satellite_leak_detection:使用机器学习检测卫星图像中的漏水-源码

上传者: 42135462 | 上传时间: 2021-09-07 13:27:48 | 文件大小: 20.05MB | 文件类型: ZIP
泄漏检测 草稿2017-05-01 迈克尔·克拉克(Michael.clark via wassname dot org),克雷格·巴尔达奇诺(Craig Baldacchino) 该项目探讨了我们可以使用卫星图像和机器学习来发现泄漏的想法。 主要假设是,鉴于泄漏维修的时间和地点以及给定的10-15m2分辨率的卫星图像,我们可以比随机猜测所定义的基准更好地预测泄漏。 我们使用随机森林模型,然后使用超优化调整数据过滤器和模型参数。 我们的结果显示f1得分约为0.6,而虚拟f1得分为0.5。 这个小的改进支持了我们的假设,但是它表示预测能力太差,无法用于管道维护。 我们预计,以更高分辨率的图像重复实验可能会提供有用的预测能力水平。 介绍 西澳大利亚州的漏水造成了超过100亿升的水,每年造成的损失超过10亿美元。 西澳大利亚州自来水公司每年只能人工检查10-12%的管网是否有不可见的泄漏 。

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