• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10B
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• pp.866-879
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• 2004

This paper presents a pricing model for maximizing a service provider's profit, taking into account consumers' quality-of-service dependent willingness to pay, in integrated voice/data mobile services. For the voice and the data services, time-sensitive pricing and volume-sensitive pricing mechanism will be applied, respectively, as in the case of Korea's mobile service market. Assuming that consumers are very sensitive to call interruption during handoff moments, the model presented here considers reserving guard channels exclusively for handoff traffic, in the process of frequency channels allocation, as well as guaranteeing consumers quality of service regarding call interruption rate. Ultimately, this model proposes a means to guarantee the quality of service in the short term, through pricing strategies as well as channel allocation policies, and the simulation results show that without expanding system resources, there exists a trade-off between profit and quality-of-service guarantee.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.55-60
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• 2022

Churn prediction is a critical long-term problem for many business like music, games, magazines etc. The churn probability can be used to study many aspects of a business including proactive customer marketing, sales prediction, and churn-sensitive pricing models. It is quite challenging to design machine learning model to predict the customer churn accurately due to the large volume of the time-series data and the temporal issues of the data. In this paper, a parallel artificial neural network is proposed to create a highly-accurate customer churn model on a large customer dataset. The proposed model has achieved significant improvement in the accuracy of churn prediction. The scalability and effectiveness of the proposed algorithm is also studied.