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Use of WASD neuronet in projecting the population of Oceania based on 1000-year historical data

机译:基于1000年历史数据的WASD神经网络在预测大洋洲人口中的应用

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With growing economic and political influence in the world, the important role played by Oceania in population issues should not be neglected. So it is very important and urgent to find an effective way to make a proper population projections. Nonetheless, the traditional methods focused on fertility and mortality may lead to the lack of all-sidedness in projection results. We realize that the historical data contain the internal mechanism of the population development, and the neuronet performs well with nonlinear data and the multifactor system. Therefore, in this report, we construct a 3-layer feed-forward neuronet equipped with a weights-and-structure-determination (WASD) algorithm to learn the historical data and project the population. With the neuronet well trained by over 1000-year historical data, we successfully project that the future Oceania population will keep a steady increasing trend in the coming fifteen years.
机译:随着世界经济和政治影响力的日益增长,大洋洲在人口问题中发挥的重要作用不容忽视。因此,找到有效的方法来进行适当的人口预测是非常重要和紧迫的。尽管如此,专注于生育率和死亡率的传统方法可能会导致投影结果缺乏全面性。我们意识到历史数据包含人口发展的内部机制,并且神经网络在非线性数据和多因素系统中表现良好。因此,在本报告中,我们构建了一个装备有权重和结构确定(WASD)算法的3层前馈神经网络,以学习历史数据并规划种群。利用经过1000多年历史数据训练的神经网络,我们成功地预测了未来的大洋洲人口将在未来15年中保持稳定增长的趋势。

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