The service capacity of urban public open spaces is an important indicator of the justness and soundness of the allocation of public space resources,such as parks and green spaces,in the process of urban development.I...The service capacity of urban public open spaces is an important indicator of the justness and soundness of the allocation of public space resources,such as parks and green spaces,in the process of urban development.Improving the service capacity of urban public open spaces is conductive to healthy,sustainable urban development.In this study,taking Shengyang City,China as a case study,a Gaussian-based two-step floating catchment area method(2 SFCA)is used to calculate an accessibility index and identify residential areas with a poor accessibility to urban public open spaces.Then,a particle swarm algorithm(PSA)is used to optimize the locations of new open space developments.Finally,the optimization results are verified using the analytic network process(ANP).The results show that the service capacity of public open spaces in the center of Shenyang City(covering six districts)is relatively low and exhibits an uneven spatial distribution.In the service scope of the existing urban public open spaces,the accessibility for 48.6%of the residential estates is moderately poor or poor.The layout is optimized when the number of optimization points is set to 8.These points are mainly located in old town areas such as the Tiexi,Huanggu,and Dadong districts.The optimization increases the green space area accessible by motor vehicles(60 min),bicycles(60 min),and walking(30 min)by 4.67%,5.38%,and 8.03%of the study area,respectively.Finally,green space planning recommendations are offered from two perspectives:spatial layout and transport system optimization.展开更多
With the emergence of the loT era,wireless sensor networks will be more and more widely used.In addition to collecting,transmitting and processing simple data such as humidity,temperature and density of the dome,they ...With the emergence of the loT era,wireless sensor networks will be more and more widely used.In addition to collecting,transmitting and processing simple data such as humidity,temperature and density of the dome,they can also provide multimedia information services such as video and images.It enables more comprehensive and accurate environmental monitoring.Therefore,MSDs have a huge demand in military,daily,forestry,biomedicine and other fields.The intensive city model has obvious advantages in meeting people's diverse needs and comfortable life.Most obviously,it speeds up the rhythm of life for residents,thereby increasing efficiency and saving time.Starting from this aspect,this paper conducts a research on the evaluation index system of public built on the following areas of open space loT and mental health.In this paper,the GRNN neural network model is constructed,the mean condition is calculated,the density function can be estimated,the network output,and the schematic diagram of the generalized regression neural network is improved.Using the established system,the index in 2018 is selected as the base year,and after transformation,the standardized values of the past years are formed,which are substituted into the cells to form different matrices.The value of each cell is counted to obtain the subsystem coordination degree,and the global coordination degree is obtained through calculation.The evaluation results of ecological civilization construction and development in 2018 and 2019,2020 and 2021 were compared.The experimental data shows that compared with 2018,economic development will change from 1 to 2.000,social harmony will change from 1 to 2.480,ecological health will decrease to 0.850,environmental friendliness will decrease to 0.750,and comprehensive evaluation will decrease to 0.513.This shows that while the economy is developing this year,the construction of ecological civilization has been gradually carried out,and good results have been achieved.This reflects the effectiveness of the system.The subject of the evaluation index system of green public open space based on the Internet of Things and mental health has been well completed.展开更多
This study examined public attitudes concerning the value of outdoor spaces which people use daily. Two successive analyses were performed based on data from common residents and college students in the city of Hangzh...This study examined public attitudes concerning the value of outdoor spaces which people use daily. Two successive analyses were performed based on data from common residents and college students in the city of Hangzhou, China. First, citizens registered various items constituting desirable values of residential outdoor spaces through a preliminary questionnaire. The result proposed three general attributes (functional, aesthetic and ecological) and ten specific qualities of residential outdoor spaces. An analytic hierarchy process (AHP) was applied to an interview survey in order to clarify the weights among these attributes and qualities. Second, principal factors were extracted from the ten specific qualities with principal component analysis (PCA) for both the common case and the campus case. In addition, the variations of respondents’ groups were classified with cluster analysis (CA) using the results of the PCA. The results of the AHP application found that the public prefers the functional attribute, rather than the aesthetic attribute. The latter is always viewed as the core value of open spaces in the eyes of architects and designers. Fur-thermore, comparisons of ten specific qualities showed that the public prefers the open spaces that can be utilized conveniently and easily for group activities, because such spaces keep an active lifestyle of neighborhood communication, which is also seen to protect human-regarding residential environments. Moreover, different groups of respondents diverge largely in terms of gender, age, behavior and preference.展开更多
基金Under the auspices of the China National R&D Program(No.2017YFC0505704)National Natural Science Foundation of China(No.32101325)+1 种基金Fundamental Research Funds for the Central Universities of China(No.N2011005)Student Innovation Training Program of Northeastern University of China(No.201299)。
文摘The service capacity of urban public open spaces is an important indicator of the justness and soundness of the allocation of public space resources,such as parks and green spaces,in the process of urban development.Improving the service capacity of urban public open spaces is conductive to healthy,sustainable urban development.In this study,taking Shengyang City,China as a case study,a Gaussian-based two-step floating catchment area method(2 SFCA)is used to calculate an accessibility index and identify residential areas with a poor accessibility to urban public open spaces.Then,a particle swarm algorithm(PSA)is used to optimize the locations of new open space developments.Finally,the optimization results are verified using the analytic network process(ANP).The results show that the service capacity of public open spaces in the center of Shenyang City(covering six districts)is relatively low and exhibits an uneven spatial distribution.In the service scope of the existing urban public open spaces,the accessibility for 48.6%of the residential estates is moderately poor or poor.The layout is optimized when the number of optimization points is set to 8.These points are mainly located in old town areas such as the Tiexi,Huanggu,and Dadong districts.The optimization increases the green space area accessible by motor vehicles(60 min),bicycles(60 min),and walking(30 min)by 4.67%,5.38%,and 8.03%of the study area,respectively.Finally,green space planning recommendations are offered from two perspectives:spatial layout and transport system optimization.
文摘With the emergence of the loT era,wireless sensor networks will be more and more widely used.In addition to collecting,transmitting and processing simple data such as humidity,temperature and density of the dome,they can also provide multimedia information services such as video and images.It enables more comprehensive and accurate environmental monitoring.Therefore,MSDs have a huge demand in military,daily,forestry,biomedicine and other fields.The intensive city model has obvious advantages in meeting people's diverse needs and comfortable life.Most obviously,it speeds up the rhythm of life for residents,thereby increasing efficiency and saving time.Starting from this aspect,this paper conducts a research on the evaluation index system of public built on the following areas of open space loT and mental health.In this paper,the GRNN neural network model is constructed,the mean condition is calculated,the density function can be estimated,the network output,and the schematic diagram of the generalized regression neural network is improved.Using the established system,the index in 2018 is selected as the base year,and after transformation,the standardized values of the past years are formed,which are substituted into the cells to form different matrices.The value of each cell is counted to obtain the subsystem coordination degree,and the global coordination degree is obtained through calculation.The evaluation results of ecological civilization construction and development in 2018 and 2019,2020 and 2021 were compared.The experimental data shows that compared with 2018,economic development will change from 1 to 2.000,social harmony will change from 1 to 2.480,ecological health will decrease to 0.850,environmental friendliness will decrease to 0.750,and comprehensive evaluation will decrease to 0.513.This shows that while the economy is developing this year,the construction of ecological civilization has been gradually carried out,and good results have been achieved.This reflects the effectiveness of the system.The subject of the evaluation index system of green public open space based on the Internet of Things and mental health has been well completed.
文摘This study examined public attitudes concerning the value of outdoor spaces which people use daily. Two successive analyses were performed based on data from common residents and college students in the city of Hangzhou, China. First, citizens registered various items constituting desirable values of residential outdoor spaces through a preliminary questionnaire. The result proposed three general attributes (functional, aesthetic and ecological) and ten specific qualities of residential outdoor spaces. An analytic hierarchy process (AHP) was applied to an interview survey in order to clarify the weights among these attributes and qualities. Second, principal factors were extracted from the ten specific qualities with principal component analysis (PCA) for both the common case and the campus case. In addition, the variations of respondents’ groups were classified with cluster analysis (CA) using the results of the PCA. The results of the AHP application found that the public prefers the functional attribute, rather than the aesthetic attribute. The latter is always viewed as the core value of open spaces in the eyes of architects and designers. Fur-thermore, comparisons of ten specific qualities showed that the public prefers the open spaces that can be utilized conveniently and easily for group activities, because such spaces keep an active lifestyle of neighborhood communication, which is also seen to protect human-regarding residential environments. Moreover, different groups of respondents diverge largely in terms of gender, age, behavior and preference.
