Development of an Optimal RTK Calculation Program Using Genetic Algorithm

Da Hae Yu, Jin Hyuk Jeon, Jung Ho Lee, Dong Jun Kim
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Abstract

Rising levels of underground water and inappropriate pipe alignment during rainy weather have led to a rise in rainfall-derived infiltration and inflow (RDII), increasing incidences of separate sewer overflows (SSOs) and reducing the efficiency of sewage treatment systems. RTK analysis based on measured RDII data of the target area through computer modeling is essential when maintaining sewer pipes in order to address this RDII problem. In the Sanitary Sewer Overflow Analysis and Planning (SSOAP) program used for RTK analysis, calculating RTK using a trial and error method is a bit challenging. Accordingly, this study introduces a program to calculate the optimal RTK at the measurement point using a genetic algorithm. In ROP, accuracy was added to the RDII prediction mechanism by incorporating error rates based on time intervals into the evaluation factors of SSOAP, namely rainfall inflow rate and peak flow error rate. The error rate for the SSOAP program and ROP was validated as 2.66%.
利用遗传算法开发最佳 RTK 计算程序
雨季地下水位上升和管道走向不当导致雨水渗入和流入(RDII)增加,增加了单独下水道溢流(SSO)的发生率,降低了污水处理系统的效率。为了解决 RDII 问题,在维护下水管道时,必须通过计算机建模,根据目标区域的 RDII 测量数据进行 RTK 分析。在用于 RTK 分析的下水道溢流分析和规划(SSOAP)程序中,使用试错法计算 RTK 有点困难。因此,本研究引入了一个程序,利用遗传算法计算测量点的最佳 RTK。在 ROP 中,通过将基于时间间隔的误差率纳入 SSOAP 的评估因素(即降雨流入率和峰值流量误差率),增加了 RDII 预测机制的准确性。经验证,SSOAP 程序和 ROP 的误差率为 2.66%。
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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