室分信源自动识别算法指导服务

室分信源基础信息维护长期依赖人工录入，存在准确率和更新及时率问题。自主研发室分信源自动识别算法，基于室内网元的性能特征，利用随机森林分类算法根据用户手机MR上报信息，结合用户活动特征，可以快速大范围识别室分信源。纠正人工信息录入错的影响，提高基础信息的准确性和及时性。The maintenance of basic information for in-building distribution network signal sources has long relied on manual entry, resulting in problems with both accuracy and update timeliness. To address this issue, an independently developed automatic identification algorithm for in-building distribution network signal sources is proposed. Based on the performance characteristics of indoor network elements, this algorithm utilizes the Random Forest classification algorithm, combined with user activity characteristics and mobile Measurement Report (MR) data reported by user handsets, to rapidly and widely identify in-building distribution network signal sources. This approach can rectify the impacts of manual information entry errors and improve the accuracy and timeliness of basic information.

搜集汇总

背景与挑战

背景概述

该数据集提供室分信源自动识别算法服务，通过随机森林分类处理手机MR数据及用户特征，解决人工录入不准确问题，显著提升室分信源信息的准确性和时效性。