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基于RBF神经网络对宁波地铁粉丝量的预测及广告运营模式研究 被引量:3

Research on Prediction of Ningbo Metro Fan Volume and Advertising Operation Model Based on RBF Neural Network
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摘要 近年来,为了缓解城市的交通压力,各大城市陆续建造地铁,地铁已成为很多人出行的主要方式。地铁也逐渐变成了地铁生活圈,将商业中心、商务区、居民社区紧密联系在一起,不仅为出行者带来极大的方便,也在悄无声息中影响着人们的消费习惯、出行等生活方式。地铁的巨大客流量也为电子屏广告带来了不可小觑的商业价值。传统的只有广告没有内容吸引人群,注定会慢慢被淘汰,在什么时段投放何种广告,投放多久,已经成为广告运营方式的重点。文章将在研究宁波地铁公众号数据的基础上,挖掘用户信息,运用RBF预测模型,对广告运营模式进行研究。 In recent years, in order to alleviate the traffic pressure in cities, metro has been built in succession in major cities, and metro has become the main way for many people to travel. Metro has gradually become a metro life circle,which closely links the business center, business district and residential community. It not only brings great convenience to travelers, but also quietly affects people’s consumption habits,travel and other lifestyles. The huge passenger flow of metro also brings great commercial value for electronic screen advertisement. Traditionally, only advertising has no content to attract people. It is doomed to be eliminated slowly. What kind of advertising should be put in at what time and how long should it be put in has become the focus of advertising operation mode. Based on the study of Ningbo metro public number data, this paper will mine user information and use RBF prediction model to study the advertising operation mode.
作者 王珏 周健勇 WANG Jue;ZHOU Jianyong(Management School, University of Shanghai for Science and Technology, Shanghai 200093, China)
出处 《物流科技》 2019年第5期87-91,共5页 Logistics Sci-Tech
关键词 微信公众号 电子屏 粉丝量预测 RBF网络 wechat public number electronic screen fan quantity prediction RBF network
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