A BPNN-Based Method for Regional Competitiveness: Taking the Guangdong-Hong Kong-Macau Greater Bay Area as an Example
摘要
Guangdong-Hong Kong-Macau Greater Bay Area (GBA) reveals a significant opportunity for self-developing and regional competition since China’s government regards it as one of the most significant developing strategies. However, cities in this area are enhancing comprehensive competitiveness at different levels. This paper proposed a competitiveness evaluation model based on the entropy approach and built a competitiveness measuring and predictive model based on the BPNN machine learning algorithm. The research results illustrate that comprehensive competitiveness is approximately increasing over time, which shows a trend of eastward development. Hong Kong, Guangzhou, Shenzhen, Macau, and Dongguan are the top-5 cities during the three years. On the contrary, Zhongshan is the least competitive city, however, Zhongshan‘s comprehensive competitiveness emerges at the highest increasing rate.