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  • Open Access

    ARTICLE

    Multi-Span and Multiple Relevant Time Series Prediction Based on Neighborhood Rough Set

    Xiaoli Li1, Shuailing Zhou1, Zixu An2,*, Zhenlong Du1

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3765-3780, 2021, DOI:10.32604/cmc.2021.012422

    Abstract Rough set theory has been widely researched for time series prediction problems such as rainfall runoff. Accurate forecasting of rainfall runoff is a long standing but still mostly significant problem for water resource planning and management, reservoir and river regulation. Most research is focused on constructing the better model for improving prediction accuracy. In this paper, a rainfall runoff forecast model based on the variable-precision fuzzy neighborhood rough set (VPFNRS) is constructed to predict Watershed runoff value. Fuzzy neighborhood rough set define the fuzzy decision of a sample by using the concept of fuzzy neighborhood. The fuzzy neighborhood rough set… More >

  • Open Access

    ARTICLE

    Study on the Improvement of the Application of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise in Hydrology Based on RBFNN Data Extension Technology

    Jinping Zhang1,2, Youlai Jin1, Bin Sun1,*, Yuping Han3, Yang Hong4

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.2, pp. 755-770, 2021, DOI:10.32604/cmes.2021.012686

    Abstract The complex nonlinear and non-stationary features exhibited in hydrologic sequences make hydrological analysis and forecasting difficult. Currently, some hydrologists employ the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method, a new time-frequency analysis method based on the empirical mode decomposition (EMD) algorithm, to decompose non-stationary raw data in order to obtain relatively stationary components for further study. However, the endpoint effect in CEEMDAN is often neglected, which can lead to decomposition errors that reduce the accuracy of the research results. In this study, we processed an original runoff sequence using the radial basis function neural network (RBFNN) technique… More >

  • Open Access

    ARTICLE

    Glyphosate retention in grassland riparian areas is reduced by the invasion of exotic trees

    Giaccio GCM1, P Laterra2, VC Aparicio3, JL Costa3

    Phyton-International Journal of Experimental Botany, Vol.85, pp. 108-116, 2016, DOI:10.32604/phyton.2016.85.108

    Abstract In this study, we examined some aspects regarding the effect of willow trees (Salix fragilis L.) invasion of grassland riparian environments in the Argentinean Pampas on the runoff reduction, sedimentation and glyphosate retention in the riparian vegetation strip (RVS). To assess the influence of willows on the filtering mechanisms, we performed runoff simulation experiments in plots of 1.5 x 2.5 m, in coastal environments characterized by the presence of willows or the lack of trees. Despite the short length of the experimental plots, the retention of glyphosate in the controls, with no trees, was higher and reached almost 74%. Nevertheless,… More >

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