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  • Open Access

    ARTICLE

    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 the model's ability to capture… More >

  • Open Access

    ARTICLE

    Modelling the ZR Relationship of Precipitation Nowcasting Based on Deep Learning

    Jianbing Ma1,*, Xianghao Cui1, Nan Jiang2

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1939-1949, 2022, DOI:10.32604/cmc.2022.025206

    Abstract Sudden precipitations may bring troubles or even huge harm to people's daily lives. Hence a timely and accurate precipitation nowcasting is expected to be an indispensable part of our modern life. Traditionally, the rainfall intensity estimation from weather radar is based on the relationship between radar reflectivity factor (Z) and rainfall rate (R), which is typically estimated by location-dependent experiential formula and arguably uncertain. Therefore, in this paper, we propose a deep learning-based method to model the ZR relation. To evaluate, we conducted our experiment with the Shenzhen precipitation dataset. We proposed a combined method of deep learning and the… More >

  • Open Access

    ARTICLE

    Proposed Different Signal Processing Tools for Efficient Optical Wireless Communications

    Hend Ibrahim1, Abeer D. Algarni2,*, Mahmoud Abdalla1, Walid El-Shafai3,4, Fathi E. Abd El-Samie2,3, Naglaa F. Soliman1,2

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3293-3318, 2022, DOI:10.32604/cmc.2022.022436

    Abstract Optical Wireless Communication (OWC) is a new trend in communication systems to achieve large bandwidth, high bit rate, high security, fast deployment, and low cost. The basic idea of the OWC is to transmit data on unguided media with light. This system requires multi-carrier modulation such as Orthogonal Frequency Division Multiplexing (OFDM). This paper studies optical OFDM performance based on Intensity Modulation with Direct Detection (IM/DD) system. This system requires a non-negativity constraint. The paper presents a framework for wireless optical OFDM system that comprises (IM/DD) with different forms, Direct Current biased Optical OFDM (DCO-OFDM), Asymmetrically Clipped Optical OFDM (ACO-OFDM),… More >

  • Open Access

    ARTICLE

    AttEF: Convolutional LSTM Encoder-Forecaster with Attention Module for Precipitation Nowcasting

    Wei Fang1,2,*, Lin Pang1, Weinan Yi1, Victor S. Sheng3

    Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 453-466, 2021, DOI:10.32604/iasc.2021.016589

    Abstract Precipitation nowcasting has become an essential technology underlying various public services ranging from weather advisories to citywide rainfall alerts. The main challenge facing many algorithms is the high non-linearity and temporal-spatial complexity of the radar image. Convolutional Long Short-Term Memory (ConvLSTM) is appropriate for modeling spatiotemporal variations as it integrates the convolution operator into recurrent state transition functions. However, the technical characteristic of encoding the input sequence into a fixed-size vector cannot guarantee that ConvLSTM maintains adequate sequence representations in the information flow, which affects the performance of the task. In this paper, we propose Attention ConvLSTM Encoder-Forecaster(AttEF) which allows… More >

  • Open Access

    ARTICLE

    Acoustic Scattering Performance for Sources in Arbitrary Motion

    Yunpeng Ma1, Lifeng Wang1, *, Mingxu Yi1

    CMES-Computer Modeling in Engineering & Sciences, Vol.113, No.1, pp. 89-108, 2017, DOI:10.3970/cmes.2017.113.086

    Abstract In this paper, an analytical time domain formulation based on Ffowcs Williams-Hawkings (FW-H) equation is derived for the prediction of the acoustic velocity field generated by moving bodies. This provides the imposition of the Neumann boundary condition on a rigid scattering surface. In order to calculate the scattering sound pressure of the duct, a thin-body boundary element method (BEM) has been proposed. The radiate sound pressure is calculated using the acoustic analogy FW-H equation. The scattering effect of the duct wall on the propagation of the sound wave is presented using the thin-body BEM. Computational results for a pulsating sphere,… More >

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