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  • Open Access


    CEMA-LSTM: Enhancing Contextual Feature Correlation for Radar Extrapolation Using Fine-Grained Echo Datasets

    Zhiyun Yang1,#, Qi Liu1,#,*, Hao Wu1, Xiaodong Liu2, Yonghong Zhang3

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 45-64, 2023, DOI:10.32604/cmes.2022.022045

    Abstract Accurate precipitation nowcasting can provide great convenience to the public so they can conduct corresponding arrangements in advance to deal with the possible impact of upcoming heavy rain. Recent relevant research activities have shown their concerns on various deep learning models for radar echo extrapolation, where radar echo maps were used to predict their consequent moment, so as to recognize potential severe convective weather events. However, these approaches suffer from an inaccurate prediction of echo dynamics and unreliable depiction of echo aggregation or dissipation, due to the size limitation of convolution filter, lack of global… More > Graphic Abstract

    CEMA-LSTM: Enhancing Contextual Feature Correlation for Radar Extrapolation Using Fine-Grained Echo Datasets

  • Open Access


    A Novel Method for Precipitation Nowcasting Based on ST-LSTM

    Wei Fang1,2,*, Liang Shen1, Victor S. Sheng3, Qiongying Xue1

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4867-4877, 2022, DOI:10.32604/cmc.2022.027197

    Abstract Precipitation nowcasting is of great significance for severe convective weather warnings. Radar echo extrapolation is a commonly used precipitation nowcasting method. However, the traditional radar echo extrapolation methods are encountered with the dilemma of low prediction accuracy and extrapolation ambiguity. The reason is that those methods cannot retain important long-term information and fail to capture short-term motion information from the long-range data stream. In order to solve the above problems, we select the spatiotemporal long short-term memory (ST-LSTM) as the recurrent unit of the model and integrate the 3D convolution operation in it to strengthen… More >

  • Open Access


    High Order of Accuracy for Poisson Equation Obtained by Grouping of Repeated Richardson Extrapolation with Fourth Order Schemes

    Luciano Pereira da Silva1,*, Bruno Benato Rutyna1, Aline Roberta Santos Righi2, Marcio Augusto Villela Pinto3

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 699-715, 2021, DOI:10.32604/cmes.2021.014239

    Abstract In this article, we improve the order of precision of the two-dimensional Poisson equation by combining extrapolation techniques with high order schemes. The high order solutions obtained traditionally generate non-sparse matrices and the calculation time is very high. We can obtain sparse matrices by applying compact schemes. In this article, we compare compact and exponential finite difference schemes of fourth order. The numerical solutions are calculated in quadruple precision (Real * 16 or extended precision) in FORTRAN language, and iteratively obtained until reaching the round-off error magnitude around 1.0E −32. This procedure is performed to ensure More >

  • Open Access


    Maximum Probabilistic and Dynamic Traffic Load Effects on Short-to-Medium Span Bridges

    Naiwei Lu1,*, Honghao Wang1, Kai Wang1, Yang Liu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.1, pp. 345-360, 2021, DOI:10.32604/cmes.2021.013792

    Abstract The steadily growing traffic load has resulted in lots of bridge collapse events over the past decades, especially for short-to-medium span bridges. This study investigated probabilistic and dynamic traffic load effects on short-to-medium span bridges using practical heavy traffic data in China. Mathematical formulations for traffic-bridge coupled vibration and probabilistic extrapolation were derived. A framework for extrapolating probabilistic and dynamic traffic load effect was presented to conduct an efficient and accurate extrapolation. An equivalent dynamic wheel load model was demonstrated to be feasible for short-to-medium span bridges. Numerical studies of two types of simply-supported bridges… More >

  • Open Access


    Extrapolation for Aeroengine Gas Path Faults with SVM Bases on Genetic Algorithm

    Yixiong Yu*

    Sound & Vibration, Vol.53, No.5, pp. 237-243, 2019, DOI:10.32604/sv.2019.07887

    Abstract Mining aeroengine operational data and developing fault diagnosis models for aeroengines are to avoid running aeroengines under undesired conditions. Because of the complexity of working environment and faults of aeroengines, it is unavoidable that the monitored parameters vary widely and possess larger noise levels. This paper reports the extrapolation of a diagnosis model for 20 gas path faults of a double-spool turbofan civil aeroengine. By applying support vector machine (SVM) algorithm together with genetic algorithm (GA), the fault diagnosis model is obtained from the training set that was based on the deviations of the monitored More >

  • Open Access


    Extrapolation Method for Cauchy Principal Value Integral with Classical Rectangle Rule on Interval

    Maohui Xia1, Jin Li*,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.115, No.3, pp. 313-326, 2018, DOI:10.3970/cmes.2018.08053

    Abstract In this paper, the classical composite middle rectangle rule for the computation of Cauchy principal value integral (the singular kernel 1/(x-s)) is discussed. With the density function approximated only while the singular kernel is calculated analysis, then the error functional of asymptotic expansion is obtained. We construct a series to approach the singular point. An extrapolation algorithm is presented and the convergence rate of extrapolation algorithm is proved. At last, some numerical results are presented to confirm the theoretical results and show the efficiency of the algorithms. More >

  • Open Access


    Multicriterion statistical extrapolation for a preset prediction in performance sport

    Emil Budescu1, Mircea Stefanovici2, Ioan Iacob3

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.11, No.3, pp. 84-84, 2009, DOI:10.3970/icces.2009.011.084

    Abstract The present paper presents the issues related to the dynamic series adjustment in order to determine the probability to reach preset values of performance, in the stated period of time and of known statistical chronological series. So, with trend functions, one can approximate the variation tendency in time of the sportive performance parameter, the difficulty being, though, the weight of each dynamic series of statistical data in the probability evaluation of performance. Each dynamic series represents values of the physical and physical tests monitored over a training phase, so over a stated period of time.… More >

  • Open Access


    Richardson Extrapolation Method for Singularly Perturbed Convection-Diffusion Problems on Adaptively Generated Mesh

    Pratibhamoy Das1, Srinivasan Natesan2

    CMES-Computer Modeling in Engineering & Sciences, Vol.90, No.6, pp. 463-485, 2013, DOI:10.3970/cmes.2013.090.463

    Abstract Adaptive mesh generation has become a valuable tool for the improvements of accuracy and efficiency of numerical solutions over fixed number of meshes. This paper gives an interpretation of the concept of equidistribution for singularly perturbed problems to obtain higher-order accuracy. We have used the post-processing Richardson extrapolation technique to improve the accuracy of the parameter uniform computed solution, obtained on a mesh which is adaptively generated by equidistributing a monitor function. Numerical examples demonstrate the high quality behavior of the computed solution. More >

  • Open Access


    The Application of a Hybrid Inverse Boundary Element Problem Engine for the Solution of Potential Problems

    S. Noroozi1, P. Sewell1, J. Vinney1

    CMES-Computer Modeling in Engineering & Sciences, Vol.14, No.3, pp. 171-180, 2006, DOI:10.3970/cmes.2006.014.171

    Abstract A method that combines a modified back propagation Artificial Neural Network (ANN) and Boundary Element Analysis (BEA) was introduced and discussed in the author's previous papers. This paper discusses the development of an automated inverse boundary element problem engine. This inverse problem engine can be applied to both potential and elastostatic problems.
    In this study, BEA solutions of a two-dimensional potential problem is utilised to test the system and to train a back propagation Artificial Neural Network (ANN). Once training is completed and the transfer function is created, the solution to any subsequent or new… More >

  • Open Access


    Generalized Extrapolation for Computation of Hypersingular Integrals in Boundary Element Methods

    Jin Li1, Ji-ming Wu2, De-hao Yu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.42, No.2, pp. 151-176, 2009, DOI:10.3970/cmes.2009.042.151

    Abstract The trapezoidal rule for the computation of Hadamard finite-part integrals in boundary element methods is discussed, and the asymptotic expansion of error function is obtained. A series to approach the singular point is constructed and the convergence rate is proved. Based on the asymptotic expansion of the error functional, algorithm with theoretical analysis of the generalized extrapolation are given. Some examples show that the numerical results coincide with the theoretic analysis very well. More >

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