西北城市居民生活质量分级评价的BP神经网络模型研究

A study of life quality in northwest Chinese cities based on BP neural networks

从自然环境和社会环境两个子系统,涵盖8个评价因子共36个指标,建立了西北城市居民生 活质量指标体系,并确定了分级标准,通过构建BP神经网络模型进行级别辨识．网络模型经过训练仿 真后,利用训练好的模型对西北5个省会城市生活质量进行了分级,通过与模糊识别方法所测结果相 比较,验证了本文模型在实际应用中是可行的;文中所建指标体系和分级标准,除适合西北地区外,对 全国其他地区城市进行科学客观的居民生活质量分级评价也具有一定参考指导意义．引入BP神经网 络方法,为生活质量量化和进一步深入研究提供了新的研究方法和思路．

Based on the natural and social environment system, which contains 36 indexes, this paper establishes the index system of life quality in northwest Chinese cities and set up the standard level and also designs a model based on BP neural networks to measure off the levels. As a example we use the model, which has already been trained and simulated, to classify the level using the dates of five capital cities in northwest region. Finally, a comparison of the results obtained from fussy diagnosing method confirms that the model is feasiblein in practical use. The index system and the standard level we have established not only fit northwest citie, but also can be a reference to others all over the country. Similarly the BP neural networks model offers a new way to quantificationally and accurately study life quality.