CAJ | 학술논문

运用Elman神经网络模型对2010—2050年河北省人口数进行预测,经过分析得出,河北省的人口老龄化具有以下几个特征:老年人口规模庞大,增长迅速;老龄化程度超前于河北省的经济发展水平,社会负担沉重;老年人口的高龄化趋势明显;老年人口的性别差异较大;老年人口的分布具有明显的差异性等.根据这些特征为河北省应对人口老龄化提供了一些对策建议.
운용Elman신경망락모형대2010—2050년하북성인구수진행예측,경과분석득출,하북성적인구노령화구유이하궤개특정:노년인구규모방대,증장신속;노령화정도초전우하북성적경제발전수평,사회부담침중;노년인구적고령화추세명현;노년인구적성별차이교대;노년인구적분포구유명현적차이성등.근거저사특정위하북성응대인구노령화제공료일사대책건의.
Elman neural network model is used to make population projections in 2010—2050 of Hebei Province population. After analysis, the aging of Hebei province has the following characteristics: the aging population is of large scale and grows rapidly in recent years;the degree of aging is ahead of the level of economic development in Hebei Province, which leads to a huge burden on the society; the aging trend of the elderly population is insurmountable; there are relatively large gender gap among elderly population; the distribution of the elderly population has significant differences. Based on these characteristics, we offer some countermeasures to deal with the aging population problem in Hebei Province.