Combining Numeric Method and Visualization Method Together to Analyze Big Data and the Prediction of the Rate of Accidental Death in China’s Coal Mining Industry
Yousuo Zou *
Computer Science Program, University of Guam, Mangilao, GU 96923, USA.
Steed J. Huang
Department of Systems and Computer Engineering, Carleton University, Ottawa, on K1S5B6, Canada.
Xin Luo
Computer Science Program, University of Guam, Mangilao, GU 96923, USA.
Anne Zou
Department of Computer Science, Vanderbilt University, Nashville, TN 37235, USA.
*Author to whom correspondence should be addressed.
Abstract
In this paper, we want to introduce an Enhanced Least Square method. We will utilize this method to analyze the given data, which is the number of deaths annual in colliery accidents in China in 2005-2018. And we will predict the future performance, offering an opinion about the current measures for safety precautions in coal industry. Analyzing the rules of the big data can not only help analyze the situation, but predict the trends, allowing an improvement of probability in decision making. In this research, we will use the Standard Total Deviation and Pearson Correlation Coefficient analysis methods to conduct the error analysis.
Keywords: Algorithm development, big data, SINC methods, nonlinear data pattern, accident death rate in coal mining
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