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SYSTEM FOR CONSTRUCTING PREDICTION MODEL OF TRAFFIC AT DISASTER AND CONTROL SYSTEM

机译：交通事故预测模型构建系统及控制系统

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摘要

PPROBLEM TO BE SOLVED: To construct a traffic prediction model which accurately predicts communication traffic in an earthquake disaster area. PSOLUTION: A traffic data collection part 2 collects data of communication traffic from NW nodes. A traffic data analysis part 3 processes traffic data to acquire a peak characteristic value. Information about distances between respective accommodation areas and populations in respective accommodation areas is preliminarily recorded in an information DB 6. An absorption/discharge factor acquisition part 4 acquires absorption factors and discharge factors per accommodation area of NW nodes. At each time of the occurrence of earthquake disasters, absorption factors and discharge factors in respective accommodation areas and the peak characteristic values are recorded in a history DB 5 in association with each other. A traffic prediction model constructing part 8 constructs a prediction model for a peak characteristic value A and furthermore constructs a prediction formula of traffic at disasters, on which a prediction result of the peak characteristic value is reflected. A communication traffic prediction part 9 predicts a communication traffic amount during the occurrence of earthquake disasters on the basis of the traffic prediction formula, per accommodation area of NW nodes. PCOPYRIGHT: (C)2011,JPO&INPIT

机译：

要解决的问题：构建一个流量预测模型，该模型可以准确地预测地震灾区的通信流量。

解决方案：流量数据收集部分2收集来自NW节点的通信流量数据。交通数据分析部分3处理交通数据以获得峰值特征值。预先将关于各个容纳区域之间的距离和各个容纳区域中的人口的距离的信息记录在信息DB 6中。吸收/放电因子获取部4获取NW节点的每个容纳区域的吸收因子和排放因子。在每次发生地震灾害时，将各自的容纳区域中的吸收因子和排放因子以及峰值特征值彼此关联地记录在历史DB 5中。交通量预测模型构建部8构建峰值特征值A的预测模型，并且进一步构建灾害时交通量的预测公式，在该公式上反映峰值特征值的预测结果。通信业务量预测部9基于通信量预测公式，在NW节点的每个容纳区域中预测地震灾害发生期间的通信业务量。

版权：（C）2011，日本特许厅＆INPIT 展开▼

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公开/公告号JP2011055108A

专利类型
公开/公告日2011-03-17

原文格式PDF
申请/专利权人 KDDI CORP;
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申请/专利号JP20090200314
发明设计人 KOGASHIRA HIDEYUKI;NAKAMURA HAJIME;
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申请日2009-08-31
分类号H04M3/22;H04M3/24;G06Q50;
国家 JP
入库时间 2022-08-21 18:23:49

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