论文标题
全球人口增长作为社会经济软件系统动力学的发展
Global Population Growth as Socio-Economic Soft Matter System Dynamics Evolution
论文作者
论文摘要
该报告将全球人口的动态视为社会经济软件系统的独特情况。由于局部自组织的固有趋势，该类别是针对以中尺度组件为主的复杂系统引入的。通过使用软物质科学中开发的普遍主义缩放模式研究人口增长的进化来验证该假设。它得到了基于创新的衍生化和扭曲敏感分析的支持，显示了延长的Malthus型趋势从10 000 B到CA。第1200年。随后，显示了指数级的人口上升模式的明确证据，其独特的交叉位置接近1970年。与较早的趋势相比，今年人口增长有系统地降低。人口增长面临着全球粮食需求的进化，这也会发生变化，也遵循指数式的模式。网络和创新的兴起表明是从马尔萨斯型指数行为到有能力的指数级的驱动力。它得到了对创新专利数量的分析的支持。作者介绍了基于导数的和扭曲敏感的分析，以最佳实现用于描述动态数据的有能力的指数函数。
The report considers the dynamics of the global population as the unique case of the Socio-Economic Soft Matter system. This category was introduced for complex systems dominated by mesoscale assemblies, emerging due to the inherent tendency for local self-organization. The hypothesis is validated by studying population growth evolution using universalistic scaling patterns developed in Soft Matter science. It is supported by the innovative derivative-based and distortions-sensitive analysis, showing the extended Malthus-type trend from 10 000 B till ca. the year 1200. Subsequently, the explicit evidence of the powered exponential population rise pattern is shown, with the unique crossover near 1970. Following this year, the population growth systematically slows down compared to earlier trends. Population growth is confronted with global food demand evolution, which changes and also follows an exponential pattern. The rise of networking and innovations are indicated as the driving force leading to the crossover from the Malthus-type exponential behavior to the powered exponential one. It is supported by the analysis of the number of patents for innovations. The authors introduced the derivative-based and distortions-sensitive analysis for the optimal implementation of the powered exponential function for describing dynamic data.
