Showing papers by "Jun Yang published in 2015"
TL;DR: Zhang et al. as discussed by the authors examined the socio-spatial context of uneven development and the residential accessibility of green space in Dalian of Liaoning Province, China, and analyzed social fairness with a community scale as the basis.
Abstract: This study examines the socio-spatial context of uneven development and the residential accessibility of green space in Dalian of Liaoning Province, China. The social fairness was analyzed with a community scale as the basis. We combined social scientific methods with a GIS method using a behavior accessibility model from the perspectives of fairness of urban green space allocation based on social geography, geographic information science, management science and many other related discipline theories. The results show that: 1) Most of the urban green space distribution presents an unbalanced phenomenon, and it does not match with the population distribution; 2) We found some differences in the accessibility of the population with different attributes and opportunities to use and enjoy the urban green spaces, mainly due to: the dual social and spatial attributes of the residents and the serious stratum differentiation generated were the internal causes; the residential space differentiation and the pursuit of economic and real estate development were the direct causes; and unreasonable planning, in regard to the fact that government policies did not give consideration to efficiency and fairness, was also an important factor.
21 citations
TL;DR: In this article, a fuzzy genetic algorithm (FGA) was proposed for maximizing the economic profitability of a wind power plant micro-siting, which considers a new WF model including several important factors to the design of the layout.
Abstract: With the fast growth in the number and size of installed wind farms (WFs) around the world, optimal wind turbines (WTs) micrositing has become a challenge from both technological and mathematical points of view. An appropriate layout of wind turbines is crucial to obtain adequate performance with respect to the development and operation of the wind power plant during its life span. This work presents a fuzzy genetic algorithm (FGA) for maximizing the economic profitability of the project. The algorithm considers a new WF model including several important factors to the design of the layout. The model consists of wake loss, terrain effect, and economic benefits, which can be calculated by locations of wind turbines. The results demonstrate that the algorithm performs better than genetic algorithm, in terms of maximum values of net annual value of wind power plants and computational burden.
10 citations