In this paper, we research on the research on the mass structured data storage and sorting algorithm and methodology for SQL database under the big data environment. With the data storage market development and center...In this paper, we research on the research on the mass structured data storage and sorting algorithm and methodology for SQL database under the big data environment. With the data storage market development and centering on the server, the data will store model to data- centric data storage model. Storage is considered from the start, just keep a series of data, for the management system and storage device rarely consider the intrinsic value of the stored data. The prosperity of the Internet has changed the world data storage, and with the emergence of many new applications. Theoretically, the proposed algorithm has the ability of dealing with massive data and numerically, the algorithm could enhance the processing accuracy and speed which will be meaningful.展开更多
With the development of economic globalization, people have higher and higher requirements for quality of life and service, and environmental pollution is one of the important issues, so big data of environmental prot...With the development of economic globalization, people have higher and higher requirements for quality of life and service, and environmental pollution is one of the important issues, so big data of environmental protection arises at the historic moment. The application of big data in environmental pollution control is a brand-new perspective. It can not only transform the traditional single and extensive management mode into an integrated mode of intensification and intelligence. Environmental big data can effectively reduce energy consumption and pollutant emissions by monitoring all aspects of enterprise production activities and realizing information sharing;But also can promote the improvement of the ecological environment and improve the efficiency of the ecological protection work.展开更多
The development of environmental information governance includes three phases: providing for oneself,information disclosure,and public service. And then China is in the transition and transformation of environmental i...The development of environmental information governance includes three phases: providing for oneself,information disclosure,and public service. And then China is in the transition and transformation of environmental information disclosure to the environmental information public service. The core of the transformation is public participation,in the whole procedure of environmental information supply decision making,production,and quality supervision and evaluation,etc. The target path of the environmental information governance reform includes five parts: improvement of public satisfaction,optimizing information disclosure,information quality control,integration of information resources,and multiple supply.展开更多
The year of 2011 is considered the first year of big data market in China.Compared with the global scale,China's big data growth will be faster than the global average growth rate,and China will usher in the rapid...The year of 2011 is considered the first year of big data market in China.Compared with the global scale,China's big data growth will be faster than the global average growth rate,and China will usher in the rapid expansion of big data market in the next few years.This paper presents the overall big data development in China in terms of market scale and development stages,enterprise development in the industry chain,the technology standards,and industrial applications.The paper points out the issues and challenges facing big data development in China and proposes to make polices and create support approaches for big data transactions and personal privacy protection.展开更多
This study aims to explore the application of Bayesian analysis based on neural networks and deep learning in data visualization.The research background is that with the increasing amount and complexity of data,tradit...This study aims to explore the application of Bayesian analysis based on neural networks and deep learning in data visualization.The research background is that with the increasing amount and complexity of data,traditional data analysis methods have been unable to meet the needs.Research methods include building neural networks and deep learning models,optimizing and improving them through Bayesian analysis,and applying them to the visualization of large-scale data sets.The results show that the neural network combined with Bayesian analysis and deep learning method can effectively improve the accuracy and efficiency of data visualization,and enhance the intuitiveness and depth of data interpretation.The significance of the research is that it provides a new solution for data visualization in the big data environment and helps to further promote the development and application of data science.展开更多
文摘In this paper, we research on the research on the mass structured data storage and sorting algorithm and methodology for SQL database under the big data environment. With the data storage market development and centering on the server, the data will store model to data- centric data storage model. Storage is considered from the start, just keep a series of data, for the management system and storage device rarely consider the intrinsic value of the stored data. The prosperity of the Internet has changed the world data storage, and with the emergence of many new applications. Theoretically, the proposed algorithm has the ability of dealing with massive data and numerically, the algorithm could enhance the processing accuracy and speed which will be meaningful.
文摘With the development of economic globalization, people have higher and higher requirements for quality of life and service, and environmental pollution is one of the important issues, so big data of environmental protection arises at the historic moment. The application of big data in environmental pollution control is a brand-new perspective. It can not only transform the traditional single and extensive management mode into an integrated mode of intensification and intelligence. Environmental big data can effectively reduce energy consumption and pollutant emissions by monitoring all aspects of enterprise production activities and realizing information sharing;But also can promote the improvement of the ecological environment and improve the efficiency of the ecological protection work.
文摘The development of environmental information governance includes three phases: providing for oneself,information disclosure,and public service. And then China is in the transition and transformation of environmental information disclosure to the environmental information public service. The core of the transformation is public participation,in the whole procedure of environmental information supply decision making,production,and quality supervision and evaluation,etc. The target path of the environmental information governance reform includes five parts: improvement of public satisfaction,optimizing information disclosure,information quality control,integration of information resources,and multiple supply.
文摘The year of 2011 is considered the first year of big data market in China.Compared with the global scale,China's big data growth will be faster than the global average growth rate,and China will usher in the rapid expansion of big data market in the next few years.This paper presents the overall big data development in China in terms of market scale and development stages,enterprise development in the industry chain,the technology standards,and industrial applications.The paper points out the issues and challenges facing big data development in China and proposes to make polices and create support approaches for big data transactions and personal privacy protection.
文摘This study aims to explore the application of Bayesian analysis based on neural networks and deep learning in data visualization.The research background is that with the increasing amount and complexity of data,traditional data analysis methods have been unable to meet the needs.Research methods include building neural networks and deep learning models,optimizing and improving them through Bayesian analysis,and applying them to the visualization of large-scale data sets.The results show that the neural network combined with Bayesian analysis and deep learning method can effectively improve the accuracy and efficiency of data visualization,and enhance the intuitiveness and depth of data interpretation.The significance of the research is that it provides a new solution for data visualization in the big data environment and helps to further promote the development and application of data science.
