An Empty Nester Recognition Model Based on a Feed Forward Neural Network

Rui Sun; Xiancheng Feng; Hongyi Xia

doi:10.1109/ISCMI.2015.27

An Empty Nester Recognition Model Based on a Feed Forward Neural Network

Rui Sun
, Xiancheng Feng
, Hongyi Xia

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

With the trend of aging of society, the number of empty nesters is rising, which has become a social problem that cannot be ignored. In this paper, two empty nester recognition models were presented based on the analysis of calling list and user information table. Based on the normal data, the empty nesters and their children's number can be identified by a recognition function. When the properties of a user are not adequate, recognition function cannot be applied to identify it. Feed forward neural network algorithm is used to solve this problem. The recognition accuracy rate can reach 73.3% after training the network. Based on the research, certain approaches can be made to improve the situations, which is beneficial to the development of a harmonious society.

Original language	English
Title of host publication	Proceedings - 2015 2nd International Conference on Soft Computing and Machine Intelligence, ISCMI 2015
Publisher	IEEE
Pages	60-63
ISBN (Print)	9781467398190
DOIs	https://doi.org/10.1109/ISCMI.2015.27
Publication status	Published - 19 Feb 2016
Event	2nd International Conference on Soft Computing and Machine Intelligence, ISCMI 2015 - Hong Kong, Hong Kong, China Duration: 23 Nov 2015 → 24 Nov 2015

Conference

Conference	2nd International Conference on Soft Computing and Machine Intelligence, ISCMI 2015
Place	Hong Kong, China
City	Hong Kong
Period	23/11/15 → 24/11/15

Research Keywords

Empty nesters
Feed Forward neural networks
Recognition function

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10.1109/ISCMI.2015.27

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@inproceedings{431ead22c91447c29d0ad9cb13982f90,

title = "An Empty Nester Recognition Model Based on a Feed Forward Neural Network",

abstract = "With the trend of aging of society, the number of empty nesters is rising, which has become a social problem that cannot be ignored. In this paper, two empty nester recognition models were presented based on the analysis of calling list and user information table. Based on the normal data, the empty nesters and their children's number can be identified by a recognition function. When the properties of a user are not adequate, recognition function cannot be applied to identify it. Feed forward neural network algorithm is used to solve this problem. The recognition accuracy rate can reach 73.3\% after training the network. Based on the research, certain approaches can be made to improve the situations, which is beneficial to the development of a harmonious society.",

keywords = "Empty nesters, Feed Forward neural networks, Recognition function",

author = "Rui Sun and Xiancheng Feng and Hongyi Xia",

year = "2016",

month = feb,

day = "19",

doi = "10.1109/ISCMI.2015.27",

language = "English",

isbn = "9781467398190",

pages = "60--63",

booktitle = "Proceedings - 2015 2nd International Conference on Soft Computing and Machine Intelligence, ISCMI 2015",

publisher = "IEEE",

address = "United States",

note = "2nd International Conference on Soft Computing and Machine Intelligence, ISCMI 2015 ; Conference date: 23-11-2015 Through 24-11-2015",

}

Sun, R, Feng, X & Xia, H 2016, An Empty Nester Recognition Model Based on a Feed Forward Neural Network. in Proceedings - 2015 2nd International Conference on Soft Computing and Machine Intelligence, ISCMI 2015., 7414674, IEEE, pp. 60-63, 2nd International Conference on Soft Computing and Machine Intelligence, ISCMI 2015, Hong Kong, Hong Kong, China, 23/11/15. https://doi.org/10.1109/ISCMI.2015.27

An Empty Nester Recognition Model Based on a Feed Forward Neural Network. / Sun, Rui; Feng, Xiancheng; Xia, Hongyi.
Proceedings - 2015 2nd International Conference on Soft Computing and Machine Intelligence, ISCMI 2015. IEEE, 2016. p. 60-63 7414674.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - An Empty Nester Recognition Model Based on a Feed Forward Neural Network

AU - Sun, Rui

AU - Feng, Xiancheng

AU - Xia, Hongyi

PY - 2016/2/19

Y1 - 2016/2/19

N2 - With the trend of aging of society, the number of empty nesters is rising, which has become a social problem that cannot be ignored. In this paper, two empty nester recognition models were presented based on the analysis of calling list and user information table. Based on the normal data, the empty nesters and their children's number can be identified by a recognition function. When the properties of a user are not adequate, recognition function cannot be applied to identify it. Feed forward neural network algorithm is used to solve this problem. The recognition accuracy rate can reach 73.3% after training the network. Based on the research, certain approaches can be made to improve the situations, which is beneficial to the development of a harmonious society.

AB - With the trend of aging of society, the number of empty nesters is rising, which has become a social problem that cannot be ignored. In this paper, two empty nester recognition models were presented based on the analysis of calling list and user information table. Based on the normal data, the empty nesters and their children's number can be identified by a recognition function. When the properties of a user are not adequate, recognition function cannot be applied to identify it. Feed forward neural network algorithm is used to solve this problem. The recognition accuracy rate can reach 73.3% after training the network. Based on the research, certain approaches can be made to improve the situations, which is beneficial to the development of a harmonious society.

KW - Empty nesters

KW - Feed Forward neural networks

KW - Recognition function

UR - https://www.scopus.com/pages/publications/84964402205

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84964402205&origin=recordpage

U2 - 10.1109/ISCMI.2015.27

DO - 10.1109/ISCMI.2015.27

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781467398190

SP - 60

EP - 63

BT - Proceedings - 2015 2nd International Conference on Soft Computing and Machine Intelligence, ISCMI 2015

PB - IEEE

T2 - 2nd International Conference on Soft Computing and Machine Intelligence, ISCMI 2015

Y2 - 23 November 2015 through 24 November 2015

ER -

An Empty Nester Recognition Model Based on a Feed Forward Neural Network

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