期刊：
Systems and Soft Computing,2025年:200269 ISSN：2772-9419
通讯作者：
Hui Tang
作者机构：
College of Architecture and Urban Planning, Hunan City University, Yiyang, 413000, China;[Wenxing You] Beijing Century Chief International Architecture Design Co., Ltd, Beijing, 110000, China;[Lu Ou] School of Architecture, Changsha University of Science & Technology, Changsha, Hunan 410000, China;Hunan Provincial Key Laboratory of Urban Planning Information Technology, Yiyang, 413000, China;School of Architecture and Planning, Hunan University, Changsha, 410000, China
通讯机构：
[Hui Tang] C;College of Architecture and Urban Planning, Hunan City University, Yiyang, 413000, China<&wdkj&>Hunan Provincial Key Laboratory of Urban Planning Information Technology, Yiyang, 413000, China
摘要：
Urban resilience evaluates systems’ capacities to prepare for, adapt to, absorb, and recover from disruptions. Evaluation frameworks incorporate metrics like recovery speed, adaptive ability, and absorptive capacity. Assessing critical infrastructure interdependencies is challenging yet vital to limit failure propagation. While static assessments, multi-layer frameworks, and software like Hazus are used, limitations persist. Machine learning often focuses on infrastructure data for recovery monitoring. A common workflow entails acquiring and organizing data, then applying supervised, unsupervised, or reinforcement learning models. Supervised learning uses labeled data while unsupervised learning detects patterns in unlabeled data. Reinforcement learning optimizes rewards through trial-and-error interactions. Machine learning assists in meeting intensifying urbanization and climate change challenges. Leveraging advances in sensors, IoT, and computing enables tasks like image labeling and semantic segmentation. The techniques facilitate resilience through real-time data analytics for informed decision-making and responsive disaster management.
Urban resilience evaluates systems’ capacities to prepare for, adapt to, absorb, and recover from disruptions. Evaluation frameworks incorporate metrics like recovery speed, adaptive ability, and absorptive capacity. Assessing critical infrastructure interdependencies is challenging yet vital to limit failure propagation. While static assessments, multi-layer frameworks, and software like Hazus are used, limitations persist. Machine learning often focuses on infrastructure data for recovery monitoring. A common workflow entails acquiring and organizing data, then applying supervised, unsupervised, or reinforcement learning models. Supervised learning uses labeled data while unsupervised learning detects patterns in unlabeled data. Reinforcement learning optimizes rewards through trial-and-error interactions. Machine learning assists in meeting intensifying urbanization and climate change challenges. Leveraging advances in sensors, IoT, and computing enables tasks like image labeling and semantic segmentation. The techniques facilitate resilience through real-time data analytics for informed decision-making and responsive disaster management.
摘要：
INTRODUCTION: University campuses, with their abundant natural resources and sports facilities, are essential in promoting walking activities among students, faculty, and nearby communities. However, the mechanisms through which campus environments influence walking activities remain insufficiently understood. This study examines universities in Wuhan, China, using crowdsourced data and machine learning methods to analyze the nonlinear and interactive effects of campus built environments on exercise walking. METHODS: This study utilized crowdsourced exercise walking data and incorporated diverse campus characteristics to construct a multidimensional variable system. By applying the XGBoost algorithm and SHAP (SHapley Additive exPlanations), an explainable machine learning framework was established to evaluate the importance of various factors, explore the nonlinear relationships between variables and walking activity, and analyze the interaction effects among these variables. RESULTS: The findings underscore the significant impact of several key factors, including the proportion of sports land, proximity to water bodies, and Normalized Difference Vegetation Index NDVI, alongside the notable influence of six distinct campus area types. The analysis of nonlinear effects revealed distinct thresholds and patterns of influence that differ from other urban environments, with some variables exhibiting fluctuated or U-shaped effects. Additionally, strong interactions were identified among variable combinations, highlighting the synergistic impact of elements like sports facilities, green spaces, and waterfront areas when strategically integrated. CONCLUSION: This research contributes to the understanding of how campus built environments affect walking activities, offering targeted recommendations for campus planning and design. Recommendations include optimizing the spatial configuration of sports facilities, green spaces, and water bodies to maximize their synergistic impacts on walking activity. These insights can foster the development of inclusive, health-promoting, and sustainable campuses.
作者机构：
[Han, Xiaojuan; Peng, Fang; Zeng, Qing] College of Architecture and Urban Planning, Hunan City University, Yiyang, China
摘要：
Global awareness of sustainable development has heightened interest in green buildings as a key strategy for reducing energy consumption and carbon emissions. Accurate prediction of energy consumption plays a vital role in developing effective energy management and conservation strategies. This study addresses these challenges by proposing an advanced deep learning framework that integrates Time-Dependent Variational Autoencoder (TD-VAE) with Adaptive Gated Self-Attention GRU (AGSA-GRU). The framework incorporates self-attention mechanisms and Multi-Task Learning (MTL) strategies to capture long-term dependencies and complex patterns in energy consumption time series data, while simultaneously optimizing prediction accuracy and anomaly detection. Experiments on two public green building energy consumption datasets validate the effectiveness of our proposed approach. Our method achieves a prediction accuracy of 93.2%, significantly outperforming traditional deep learning methods and existing techniques. ROC curve analysis demonstrates our model's robustness, achieving an Area Under the Curve (AUC) of 0.91 while maintaining a low false positive rate (FPR) and high true positive rate (TPR). This study presents an efficient solution for green building energy consumption prediction, contributing significantly to energy conservation, emission reduction, and sustainable development in the construction industry.
摘要：
Outdoor thermal comfort (OTC) in traditional villages is a concern for the health of the residents and the development of rural tourism. However, previous studies on outdoor thermal comfort have given limited attention to traditional villages. Based on a field study conducted during summer in a traditional village in Fenghuang, China, which is a hot-humid environment, this study assesses outdoor thermal comfort variations between residents and tourists by considering three aspects: thermal benchmarks, influencing factors, and thermal adaptations. Results show that: (1) Residents are more acclimatized to the local hot-humid environment than tourists. The neutral PET (NPET) of residents (24.8 °C) was higher than that of tourists (20.1 °C). The neutral PET range (NPETR) of residents (21.0–28.7 °C) was higher compared to that of tourists (16.5–23.6 °C). The 80 % thermal acceptability range for residents and tourists was below 30.9 °C and 25.4 °C, respectively. (2) Factors influencing the thermal perceptions of residents and tourists vary with weather conditions. Solar radiation is the dominant influence on sunny days, while temperature is the dominant influence on cloudy days. Non-meteorological factors (individual and psychological factors) have a greater impact on tourists than on residents in both weather conditions. (3) When dissatisfied with the environment, tourists prefer improved temperatures and wind, while residents prefer improved humidity. Tourists manage thermal discomfort with drinking water and reducing activity intensity, while residents prefer moving to shade and reducing activity intensity. Accordingly, some suggestions were proposed, that could offer valuable references for the environmental optimization of traditional villages.
Outdoor thermal comfort (OTC) in traditional villages is a concern for the health of the residents and the development of rural tourism. However, previous studies on outdoor thermal comfort have given limited attention to traditional villages. Based on a field study conducted during summer in a traditional village in Fenghuang, China, which is a hot-humid environment, this study assesses outdoor thermal comfort variations between residents and tourists by considering three aspects: thermal benchmarks, influencing factors, and thermal adaptations. Results show that: (1) Residents are more acclimatized to the local hot-humid environment than tourists. The neutral PET (NPET) of residents (24.8 °C) was higher than that of tourists (20.1 °C). The neutral PET range (NPETR) of residents (21.0–28.7 °C) was higher compared to that of tourists (16.5–23.6 °C). The 80 % thermal acceptability range for residents and tourists was below 30.9 °C and 25.4 °C, respectively. (2) Factors influencing the thermal perceptions of residents and tourists vary with weather conditions. Solar radiation is the dominant influence on sunny days, while temperature is the dominant influence on cloudy days. Non-meteorological factors (individual and psychological factors) have a greater impact on tourists than on residents in both weather conditions. (3) When dissatisfied with the environment, tourists prefer improved temperatures and wind, while residents prefer improved humidity. Tourists manage thermal discomfort with drinking water and reducing activity intensity, while residents prefer moving to shade and reducing activity intensity. Accordingly, some suggestions were proposed, that could offer valuable references for the environmental optimization of traditional villages.
作者机构：
[Long, Tianxiang] Hunan City Univ, Coll Architecture & Urban Planning, Yiyang 413000, Peoples R China.;[Long, Tianxiang] Key Lab Urban Planning Informat Technol, Yiyang 413000, Peoples R China.;[Long, Tianxiang] Key Lab Digital Urban & Rural Spatial Planning, Yiyang 413000, Peoples R China.;[Liu, Yuxin] Tongji Univ, Sch Econ & Management, Shanghai 200092, Peoples R China.;[Zhong, Qikang] Cent South Univ, Sch Architecture & Art, Changsha 410083, Peoples R China.
通讯机构：
[Zhong, QK ] C;Cent South Univ, Sch Architecture & Art, Changsha 410083, Peoples R China.
关键词：
population-ecology-energy-digital economy;coupling coordination development;spatial-temporal evolution;spatial autocorrelation;driving factors;Yangtze River Basin
摘要：
Against the backdrop of globalization and ecological civilization, this study aims to analyze the patterns of system coupling coordination development in the Yangtze River Basin under the interacting influences of population growth, ecological conservation, energy utilization, and digital economic development. Using a multisource model, this paper explores the state of coordinated development, spatial–temporal evolution characteristics, and influencing factors in the Yangtze River Basin from 2011 to 2020. The results indicate the following: (1) The overall degree of coupling coordination in the Yangtze River Basin shows better performances in the eastern coastal areas compared to the central and western regions. Over time, the spatial autocorrelation of coupling and coordination increases, exhibiting a significant spatial clustering trend. (2) The Moran’s I index increased from 0.327 to 0.370, with high–high clusters primarily distributed in economically developed coastal provinces, while low–low clusters were observed in remote provinces in the central and western regions, revealing regional development imbalance issues. (3) The driving force analysis shows that green coverage and GDP are the core factors influencing the spatial differentiation of coupling coordinated development. Factors such as the urbanization rate, nighttime light index, and energy consumption had significant impacts in certain years but are generally considered minor factors. The results of this study not only contribute to understanding the dynamic mechanisms of regional coupling and development but also provide a scientific basis for formulating regional coordinated development policies, promoting the achievement of win–win goals of economic growth and ecological civilization in the Yangtze River Basin and similar regions.
作者机构：
[Luo, Qiao; Yu, Hongbing] Hunan City Univ, Coll Architecture & Urban Planning, Yiyang 413000, Peoples R China.;[Luo, Qiao; Yu, Hongbing] Hunan City Univ, Coll Architecture & Urban Planning, Lab Key Technol Digital Urban Rural Spatial Planni, Yiyang 413000, Peoples R China.;[Li, Yong] Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Atmospher Boundary Layer Phys & Atmo, Beijing 100029, Peoples R China.;[Jiang, Shufang; Cao, Xueyou] Forestry Bur Yiyang City, Yiyang 410004, Peoples R China.
通讯机构：
[Li, Y ] C;Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Atmospher Boundary Layer Phys & Atmo, Beijing 100029, Peoples R China.
关键词：
South Dongting Lake Nature Reserve;blue space;green space;precipitation;air temperature
摘要：
In recent years, the water level of the Dongting Lake (DTL) has been continuously low, and the wetland area and landscape pattern have changed significantly. Considering the obvious spatial heterogeneity of water regime changes in different waters of the DTL, this paper takes two core areas of the South Dongting Lake Nature Reserve (SDLNR) as study areas and analyzes the spatial distribution characteristics of the wetland blue–green landscape patterns by using remote sensing image data and hydrological and meteorological data. The multi-scale correlation between runoff, precipitation, temperature, and evapotranspiration in the SDLNR was studied via cross-wavelet transform analysis. The results show the following: (1) The change in the blue–green spatial patterns in different regions in different periods is inconsistent, and this inconsistency is related to the topography, climate, and human activities in each region; (2) there are seasonal fluctuations in precipitation, air temperature, and evapotranspiration in the SDLNR. Among them, the annual mean temperature shows a rising trend and passes the significance test with 95% confidence, while the annual mean precipitation and annual mean evapotranspiration show no significant change trend; and (3) our Pearson correlation analysis and cross-wavelet change results show that precipitation and temperature are strongly correlated with runoff, with a resonance period of 8–16 months, while the correlation between evapotranspiration and runoff is not significant. We recommend that policymakers establish an effective early warning system and make plans to store water through micro-terrain transformation in possible climate change treatments and strategies.
关键词：
landscape architecture;experiential learning education;cultural services;rural cultural revitalization;rural landscape planning
摘要：
Culture is never static. In modern society, Chinese rural areas are constantly intertwined and dislocated in the processes of traditional culture and modern civilization, involving the equitable and mutually beneficial relationship between people and natural resources and the reconstruction of regional cultural genres in specific periods. The rural humanities and natural resources are important carriers of cultural services. Therefore, research on experiential learning education is important for realizing local cultural revitalization. The efforts of revitalization and renewal of cultural services in rural ecosystems can not only inherit traditional culture, but also promote ecological protection, enhance villagers’ scientific literacy, and realize a harmony between humans and nature. This paper takes Daheping Village in the Hunan Province as an example, combining the ideas of natural education and landscape thinking to explore new ways to activate and enhance the value of rural cultural services from the perspectives of cultural connotations, spatial patterns, basic facilities, and route design. This study provides a new practical guidance paradigm for rural cultural revitalization and future human settlement improvement.
作者机构：
[Hui Tang; Deng Pan; Jie Yan; Yu Chen; Chen, Yu] Hunan City Univ, Coll Architecture & Urban Planning, Yiyang, Peoples R China.;[Hui Tang; Yu Chen; Chen, Yu] Key Lab Key Technol Digital Urban Rural Spatial Pl, Yiyang, Peoples R China.;[Hui Tang] Key Lab Urban Planning Informat Technol Hunan Prov, Yiyang, Peoples R China.;[Yu Chen; Chen, Yu] Hunan Univ, Sch Architecture & Planning, Changsha, Peoples R China.
通讯机构：
[Chen, Y ] H;Hunan City Univ, Coll Architecture & Urban Planning, Yiyang, Peoples R China.;Key Lab Key Technol Digital Urban Rural Spatial Pl, Yiyang, Peoples R China.;Hunan Univ, Sch Architecture & Planning, Changsha, Peoples R China.
关键词：
Health equality;medical health resource allocating;gini coefficient;Changsha City
摘要：
This paper analyzes the healthcare level and the evolution of spatial and temporal pattern of each district and county in Changsha City by using the entropy value method based on the statistics of the number of healthcare facilities, beds, and health technicians in Changsha City from 2010 to 2018, and evaluates the fairness and trend of healthcare resource distribution in Changsha City over the years in terms of per capita level through the calculation of the Gini coefficient. The results show that the medical level in the southern part of Changsha City is better, the medical level in the northern part is weaker, there are significant differences in the healthcare level between districts and counties and the differences between districts and counties are decreasing year by year; there is a lack of fairness in the level of healthcare technicians in each district and counties in comparison with the level of the number of health care institutions and beds. In this regard, suggestions are made to improve the level of protection of health technical personnel, to equalize the distribution of the internal components of health care, and to improve the construction of the health care system and resource sharing.
期刊：
PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-MUNICIPAL ENGINEER,2024年177(3):130-143 ISSN：0965-0903
作者机构：
Department Chair of Urban Design, School of Architecture and Urban Planning, Hunan City University, Yiyang, China;Hunan Provincial Key Laboratory of Urban Planning Information Technology, Yiyang, China (corresponding author: yuchenhu@yandex.com );[Shaoyao He] Professor, School of Architecture and Planning, Hunan University, Changsha, China;[Mengmiao Zhang] PhD student, School of Architecture and Planning, Hunan University, Changsha, China;[Yan Cai] Lecturer, College of Humanities, Hunan City University, Yiyang, Hunan, China
摘要：
In response to elevated living standards and evolving recreational values, public sports facilities have become a focal point. This study, targeting the central districts of Yiyang City across 17 neighborhoods, integrates questionnaire surveys, in-depth interviews, and geographic information system analysis to address the diversified needs in sports infrastructure. It reveals a discrepancy characterised by uniform facility types and flawed layouts, notably in Heshan and Ziyang, that fail to satisfy the diversified demands of residents. Consequently, the research introduces a bottom-up strategy, emphasising the need for facility selections and spatial layouts informed by community needs. Furthermore, it highlights the importance of demographic factors such as age, income, and education in guiding facility placement strategies to accommodate a broad spectrum of users. By doing so, the study contributes a novel, resident-focused framework to the discourse on public sports facilities, promoting sustainable and inclusive urban sports environment development.
期刊：
Frontiers in Public Health,2024年12:1376518 ISSN：2296-2565
通讯作者：
Ao, RJ
作者机构：
[Tang, Hui] Hunan City Univ, Coll Architecture & Urban Planning, Yiyang, Hunan, Peoples R China.;[Tang, Hui; Ao, Rongjun] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Hubei, Peoples R China.;[Tang, Hui] Key Lab Key Technol Digital Urban Rural Spatial Pl, Yiyang, Hunan, Peoples R China.;[Li, Yilei] Hunan Univ Technol, Coll Urban & Environm Sci, Zhuzhou, Peoples R China.
通讯机构：
[Ao, RJ ] C;Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Hubei, Peoples R China.
关键词：
China;health productivity of health resources;influencing factors;prefecture-level regions;spatial and temporal patterns
摘要：
There is always a contradiction between the limited health resources and the unlimited demand of the population for health services, and only by improving the productivity of health resources can the health level of the population be improved as much as possible. Using prefecture-level administrative regions as spatial units, the paper analyzes the spatial pattern and changes of health productivity of health resources in China from 2000 to 2010, and uses a spatial panel Tobit model to examine the effects of factors such as technical level of health institutions, health service accessibility, public health policies and ecological environment quality on health productivity of health resources. The results show that with the Hu Huanyong line as the dividing line, the spatial heterogeneity of “high in the southeast and low in the northwest” in the health productivity of China's health resources is clear; as the regional differences narrow, the spatial correlation increases, and the spatial pattern of “overall dispersion and partial agglomeration” becomes more obvious. The fitting results of the spatial Durbin model reveal the direction and degree of influence of local and adjacent factors on the production efficiency of health resources. The positive influence of technical level of local health institutions and the accessibility of health services, the literacy level and the ability to pay for health services of residents in adjacent areas, the degree of urbanization of regional health resource allocation, climate suitability and the quality of the atmospheric environment are significant. And the negative influence of local residents' literacy and ability to pay for health services, the technical level of health institutions in adjacent areas and the degree of medicalization of health resource allocation are also significant. The influence of the degree of medicalization of local health resource allocation and the accessibility of health services in adjacent areas are significantly spatial-heterogeneous.
期刊：
Stochastic Environmental Research and Risk Assessment,2024年38(7):2563-2579 ISSN：1436-3240
通讯作者：
Isik, C
作者机构：
[Long, Tianxiang] Hunan City Univ, Coll Architecture & Urban Planning, Yiyang 413000, Peoples R China.;[Cui, Xiangying] Hong Kong Univ Sci & Technol, Hong Kong 999077, Peoples R China.;[Yan, Jiale] Irvine Valley Coll, Irvine, CA 92618 USA.;[Isik, Cem; Isik, C] Anadolu Univ, Fac Econ & Adm Sci, Dept Econ, Eskisehir, Turkiye.;[Isik, Cem; Irfan, Muhammad; Isik, C] Lebanese Amer Univ, Adnan Kassar Sch Business, Byblos, Lebanon.
摘要：
AbstractIncreased risks of economic policy uncertainty and overexploitation of natural resources exist in China. At the same time, the growth rate of urban residents’ consumption has generally declined. The paper analyses the role of economic policy uncertainty (EPU) and natural resource exploitation on the urban residents’ consumption in China. Based on the data from the first quarter of 2002 to the third quarter of 2021, the paper uses a nonlinear autoregressive distributed lag model to verify the asymmetric effects. Then the paper constructs a time-varying parameter vector autoregressive model with stochastic volatility term to analyze the nonlinear responses. Impulse response analysis was used to further explain the relationship between the three. The negative impact of rising EPU on urban residents’ consumption is larger than its reduction. Negative shocks to natural resource development increase the urban residents’ consumption. Positive shocks reduce the urban residents’ consumption. There is a time-varying non-linear effect of EPU and natural resource development on urban residents’ consumption in China. The negative impact of EPU on urban consumption has been further exacerbated by major crises such as the financial crisis, COVID-19 and the post-crisis period. The negative impact of natural resource development diminished after the government introduced industrial upgrading policies and environmental regulations. This study provides constructive suggestions for the optimization of economic policies and the improvement of urban consumption. This study also enriches consumer theory and provides new evidence for the resource curse hypothesis.
