用低音扩散模型预测亚太地区的移动用户

W. Wenrong, M. Xie, K. Tsui
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引用次数: 11

摘要

在当今这个充满活力的世界里,移动通信已经改变了许多人的生活方式。预测一个国家的移动用户是研究领域之一。本文采用Bass扩散模型对亚太地区主要国家的移动业务用户数量进行预测。从技术上比较了低音扩散模型和类比扩散两种预测方法。一种在研究中很流行,另一种在实践中普遍应用。比较了Bass扩散模型的两种估计方法:自适应非线性最小二乘(adaptive NLS)和遗传算法(GA)。结果表明,Bass扩散模型总体上优于基于样本内误差平方和和样本外误差平方和的类比扩散模型。另一方面,自适应NLS和遗传算法在产生合理可靠的预测结果方面具有可比性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecasting of Mobile Subscriptions in Asia Pacific Using Bass Diffusion Model
In today's dynamic world, mobile communication has changed the lifestyle of many people. Forecasting of mobile subscriptions in a country is one of the research areas. In this paper, Bass diffusion model is used to forecast the number of mobile service subscribers in major countries in Asia Pacific. Technically, we compare two forecasting methods: Bass diffusion model and diffusion by analogy. One is popular in research and the other is commonly applied in practice. Two estimation methods for Bass diffusion model are also compared: adaptive nonlinear least square (adaptive NLS) and genetic algorithm (GA). The results show that Bass diffusion model in general performs better than diffusion by analogy based on the in-sample sum of squared errors (SSE) and out-of-sample SSE. On the other hand, adaptive NLS and genetic algorithms are comparable in generating reasonably sound forecasting results
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