来源：
2016 SECOND INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE & COMMUNICATION TECHNOLOGY (CICT) | 2016年
关键词：
Classification; Naive Bayesian Classifier; Carbon Stock; Above Ground Biomass; Below Ground Biomass; Litter; oil Organic Matter; Dead Wood;
D O I：
10.1109/CICT.2016.61
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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 Naive 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.
引用
收藏
页码：275 / 279
页数：5
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