An Unsupervised Neural Network Algorithm SOMO for Continuous Optimization Problems

DOI

10.2991/iwmecs-18.2018.21How to use a DOI?

Keywords

SOMO, Continuous Optimization Problems, Unsupervised Neural Network Algorithm

Abstract

The application of self-organizing neural network in customer classification is discussed. The concept of customer classification, index selection, classification method selection and SOM (Self Organization Map) clustering method are discussed, and a customer classification method based on SOM , Namely, the indexes of RFM (Recency; Frequency, Value, Monentary) are given, and the customers are classified according to the calculation of the comprehensive index and the relative learning results of each index, and the simulation calculation is performed, The simulation results are categorized to validate the algorithm.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Anzhi Qi
PY  - 2018/04
DA  - 2018/04
TI  - An Unsupervised Neural Network Algorithm SOMO for Continuous Optimization Problems
BT  - Proceedings of the 2018 3rd International Workshop on Materials Engineering and Computer Sciences (IWMECS 2018)
PB  - Atlantis Press
SP  - 98
EP  - 101
SN  - 2352-538X
UR  - https://doi.org/10.2991/iwmecs-18.2018.21
DO  - 10.2991/iwmecs-18.2018.21
ID  - Qi2018/04
ER  -