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All Journal Journal of Engineering and Technological Sciences IJIIS: International Journal of Informatics and Information Systems Journal of Applied Data Sciences
Fan Yang
Institute of Urban Construction, Hebei Normal University of Science & Technology, Qinhuangdao, Hebei Province, 066004,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering

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Skewed Pressure Characteristics of Equivalent Load in Double-Arch Tunnel Li, Chunliu; Wang, Shuren; Wang, Yongguang; Cui, Fang; Yang, Fan
Journal of Engineering and Technological Sciences Vol 48, No 3 (2016)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (569.036 KB) | DOI: 10.5614/j.eng.technol.sci.2016.48.3.8

Abstract

It is of great importance to reasonably estimate the surrounding rock load of a double-arch tunnel for the design, construction and stability evaluation of the tunnel. Currently, the basic theory on surrounding rock pressure of double-arch tunnels is insufficient for properly making the design and calculations. Generally, simplified calculations based on experience are used, such as the calculation method of Protodyakonov’s theory, the building code method and others. Considering the fact that the surrounding rock pressure of double-arch tunnels has skewed distribution characteristics, a computational model of a double-arch tunnel was built using data from an actual excavation of a highway tunnel. Taking some factors into consideration, such as different stress states, different construction methods and different sizes of double-arch tunnels, the pressure evolution of the surrounding rock was analyzed during step-by-step excavation of the double-arch tunnel. The results showed that in each condition the surrounding rock pressure of the double-arch tunnel displayed skewed distribution characteristics. The skewed distribution of the surrounding rock pressure varied with changes in stress state, construction sequence and excavation size. The skewed pressure of the double-arch tunnel was converted to equivalent load. The conversion method and distribution characteristics of the equivalent load are specified. They have important theoretical significance and practical value for similar engineering practices.
Software Defect Fault Intelligent Location and Identification Method Based on Data Mining Yang, Fan
International Journal of Informatics and Information Systems Vol 5, No 4: December 2022
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v5i4.105

Abstract

With the advancement of the times, computer technology is also constantly improving, and people's requirements for software functions are also constantly improving, and as software functions become more and more complex, developers are technically limited and teamwork is not tacitly coordinated. And so on, so in the software development process, some errors and problems will inevitably lead to software defects. The purpose of this paper is to study the intelligent location and identification methods of software defects based on data mining. This article first studies the domestic and foreign software defect fault intelligent location technology, analyzes the shortcomings of traditional software defect detection and fault detection, then introduces data mining technology in detail, and finally conducts in-depth research on software defect prediction technology. Through in-depth research on several technologies, it reduces the accidents of software equipment and delays its service life. According to the experiments in this article, the software defect location proposed in this article uses two methods to compare. The first error set is used as a unit to measure the subsequent error set software error location cost. The first error set 1F contains 19 A manually injected error program, and the average positioning cost obtained is 3.75%.
HTTP Traffic Analysis based on Multiple Deep Convolution Network Model Generation Algorithms Liu, Bocheng; Yang, Fan
Journal of Applied Data Sciences Vol 3, No 4: DECEMBER 2022
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v3i4.69

Abstract

In recent years, with the development of the Internet, social networking, online banking, e-commerce and other network applications are growing rapidly. At the same time, all kinds of malicious web pages are constantly emerging. Under the new situation, the network security threats are distributed, large-scale and complex. New network attack modes are emerging. With more and more diverse devices access to the Internet, our life is more intelligent and convenient, but also brings more loopholes and hidden dangers. Some malicious web pages through a variety of means to lure users to open URL links and conduct malicious behavior. However, if we can detect the URL of the malicious web page and identify the malicious web page, we can avoid the problems of content variability and behavior tracking. Therefore, traffic analysis based on various deep convolution network model generation algorithms arises at the historic moment, and becomes an important research issue in the field of Internet security.
Co-Authors Chunliu Li, Chunliu Fang Cui, Fang Liu, Bocheng Shuren Wang Yongguang Wang, Yongguang