利用EXPAR过程对摩洛哥年平均降雨量进行数学建模和统计分析

N. Azouagh, S. El Melhaoui
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引用次数: 0

摘要

在这项工作中,我们建议研究年平均降雨量时间序列,以评估气候随时间的变化模式。如果对这个时间序列进行正确的分析,它可以有助于改进规划和政策制定。这就是为什么我们考虑摩洛哥1901年至2020年平均年降雨量的数学建模和分析问题,使用描述性统计、结构变化分析、光谱分析和非线性指数自回归(EXPAR)过程来重现该时间序列的行为。结果表明,该时间序列在60、18和6 a左右存在显著的周期变化,全球下降趋势约为0.56 mm /年。此外,我们已经证明了使用非线性EXPAR过程而不是线性传统的EXPAR过程的选择是合理的,并提供了一个很好的拟合EXPAR模型。
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Mathematical modeling and statistical analysis of Moroccan mean annual rainfall using EXPAR processes
In this work, we propose a study of the mean annual rainfall time series in order to evaluate the climate changes pattern over time. If the analysis of this time series is carried out correctly, it can contribute to improve planning and policy development. That is why we consider the problem of mathematical modeling and analysis of the mean annual rainfall of Morocco between 1901 and 2020 using descriptive statistics, structure changes analysis, spectral analysis and a nonlinear Exponential Autoregressive (EXPAR) processes to reproduce the behavior of this time series. The results indicate three main breakpoints and show that the time series has a remarkable cycles about 60, 18 and 6 years with a global decrease tendency about 0.56 mm per year. Furthermore, we have justified the choice of using a non-linear EXPAR processes rather than a linear traditional one and provided a good fitted EXPAR model.
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来源期刊
Mathematical Modeling and Computing
Mathematical Modeling and Computing Computer Science-Computational Theory and Mathematics
CiteScore
1.60
自引率
0.00%
发文量
54
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