scholarly journals Construction of Ecological Environment Information System Based on Big Data: A Case Study on Dongting Lake Ecological Area

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Diandi Wan ◽  
Shaohua Yin

With the rapid development of cloud computing, Internet of Things, and other technologies, the information technology trend led by “big data” has an impact on all fields. The application of big data technology in the field of ecological environmental protection enables accurate and comprehensive ecological information collection, data analysis, and mining, accurate ecological problem identification, and effective solution. Taking Dongting Lake Ecological Area as an example, this paper constructs an ecological environment information system based on big data and expounds its specific application in water, atmosphere, soil environment monitoring, and pollution control, aiming to provide a reference for the application of big data technology in the field of ecological environment protection in Dongting Lake Ecological Area and more effectively maintain the ecological environmental quality and safety in the area.

2018 ◽  
Vol 10 (10) ◽  
pp. 3778 ◽  
Author(s):  
Dong-Hui Jin ◽  
Hyun-Jung Kim

Efficient decision making based on business intelligence (BI) is essential to ensure competitiveness for sustainable growth. The rapid development of information and communication technology has made collection and analysis of big data essential, resulting in a considerable increase in academic studies on big data and big data analysis (BDA). However, many of these studies are not linked to BI, as companies do not understand and utilize the concepts in an integrated way. Therefore, the purpose of this study is twofold. First, we review the literature on BI, big data, and BDA to show that they are not separate methods but an integrated decision support system. Second, we explore how businesses use big data and BDA practically in conjunction with BI through a case study of sorting and logistics processing of a typical courier enterprise. We focus on the company’s cost efficiency as regards to data collection, data analysis/simulation, and the results from actual application. Our findings may enable companies to achieve management efficiency by utilizing big data through efficient BI without investing in additional infrastructure. It could also give them indirect experience, thereby reducing trial and error in order to maintain or increase competitiveness.


2019 ◽  
Vol 3 (2) ◽  
pp. 152
Author(s):  
Xianglan Wu

<p>In today's society, the rise of the Internet and rapid development make every day produce a huge amount of data. Therefore, the traditional data processing mode and data storage can not be fully analyzed and mined these data. More and more new information technologies (such as cloud computing, virtualization and big data, etc.) have emerged and been applied, the network has turned from informationization to intelligence, and campus construction has ushered in the stage of smart campus construction.The construction of intelligent campus refers to big data and cloud computing technology, which improves the informatization service quality of colleges and universities by integrating, storing and mining huge data.</p>


2012 ◽  
Vol 253-255 ◽  
pp. 840-843
Author(s):  
Xue Fei Liu ◽  
Ning Wang ◽  
Zhi Guang Wu

With the rapid development of new rural construction, rural areas have been changed enormously. At the same time, the ecological environment of rural areas has suffered a lot, especially, for the water environment and the rural landscape. In this paper, Yansaihu greenway planning of Qinhuangdao City has been used as an example, to demonstrate how to combine the nature, the Yansaihu water, the fields, and the rural areas in series by means of the greenway planning. While using and protecting Yansaihu natural landscape, it promotes agricultural leisure industry and extends the historical and cultural context, protects water resources in the ecological environment, and promotes the purpose of harmonization of nature, landscapes, farmland, and rural landscape, in order to achieve both of the rural environment and ecology landscape as well as rural economic development.


2019 ◽  
Vol 2 (4) ◽  
pp. 70-77
Author(s):  
Zhukovskaya Irina Evgenievna

This article discusses the modern aspects of the application of information and communication technologies (ICT) in the management of the statistical industry of the Republic of Uzbekistan. The article shows that at present, ICTs are an important factor in the development of industries and spheres of the national economy. An information system has been formed in the statistical industry, which is currently being transformed under the influence of advanced technological solutions, including big data technology, which contributes to the competent adoption of managerial decisions and the effective functioning of the industry in the economic market.


2020 ◽  
Vol 2 (2) ◽  
pp. 42
Author(s):  
Xingrui Wang

<p>With the rapid development of smart phones and communication technology, the frequency of communication between the public and society through telecommunication equipment is increasing. At the same time, some lawless elements often cheat the public through telecommunication equipment, which brings irreparable economic losses to the society and the masses to a certain extent. In view of the above problems, this article takes the source of telecommunication fraud as the breakthrough point, analyzes the existing telecommunication fraud processing technology and points out its shortcomings, and then proposes a method of telephone fraud analysis based on big data technology. This technology fills the defects of the existing telecommunication interception technology and provides a new idea for effectively avoiding telecommunication fraud in the future.</p>


Author(s):  
Balasree K ◽  
Dharmarajan K

In rapid development of Big Data technology over the recent years, this paper discussing about the Machine Learning (ML) playing role that is based on methods and algorithms to Big Data Processing and Big Data Analytics. In evolutionary fields and computing fields of developments that both are complementing each other. Big Data: The rapid growth of such data solutions needed to be studied and provided to handle then to gain the knowledge from datasets and extracting values due to the data sets are very high in velocity and variety. The Big data analytics are involving and indicating the appropriate data storage and computational outline that enhanced by using Scalable Machine Learning Algorithms and Big Data Analytics then the analytics to reveal the massive amounts of hidden data’s and secret correlations. This type of Analytic information useful for organizations and companies to gain deeper knowledge, development and getting advantages over the competition. When using this Analytics we can predict the accurate implementation over the data. This paper presented about the detailed review of state-of-the-art developments and overview of advantages and challenges in Machine Learning Algorithms over big data analytics.


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