首页|Research Data from Hubei University of Economics Update Understanding of Machine Learning (Unraveling the Dynamic Relationship between Neighborhood Deprivation and Walkability over Time: A Machine Learning Approach)
Research Data from Hubei University of Economics Update Understanding of Machine Learning (Unraveling the Dynamic Relationship between Neighborhood Deprivation and Walkability over Time: A Machine Learning Approach)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in artific ial intelligence. According to news originating from Wuhan, People’s Republic of China, by NewsRx editors, the research stated, “Creating a walkable environment is an essential step toward the 2030 Sustainable Development Goals.” Funders for this research include Humanities And Social Science Fund of Ministry of Education of China. Our news editors obtained a quote from the research from Hubei University of Eco nomics: “Nevertheless, not all people can enjoy a walkable environment, and neig hborhoods with different socioeconomic status are found to vary greatly with wal kability. Former studies have typically unraveled the relationship between neigh borhood deprivation and walkability from a temporally static perspective and the produced estimations to a point-in-time snapshot were believed to incorporate g reat uncertainties. The ways in which neighborhood walkability changes over time in association with deprivation remain unclear. Using the case of the Hangzhou metropolitan area, we first measured the neighborhood walkability from 2016 to 2 018 by calculating a set of revised walk scores. Further, we applied a machine l earning algorithm, the kernel-based regularized least squares regression in part icular, to unravel how neighborhood walkability changes in relation to deprivati on over time. The results not only capture the nonlinearity in the relationship between neighborhood deprivation and walkability over time, but also highlight t he marginal effects of each neighborhood deprivation indicator.”
Hubei University of EconomicsWuhanPe ople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
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