Zaobao Liu^1,2, Weiya Xu¹, Jianfu Shao²

CMES-Computer Modeling in Engineering & Sciences, Vol.84, No.2, pp. 99-122, 2012, DOI:10.3970/cmes.2012.084.099

Abstract In this paper, the Gauss process is proposed for application on landslide displacement analysis and prediction with dynamic crossing validation. The prediction problem using noisy observations is first introduced. Then the Gauss process method is proposed for modeling non-stationary series of landslide displacements based on its ability to model noisy data. The monitoring displacement series of the New Wolong Temple Landslide is comparatively studied with other methods as an instance to implement the strategy of the Gauss process for predicting landslide displacement. The dynamic crossing validation method is adopted to manage the displacement series so as to give more precise… More >

Lianggui Liu^1,*, Wei Li¹, Huiling Jia¹

CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 97-106, 2018, DOI:10.32604/cmc.2018.03511

Abstract With the rapid development of mobile communication all over the world, the similarity of mobile phone communication data has received widely attention due to its advantage for the construction of smart cities. Mobile phone communication data can be regarded as a type of time series and dynamic time warping (DTW) and derivative dynamic time warping (DDTW) are usually used to analyze the similarity of these data. However, many traditional methods only calculate the distance between time series while neglecting the shape characteristics of time series. In this paper, a novel hybrid method based on the combination of dynamic time warping… More >

Jieren Cheng^1,2, Ruomeng Xu^1,*, Xiangyan Tang¹, Victor S. Sheng³, Canting Cai¹

CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 95-119, 2018, DOI:10.3970/cmc.2018.055.095

Abstract Distributed denial-of-service (DDoS) is a rapidly growing problem with the fast development of the Internet. There are multitude DDoS detection approaches, however, three major problems about DDoS attack detection appear in the big data environment. Firstly, to shorten the respond time of the DDoS attack detector; secondly, to reduce the required compute resources; lastly, to achieve a high detection rate with low false alarm rate. In the paper, we propose an abnormal network flow feature sequence prediction approach which could fit to be used as a DDoS attack detector in the big data environment and solve aforementioned problems. We define… More >

B. Wang¹, H.Q. Zhang¹, C.K. Chan², X.L. Wang¹

CMC-Computers, Materials & Continua, Vol.1, No.3, pp. 275-288, 2004, DOI:10.3970/cmc.2004.001.275

Abstract Dilute gas-particle turbulent flow over a backward-facing step is numerically simulated. Large Eddy Simulation (LES) is used for the continuous phase and a Lagrangian trajectory method is adopted for the particle phase. Four typical locations in the flow field are chosen to investigate the two-phase velocity fluctuations. Time-series velocities of the gas phase with particles of different sizes are obtained. Velocity of the small particles is found to be similar to that of the gas phase, while high frequency noise exists in the velocity of the large particles. While the mean and rms velocities of the gas phase and small… More >