Predictive Modeling and Mobility Pattern Analysis

Barathi Subramanian, Anand Paul, Jeonghong Kim, Madhan Kumar Srinivasan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The predictive modeling process begins once a set of current or historical data is collected for analysis. Then data scientists or analysts create algorithms and statistical models, train them with subsets of the data and run them against the full data set to generate the predictive model. In many cases, multiple models are used at once to create one prediction. While the terms predictive modeling and predictive analytics are sometimes used interchangeably. Modeling can be seen instead as the hands-on part of analytics applications. Mobility report from Google can impact many areas of life including economy and also matters to policy maker, with such mobility data as well as analysis we can also predict.

Original languageEnglish
Title of host publication2021 9th International Conference on Orange Technology, ICOT 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665478427
DOIs
StatePublished - 2021
Event9th International Conference on Orange Technology, ICOT 2021 - Tainan, Taiwan, Province of China
Duration: 16 Dec 202117 Dec 2021

Publication series

Name2021 9th International Conference on Orange Technology, ICOT 2021

Conference

Conference9th International Conference on Orange Technology, ICOT 2021
Country/TerritoryTaiwan, Province of China
CityTainan
Period16/12/2117/12/21

Keywords

  • forecasting
  • google analytics
  • mobility pattern
  • predictive modeling

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