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Further Assessment of Dissaving Risk against Life Expectancy for Elderly People through Anonymous Data and Random Data for Social Implementation

  • Yuya Yokoyama
  • , Yasunari Yoshitomi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With a view to detecting the deterioration of economic activity for elderly people at age of sixty-five or over, we have used an anonymous data (AD) obtained from the National Survey of Family Income and Expenditure (NSFIE) carried out by Ministry of Internal Affairs and Communications (MIC). So far we have developed a method to detect dissaving risk of elderly people by using AD and random data (RD). Here, AD was used as test data, while RD was set as training data. Then three methods were performed in terms of savings and income. The analysis result has shown that using both RD and AD would be as effective as using only AD for evaluating the performance of the proposed method. However, with a view to social implementation, it is required to investigate if our methods could be applicable when house types, rent or own house, are disregarded. This paper firstly shows that our method can be extensive with disregarding house types. Then these results can be improved for single males and females through altering two experimental parameters. For the purposes of performance evaluation, four sets of conditions are considered and analyzed. The best when the threshold to determine AD as dissaving risk might depend on the training data. Moreover, the best criterion to detect dissaving risk of elderly males was not the same for elderly females.

Original languageEnglish
Title of host publicationProceedings - 2020 9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020
EditorsTokuro Matsuo, Kunihiko Takamatsu, Yuichi Ono, Sachio Hirokawa
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages27-32
Number of pages6
ISBN (Electronic)9781728173979
DOIs
Publication statusPublished - 09-2020
Externally publishedYes
Event9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020 - Kitakyushu, Japan
Duration: 01-09-202015-09-2020

Publication series

NameProceedings - 2020 9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020

Conference

Conference9th International Congress on Advanced Applied Informatics, IIAI-AAI 2020
Country/TerritoryJapan
CityKitakyushu
Period01-09-2015-09-20

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Information Systems and Management

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