Mohammad Aldossary^*

Computer Systems Science and Engineering, Vol.36, No.2, pp. 353-368, 2021, DOI:10.32604/csse.2021.014974

Abstract With the expansion of cloud computing, optimizing the energy efficiency and cost of the cloud paradigm is considered significantly important, since it directly affects providers’ revenue and customers’ payment. Thus, providing prediction information of the cloud services can be very beneficial for the service providers, as they need to carefully predict their business growths and efficiently manage their resources. To optimize the use of cloud services, predictive mechanisms can be applied to improve resource utilization and reduce energy-related costs. However, such mechanisms need to be provided with energy awareness not only at the level of the Physical Machine (PM) but… More >

Mengcheng Sun^1,2, Weiya Xu^1,2,*, Huanling Wang^1,3, Qingxiang Meng^1,2, Long Yan^1,2, Wei-Chau Xie⁴

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 1057-1074, 2021, DOI:10.32604/cmc.2020.012537

Abstract The narrowing deformation of reservoir valley during the initial operation period threatens the long-term safety of the dam, and an accurate prediction of valley deformation (VD) remains a challenging part of risk mitigation. In order to enhance the accuracy of VD prediction, a novel hybrid model combining Ensemble empirical mode decomposition based interval threshold denoising (EEMD-ITD), Differential evolutions—Shuffled frog leaping algorithm (DE-SFLA) and Least squares support vector machine (LSSVM) is proposed. The non-stationary VD series is firstly decomposed into several stationary subseries by EEMD; then, ITD is applied for redundant information denoising on special sub-series, and the denoised deformation is… More >

Zhimin Zhang, Tianhe Kang^*

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 341-357, 2021, DOI:10.32604/cmc.2020.012104

Abstract In view of the three-dimensional dynamic abutment pressure, the influence of the far-field hard stratum (FHS) in deep, thick coal seams is indeterminant. Based on elastic foundation theory, a three-dimensional dynamic prediction model of the abutment pressure was established. Using this model, the dynamic change in the coal seam abutment pressure caused by the movement of the FHS was studied, and a method for determining the dynamic change range of the abutment pressure was developed. The results of the new prediction model of the abutment pressure are slightly higher than the measured values, with an error of 0.51%, which avoids… More >

Zhenhua Guo^1,2, Lixin Zhang^1,*, Xue Hu¹, Huanmei Chen²

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 625-630, 2020, DOI:10.32604/iasc.2020.013941

Abstract Wind speed prediction is an important part of the wind farm management and wind power grid connection. Having accurate prediction of short-term wind speed is the basis for predicting wind power. This paper proposes a short-term wind speed prediction strategy based on the wavelet analysis and the multilayer perceptual neural network for the Dabancheng area, in China. Four wavelet neural network models using the Morlet function as the wavelet basis function were developed to forecast short-term wind speed in January, April, July, and October. Predicted wind speed was compared across the four models using the mean square error and regression.… More >

Meng Wei^*, Ningxin Zhang, Yuan Tong, Yu Song

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 597-607, 2020, DOI:10.32604/iasc.2020.013938

Abstract The traditional radar signal detection mode of the analog digital converter (ADC) has a low prediction efficiency. Therefore, the advanced prediction model of the tunnel geological radar based on the cluster computing was designed. The completeness factor of the detection radar signal was calculated by the computer cluster effect, and then the information extraction and information integration of the radar pulse for the radar detection signal was determined. Moreover, the multi-order nonlinear regression forecasting model restructured the received signal. Thus, the prediction of the radar detection signal was achieved. In order to ensure the effectiveness of the design, the simulation… More >

Hui Li¹, Cailin Shi^{2, 3}, Xin Liu^{2, 3}, Aziguli Wulamu^{2, 3, *}, Alan Yang⁴

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 987-1004, 2020, DOI:10.32604/cmc.2020.09812

Abstract The difference in electricity and power usage time leads to an unbalanced current among the three phases in the power grid. The three-phase unbalanced is closely related to power planning and load distribution. When the unbalance occurs, the safe operation of the electrical equipment will be seriously jeopardized. This paper proposes a Hierarchical Temporal Memory (HTM)-based three-phase unbalance prediction model consisted by the encoder for binary coding, the spatial pooler for frequency pattern learning, the temporal pooler for pattern sequence learning, and the sparse distributed representations classifier for unbalance prediction. Following the feasibility of spatialtemporal streaming data analysis, we adopted… More >

Tongjing Liu^{1, 2, *}, Weixia Liu³, Pengxiang Diwu⁴, Gaixing Hu^{5, 6}, Ting Xu^{1, 7}, Yuqi Li², Zhenjiang You⁸, Runwei Qiao², Jia Wang²

CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.3, pp. 1205-1222, 2020, DOI:10.32604/cmes.2020.08961

Abstract Structure of porous media and fluid distribution in rocks can significantly affect the transport characteristics during the process of microscale tracer flow. To clarify the effect of micro heterogeneity on aqueous tracer transport, this paper demonstrates microscopic experiments at pore level and proposes an improved mathematical model for tracer transport. The visualization results show a faster tracer movement into movable water than it into bound water, and quicker occupancy in flowing pores than in storage pores caused by the difference of tracer velocity. Moreover, the proposed mathematical model includes the effects of bound water and flowing porosity by applying interstitial… More >

Nobuyuki Ishikawa^1,*, Yuya Sato¹, A. Toshimitsu Yokobori Jr.², Tadashi Kasuya³, Satoshi Minamoto⁴, Takehiro Endo³, Manabu Enoki³

The International Conference on Computational & Experimental Engineering and Sciences, Vol.22, No.2, pp. 138-138, 2019, DOI:10.32604/icces.2019.05518

Abstract Prediction model for weld hydrogen cracking (so called cold cracking) in high strength steel weld was developed by a coupled thermo-elastic-plastic and hydrogen diffusion analysis in the y-grooved weld joint. Critical conditions of cracking was given as the function of principal stress and accumulated hydrogen concentration in the root region where the cracking occurs. In order to clarify the critical conditions of cold cracking, y-grooved cold cracking tests were first conducted using the steel plate with tensile strength level of 780MPa. Plate thickness of the plates were 25 mm and 50 mm. Hydrogen concentration in the weld metal was changed… More >

Satoshi Minamoto*, Takuya Kadohira, Kaita Ito, Makoto Watanabe, Masahiko Demura

The International Conference on Computational & Experimental Engineering and Sciences, Vol.22, No.2, pp. 136-136, 2019, DOI:10.32604/icces.2019.05447

Abstract The Materials Integration (MI) System is a domestically developed system in the “Cross-ministerial Strategic Innovation Promotion Program” to analyze structural materials performance. The performance on structural materials having complicated inputs/outputs would be solved with the combination of different scientific programs or data from experiment. One of the merits of constructing a combined model (here we call workflow) is that calculations are performed and the data would be stored in the system automatically.
Furthermore, we developed a web application (“MIREA”: MI REgression Analyzer) that enables us to build high versatile prediction models based on machine learning techniques by using the… More >

Sifan Long¹, Ming Zhao^2,*, Xinfu He³

CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 727-760, 2019, DOI:10.32604/cmc.2019.04454

Abstract With the development of society and the exhaustion of fossil energy, researcher need to identify new alternative energy sources. Nuclear energy is a very good choice, but the key to the successful application of nuclear technology is determined primarily by the behavior of nuclear materials in reactors. Therefore, we studied the radiation performance of the fusion material reduced activation ferritic/martensitic (RAFM) steel. The main novelty of this paper are the statistical analysis of RAFM steel data sets through related statistical analysis and the formula derivation of the gradient descent method (GDM) which combines the gradient descent search strategy of the… More >