通过回归分析得到问题的最优解

Branko Z. Popović
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引用次数: 2

摘要

问题是各种可能的和不可能的问题、任务和谜语,它们被设置并试图以不同的方式解决。然而,假设所有问题的一半是无法解决的,而剩下的四分之一是无法定义的,那么很有可能成功地用数学方法解决问题的第二部分。通过定义回归函数、关系估计、预测结果、模拟数据、优化大小和改进解决过程,使用回归分析可以确定依赖响应和独立因素之间的关系。虽然有许多回归分析,但通常使用线性回归分析。作者提出了在16种不同的回归分析中选择显著回归分析的程序和求解回归分析的程序。在本版本中,使用这种方法,给出了寻找太阳能集热器最佳日照位置问题的最佳解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The optimal solution to the problems by regression analysis
Problems are various possible and impossible questions, tasks and riddles that are being set up and attempt to solve in different ways. However, assuming that half of all problems are not solvable and that the remaining one-fourth cannot be defined, there are good chances for a successful mathematical solution to the second quarter of the problem. Problem-solving using regression analyses allows determining the relationship between the dependent response and the independent factors through defined regression functions, relationship estimates, predicting results, simulating data, optimizing the sizes, and improving the resolution process. Although there are many regression analyses, linear regression analyses are usually used. The author proposes the application of Procedure for selecting a significant regression analysis between 16 different regression analyses and Procedures for solving regression analyses. Using this approach in this release, an optimal solution of the problem of finding the optimal best sun exposure position for the solar collector is shown.
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