Home / Journals / CSSE / Vol.39, No.3, 2021
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    ARTICLE

    Flood Forecasting of Malaysia Kelantan River using Support Vector Regression Technique

    Amrul Faruq1, Aminaton Marto2, Shahrum Shah Abdullah3,*
    Computer Systems Science and Engineering, Vol.39, No.3, pp. 297-306, 2021, DOI:10.32604/csse.2021.017468
    Abstract The rainstorm is believed to contribute flood disasters in upstream catchments, resulting in further consequences in downstream area due to rise of river water levels. Forecasting for flood water level has been challenging, presenting complex task due to its nonlinearities and dependencies. This study proposes a support vector machine regression model, regarded as a powerful machine learning-based technique to forecast flood water levels in downstream area for different lead times. As a case study, Kelantan River in Malaysia has been selected to validate the proposed model. Four water level stations in river basin upstream were identified as input variables. A… More >

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    ARTICLE

    FREPD: A Robust Federated Learning Framework on Variational Autoencoder

    Zhipin Gu1, Liangzhong He2, Peiyan Li1, Peng Sun3, Jiangyong Shi1, Yuexiang Yang1,*
    Computer Systems Science and Engineering, Vol.39, No.3, pp. 307-320, 2021, DOI:10.32604/csse.2021.017969
    Abstract Federated learning is an ideal solution to the limitation of not preserving the users’ privacy information in edge computing. In federated learning, the cloud aggregates local model updates from the devices to generate a global model. To protect devices’ privacy, the cloud is designed to have no visibility into how these updates are generated, making detecting and defending malicious model updates a challenging task. Unlike existing works that struggle to tolerate adversarial attacks, the paper manages to exclude malicious updates from the global model’s aggregation. This paper focuses on Byzantine attack and backdoor attack in the federated learning setting. We… More >

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    ARTICLE

    Hybrid Sooty Tern Optimization and Differential Evolution for Feature Selection

    Heming Jia1,2,*, Yao Li2, Kangjian Sun2, Ning Cao1, Helen Min Zhou3
    Computer Systems Science and Engineering, Vol.39, No.3, pp. 321-335, 2021, DOI:10.32604/csse.2021.017536
    Abstract In this paper, a hybrid model based on sooty tern optimization algorithm (STOA) is proposed to optimize the parameters of the support vector machine (SVM) and identify the best feature sets simultaneously. Feature selection is an essential process of data preprocessing, and it aims to find the most relevant subset of features. In recent years, it has been applied in many practical domains of intelligent systems. The application of SVM in many fields has proved its effectiveness in classification tasks of various types. Its performance is mainly determined by the kernel type and its parameters. One of the most challenging… More >

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    ARTICLE

    Front-end Control Mechanism of Electronic Records

    Jiang Xu1, Ling Wang1,2, Xinyu Liu1,2, Xiujuan Feng3, Yongjun Ren1,2,*, Jinyue Xia4
    Computer Systems Science and Engineering, Vol.39, No.3, pp. 337-349, 2021, DOI:10.32604/csse.2021.015004
    Abstract In the digital era, how to ensure the authenticity and integrity of electronic records has become an open challenging issue. Front-end control is an important concept as well as a basic principle in electronic record management. Under the instruction of front-end control, many original management links in the record-management stage are required to move forward, and the managers enter the formation stage of the electronic records to ensure the originality. However, the front-end control technique primarily focuses on transaction management, and it lacks the strategy of providing the control of electronic records. In this paper, a novel electronic record front-end… More >

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    ARTICLE

    The Arcsine-X Family of Distributions with Applications to Financial Sciences

    Yen Liang Tung1, Zubair Ahmad2, Eisa Mahmoudi2,*
    Computer Systems Science and Engineering, Vol.39, No.3, pp. 351-363, 2021, DOI:10.32604/csse.2021.014270
    Abstract The heavy-tailed distributions are very useful and play a major role in actuary and financial management problems. Actuaries are often searching for such distributions to provide the best fit to financial and economic data sets. In the current study, a prominent method to generate new distributions useful for modeling heavy-tailed data is considered. The proposed family is introduced using trigonometric function and can be named as the Arcsine-X family of distributions. For the purposes of the demonstration, a specific sub-model of the proposed family, called the Arcsine-Weibull distribution is considered. The maximum likelihood estimation method is adopted for estimating the… More >

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    ARTICLE

    A Fire Escape Simulation System Based on the Dijkstra Algorithm

    Haolong Yang1, Chunqiang Hu1, Guwei Li2,*, Jingchun Fan3
    Computer Systems Science and Engineering, Vol.39, No.3, pp. 365-372, 2021, DOI:10.32604/csse.2021.016377
    Abstract Despite the support of all kinds of fire prevention measures and high-tech fire prevention equipment, fires still occur frequently because of both anthropogenic factors and natural disasters. This issue has drawn the attention of schools, all levels of government, and other organizations. Many types of organizations carry out fire drills throughout the year. Because this kind of drill cannot anticipate the specific circumstances of each fire, which are generally far more complicated than drills, most people cannot correctly choose the optimal escape route from real fires. Thus, a fire-scene virtual simulation system based on the Dijkstra algorithm is here proposed… More >

  • Open AccessOpen Access

    ARTICLE

    Semisupervised Encrypted Traffic Identification Based on Auxiliary Classification Generative Adversarial Network

    Jiaming Mao1,*, Mingming Zhang1, Mu Chen2, Lu Chen2, Fei Xia1, Lei Fan1, ZiXuan Wang3, Wenbing Zhao4
    Computer Systems Science and Engineering, Vol.39, No.3, pp. 373-390, 2021, DOI:10.32604/csse.2021.018086
    Abstract The rapidly increasing popularity of mobile devices has changed the methods with which people access various network services and increased network traffic markedly. Over the past few decades, network traffic identification has been a research hotspot in the field of network management and security monitoring. However, as more network services use encryption technology, network traffic identification faces many challenges. Although classic machine learning methods can solve many problems that cannot be solved by port- and payload-based methods, manually extract features that are frequently updated is time-consuming and labor-intensive. Deep learning has good automatic feature learning capabilities and is an ideal… More >

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    ARTICLE

    Impact of Financial Technology on Regional Green Finance

    Zheng Liu1, Juanjuan Song1, Hui Wu2,*, Xiaomin Gu2, Yuanjun Zhao3, Xiaoguang Yue4, Lihua Shi1
    Computer Systems Science and Engineering, Vol.39, No.3, pp. 391-401, 2021, DOI:10.32604/csse.2021.014527
    Abstract Finance is the core of modern economy, and a strong country cannot do without the support of financial system. With the rapid development of economy and society, the traditional financial services can not support the increasingly large and complex economic system. As a brand-new format, financial technology can help the financial industry to restructure and upgrade. At the same time, as an international consensus, green development is the only way for China to achieve sustainable development. Therefore, it is of great practical significance to study the impact of finance on the regional development of green finance. Based on the essence… More >

  • Open AccessOpen Access

    ARTICLE

    Model Implementation and Analysis of a True Three-dimensional Display System

    Ye Tian1,2, Yang Yang1,*, Han Yang3, Ze Ji4
    Computer Systems Science and Engineering, Vol.39, No.3, pp. 403-414, 2021, DOI:10.32604/csse.2021.016357
    Abstract To model a true three-dimensional (3D) display system, we introduced the method of voxel molding to obtain the stereoscopic imaging space of the system. For the distribution of each voxel, we proposed a four-dimensional (4D) Givone–Roessor (GR) model for state-space representation—that is, we established a local state-space model with the 3D position and one-dimensional time coordinates to describe the system. First, we extended the original elementary operation approach to a 4D condition and proposed the implementation steps of the realization matrix of the 4D GR model. Then, we described the working process of a true 3D display system, analyzed its… More >

  • Open AccessOpen Access

    ARTICLE

    Finding the Time-dependent Term in 2D Heat Equation from Nonlocal Integral Conditions

    M.J. Huntul*
    Computer Systems Science and Engineering, Vol.39, No.3, pp. 415-429, 2021, DOI:10.32604/csse.2021.017924
    Abstract The aim of this paper is to find the time-dependent term numerically in a two-dimensional heat equation using initial and Neumann boundary conditions and nonlocal integrals as over-determination conditions. This is a very interesting and challenging nonlinear inverse coefficient problem with important applications in various fields ranging from radioactive decay, melting or cooling processes, electronic chips, acoustics and geophysics to medicine. Unique solvability theorems of these inverse problems are supplied. However, since the problems are still ill-posed (a small modification in the input data can lead to bigger impact on the ultimate result in the output solution) the solution needs… More >

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