Wenxiang Wu

TL;DR: Li et al. as discussed by the authors used an extended STIRPAT model to investigate the effects of human activity on energy consumption and three types of industrial pollutant emissions at the national and regional levels and tested the environmental Kuznets curve (EKC) hypothesis.

TL;DR: Wang et al. as mentioned in this paper explored the institutional innovation of China's poverty alleviation since 2013 and further revealed the mechanism behind land policy innovation promoting the targeted poverty alleviations based on a case study of Songjiagou village of Fuping county, Hebei province.

TL;DR: In this paper, the authors used a combination of phenology, climate and geography data to predict the site-based rice yields using a traditional regression-based method (MLR, multiple linear regression), and more advanced three machine learning (ML) methods: backpropagation neural network (BP), support vector machine (SVM), and random forest (RF).

TL;DR: Investigations of county-level spatial and temporal patterns in social vulnerability in China from 1980 to 2010 demonstrate that the dynamic characteristics of China's county- level social vulnerability are notably distinct, and the dominant contributors to societal vulnerability for all of the years studied were rural character, development (urbanization), and economic status.

TL;DR: Based on balanced provincial panel data in China gathered from 1990 to 2012, this paper used an improved STIRPAT model to investigate the effects of RUDT on energy consumption and CO2 emissions on the regional and national levels.