Projection of Real Mass Deformation Scenes – Intelligent Support

W. Piwowarski
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引用次数: 0

Abstract

The paper analyses the process of post-mining displacements generated by underground mining. Innovative mathematical structures for the modeling of hazard field emission were developed as strong solutions to partial differential equations in R3+1. Moreover, a stochastic equation in L2(Ω) (probabilistic space) was defined and applied as a model that takes into account the randomness of the process. Monitoring of a mining area based on solutions in the GNSS technology and classical geodesy supports the analysis of topological transformations of a given subspace. The data was archived and stored in digital form and then analyzed in many ways. The quality of the representation (measurements and modeling) was estimated with the use of incremental statistics. Thus, obtained distributions of density function are not ranked as normal distribution. The performed analyses make it possible to predict the optimal scenarios for post-mining environmental hazards.
真实质量变形场景的投影-智能支持
本文分析了地下开采产生的采后位移过程。在R3+1中的偏微分方程的强解中,开发了用于危害场发射建模的创新数学结构。此外,定义了L2(Ω)(概率空间)中的随机方程,并将其作为考虑过程随机性的模型。基于GNSS技术和经典大地测量学解决方案的矿区监测支持对给定子空间的拓扑变换进行分析。这些数据被存档并以数字形式存储,然后用多种方法进行分析。使用增量统计来估计表示(测量和建模)的质量。因此,得到的密度函数分布不属于正态分布。所进行的分析使预测采矿后环境危害的最佳方案成为可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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