Estimation Of Perceptible Water Vapor Of Atmosphere Using Artificial Neural Network, Support Vector Machine And Multiple Linear Regression Algorithm And Their Comparative Study

被引：0
|
作者：
Shastri, Niket [1 ]
Pathak, Kamlesh [2 ]
机构：
[1] Sarvajnik Coll Engn & Technol, Dept Phys, Surat, Gujarat, India
[2] Sardar Vallabhbhai Inst Technol, Dept Phys, Surat, Gujarat, India
来源：
2ND INTERNATIONAL CONFERENCE ON CONDENSED MATTER AND APPLIED PHYSICS (ICC-2017) | 2018年 / 1953卷
关键词：
D O I：
10.1063/1.5033289
中图分类号：
O59 [应用物理学];
学科分类号：
摘要：
The water vapor content in atmosphere plays very important role in climate. In this paper the application of GPS signal in meteorology is discussed, which is useful technique that is used to estimate the perceptible water vapor of atmosphere. In this paper various algorithms like artificial neural network, support vector machine and multiple linear regression are use to predict perceptible water vapor. The comparative studies in terms of root mean square error and mean absolute errors are also carried out for all the algorithms.
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页数：4
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