The accuracy of photovoltaic(PV)power prediction is significantly influenced by meteorological and environmental factors.To enhance ultra-short-term forecasting precision,this paper proposes an interpretable feedback ...The accuracy of photovoltaic(PV)power prediction is significantly influenced by meteorological and environmental factors.To enhance ultra-short-term forecasting precision,this paper proposes an interpretable feedback prediction method based on a parallel dual-stream Temporal Convolutional Network-Bidirectional Long Short-Term Memory(TCN-BiLSTM)architecture incorporating a spatiotemporal attention mechanism.Firstly,during data preprocessing,the optimal historical time window is determined through autocorrelation analysis while highly correlated features are selected as model inputs using Pearson correlation coefficients.Subsequently,a parallel dual-stream TCN-BiLSTM model is constructed where the TCN branch extracts localized transient features and the BiLSTM branch captures long-term periodic patterns,with spatiotemporal attention dynamically weighting spatiotemporal dependencies.Finally,Shapley Additive explanations(SHAP)additive analysis quantifies feature contribution rates and provides optimization feedback to the model.Validation using operational data from a PV power station in Northeast China demonstrates that compared to conventional deep learning models,the proposed method achieves a 17.6%reduction in root mean square error(RMSE),a 5.4%decrease in training time consumption,and a 4.78%improvement in continuous ranked probability score(CRPS),exhibiting significant advantages in both prediction accuracy and generalization capability.This approach enhances the application effectiveness of ultra-short-term PV power forecasting while simultaneously improving prediction accuracy and computational efficiency.展开更多
As metropolitan areas expand spatially,they encounter constraints imposed by the fixed daily time budget.Rail transit enhances transport efficiency,reduces costs,and facilitates the formation of a“transit economic fi...As metropolitan areas expand spatially,they encounter constraints imposed by the fixed daily time budget.Rail transit enhances transport efficiency,reduces costs,and facilitates the formation of a“transit economic field”centered on rail networks,thereby alleviating such temporal-spatial pressures.This paper adopts an integrated temporal-spatial analytical framework.Following a conceptual clarification of the transit economic field,it dissects the mechanisms through which rail transit improves mobility and examines how this field influences urban spatial patterns,temporal dynamics,and their interrelationships.It constructs a theoretical framework to explain the co-development of transit economic fields and cities,supplemented by empirical case studies.The key findings are as follows:Firstly,the transit economic field represents a high-density development model that expands both horizontally and vertically around rail networks.It mitigates temporal-spatial conflicts.Secondly,with rail networks as the core,the field integrates diverse spatial functions,facilitating the establishment of economic connections and stabilizing temporal-spatial relationships.Thirdly,the transit economic field contributes to the preservation of urban natural ecosystems and enhances urban livability.Overall,this research can provide insights for promoting rail transit-oriented development transitions in large cities and urban agglomerations.展开更多
[Objective] This study aimed to analyze the temporal-spatial variation of Inner Mongolian grassland degradation during past three decades. [Method] The dis- tribution characteristics of grassland were described by lan...[Objective] This study aimed to analyze the temporal-spatial variation of Inner Mongolian grassland degradation during past three decades. [Method] The dis- tribution characteristics of grassland were described by land use types supervised classification with TM/ETM. Then, temporal-spatial changes of grassland coverage were quantified by the mean of maximum vegetation coverage in last 30 years. Lastly, the grassland degradation reasons were explored through statistic analysis between the grassland coverage and precipitation, temperature and grazing intensity. [Result] The grassland degradation index of Inner Mongolia was increased from 1.38 to 1.68, and the smallest was 1.28 in 2005s. Grassland degradation and improve- ment were concurrent after 1980s, but grassland degradation was the major change trend for Inner Mongolia grassland. The area of grassland degradation was enlarged from 18.08×10^4 km2 in 1980s to 22.47×10^4 km2 in 2010s on the whole and distribu- tion range was shifted from central-eastern to west in Inner Mongolia that mainly distributed on Hulun Buir and Xilin Gol grassland in 1980s and Ordos and Alax grassland in 2010s. The grassland area of degradation had a rising trend form 1980s to 1995s, then reduced to 10.8x104 km2 in 2005s, and decreased in 2010s, which mainly speared in the west of Xilin Gol grassland. [Conclusion] Inner Mongo-lian grassland degradation were become more seriously in last 30 years because that temperature, precipitation and graze intensities change, which not performance on decreasing coverage but grassland areas.展开更多
[Objective] The aim was to study on temporal-spatial distribution model of cold chain logistics for vegetables. [Method] Broccoli was taken as an example. Detailedly, time-space distribution model of cold chain logist...[Objective] The aim was to study on temporal-spatial distribution model of cold chain logistics for vegetables. [Method] Broccoli was taken as an example. Detailedly, time-space distribution model of cold chain logistics for broccoli was proposed from standpoints of costs and benefits based on changes of time and space, and a comprehensive evaluation was made on timeliness, efficiency, risks, added- value of products and satisfaction of information in cold-chain logistics. [Result] The efficiency of cold chain logistics for vegetable can be greatly improved by temporal- spatial distribution model of cold chain logistics. [Conclusion] Costs and benefits of vegetables in temporal-apstial distribution could be evaluated by the model.展开更多
目的探究MR 3D CUBE与常规磁共振成像(MRI)在膝关节前交叉韧带损伤中的应用价值。方法选取2022年1月至2024年4月本院收治的136例膝关节前交叉韧带损伤患者,根据患者损伤程度分为Ⅰ级、Ⅱ级和Ⅲ级;患者均进行MR 3D CUBE与常规MRI检查;Ka...目的探究MR 3D CUBE与常规磁共振成像(MRI)在膝关节前交叉韧带损伤中的应用价值。方法选取2022年1月至2024年4月本院收治的136例膝关节前交叉韧带损伤患者,根据患者损伤程度分为Ⅰ级、Ⅱ级和Ⅲ级;患者均进行MR 3D CUBE与常规MRI检查;Kappa检验分析MR 3D CUBE、常规MRI与关节镜诊断的一致性;以关节镜检查结果为金标准,采用四格表分析MR 3D CUBE与常规MRI对膝关节前交叉韧带不同损伤分级的诊断价值;膝关节前交叉韧带损伤治疗效果的影响因素采用Logistic回归分析。结果MR 3D CUBE、常规MRI与关节镜诊断的一致性较好(Kappa=0.664、0.832,P<0.05)。MR 3D CUBE在诊断膝关节前交叉韧带损伤Ⅰ级时准确度为91.91%,Ⅱ级时准确度为91.18%,Ⅲ级时准确度为94.85%;常规MRI在诊断膝关节前交叉韧带损伤Ⅰ级时准确度为85.29%,Ⅱ级时准确度为83.09%,Ⅲ级时准确度为87.50%,MR 3D CUBE在诊断膝关节前交叉韧带损伤Ⅲ级时准确度显著高于常规MRI(P<0.05)。不良组和良好组病程和既往损伤比较有差异(P<0.05)。多因素Logistic回归分析得知,病程和既往损伤是影响膝关节前交叉韧带损伤患者治疗效果的危险因素(P<0.05)。结论MR 3D CUBE与常规MRI均能诊断膝关节前交叉韧带损伤,但MR 3D CUBE诊断效能高于常规MRI,可在临床应用。展开更多
In global change research, changes of soil organic carbon (SOC) reservoirs intropical and subtropical regions are still unknown. The temporal-spatial variability of SOC stockswas determined in a basin of over 579 km^2...In global change research, changes of soil organic carbon (SOC) reservoirs intropical and subtropical regions are still unknown. The temporal-spatial variability of SOC stockswas determined in a basin of over 579 km^2 in subtropical China from 1981to 2002. ArcGIS8.l softwarewas utilized for spatial analysis of semivariance, ordinary kriging (OK), and probability kriging(PK). Grid and hierarchical approaches were employed for the sampling scenario in 2002 with 106Global Position System (GPS) established spots sampled. Bulk topsoil samples (0—30 cm) werecollected at three random sites on each spot. The SOC content for 1981 came from the SOC map of theSecond National Soil Survey. Geostatistical results of the nugget to sill ratio (0.215-0.640)in therehabilitating ecosystem indicated a moderate spatial dependence for SOC on this large scale. Therange of SOC changed from 2.04 km in 1981 to 7.15 km in 2002. The mean topsoil SOC increased by 4.6%from 10.63 g kg^(-1) (1981) to 11.12 g kg^(-1)(2002). However, during this 21-year period 25.2% ofthe total basin area experienced a decrease in SOC. Also, the probability kriging results showedthat the geometric mean probabilities of SOC <= 6.0 g kg^(-1), <= 11.0 g kg^(-1) and > 15.0 gkg^(-1) were 0.188, 0.534 and 0.378, respectively in 2002, comparing to 0.234, 0.416 and 0.234 inthat order in 1981, respectively. The SOC storage in the topsoil increased by 17.0% during this timewith the main increase occurring in forests and cultivated land,which amounted to 82.5% and 17.0%of the total increase, respectively.展开更多
Sand-dust storm is a special natural disaster that frequently occurs in deserts and their surrounding areas. With the data published onSurface Meteorological Monthly Bulletin andSurface Chart during 1971–1996, the te...Sand-dust storm is a special natural disaster that frequently occurs in deserts and their surrounding areas. With the data published onSurface Meteorological Monthly Bulletin andSurface Chart during 1971–1996, the temporal-spatial distribution and annual variation of sand-dust storms are analyzed on the basis of the case study of atmospheric processes. Furthermore, the tracks and source areas of sand-dust storms are determined with the aid of GIS. The results show that except some parts of Qinghai Province and Inner Mongolia as well as Beijing, sand-dust storms decrease apparently in time and space in recent decades in China. Sand-dust storms occur most frequently in spring, especially in April. According to their source areas, sand-dust storms are classified into two types, i.e., the inner-source and outer-source sand-dust storms. Most of the outer-source sand-dust storms move along the north and west tracks. The north-track outer-source sand-dust storms always intrude into China across the Sino-Mongolian border from Hami, a city in the eastern part ofXinjiang, to Xilin Gol, a league in Inner Mongolia, while the west-track ones intrude into China from both southern and northern Xinjiang. The source lands of inner-source sand-dust storms concentrate in the Taklimakan Desert and its surrounding areas in southern Xinjiang, southern part of the Junggar Basin in north of Xinjiang, the Hexi Corridor in western Gansu Province, the dry deserts of Inner Mongolia and the Qaidam Basin in Qinghai.展开更多
Heavy metal contamination in soils has been of wide concern in China in the last several decades. The heavy metal contamination was caused by sewage irrigation, mining and inappropriate utilization of various agrochem...Heavy metal contamination in soils has been of wide concern in China in the last several decades. The heavy metal contamination was caused by sewage irrigation, mining and inappropriate utilization of various agrochemicals and pesticides and so on. The Shenyang Zhangshi irrigation area （SZIA） in China is a representative area of heavy metal contamination of soils resulting from sewage irrigation for about 30 years duration. This study investigated the spatial distribution and temporal variation of soil cadmium contamination in the SZIA. The soil samples were collected from the SZIA in 1990 and 2004; Cd of soils was analyzed and then the spatial distribution and temporal variation of Cd in soils was modelled using kriging methods. The kriging map showed that long-term sewage irrigation had caused serious Cd contamination in topsoil and subsoil. In 2004, the Cd mean concentrations were 1.698 and 0.741 mg/kg, and the maxima 10.150 and 7.567 mg/kg in topsoils （0-20 cm） and subsoils （20-40 cm） respectively. These values are markedly more than the Cd levels in the second grade soil standard in China. In 1990, the Cd means were 1.023 and 0.331 mg/kg, and the maxima 9.400 and 3.156 mg/kg, in topsoils and subsoils respectively. The soil area in 1990 with Cd more than 1.5 mg/kg was 2701 and 206.4 hnl2 in topsoils and subsoils respectively; and in 2004, it was 7592 and 1583 hm^2, respectively. Compared with that in 1990, the mean and maximum concentration of Cd, as well as the soil area with Cd more than 1.5 mg/kg had all increased in 2004, both in topsoils and subsoils.展开更多
The Huaihe River basin of Anhui is not only a transitional zone of physical geography, but also a convergent area of many cultures in China. It is one of the sensitive ecotones to global changes and the birthplace of ...The Huaihe River basin of Anhui is not only a transitional zone of physical geography, but also a convergent area of many cultures in China. It is one of the sensitive ecotones to global changes and the birthplace of Chinese civilization. Using the field archaeological data and the sporo-pollens and the age data of the drilling cores, we analysed Neolithic cultural development and environmental evolution in the Huaihe River basin of Anhui. According to the combination of some research results in archaeology with environmental evolution research, this paper discusses the relationship between culture and environment in the Huaihe River basin of Anhui. The Neolithic cultural development was strongly impacted by the environmental change. The primitive culture （Shishanzi） was developed in the beginning of the Holocene Megathermal Period with distinct regional feature of the culture. From 6.5 kaBP to 5.5 kaBP, the climate changed warmer and wetter. The frequent occurrence of flood and waterlog due to such a climate regime and high sea level caused the earth＇s surface environment deteriorated in the Huaihe River basin of Anhui and the interruption of the Neolithic cultural development, hence a lack of archaeological sites. From 5.5 kaBP to 4.0 kaBP, the climate changed from wet to dry, the natural environment was propitious to human survival. Dawenkou Culture and Longshan Culture flourished in this period. The Neolithic cultural development, the number of the sites and their distribution characteristics of the sites in the study area differed apparently from those in Central China and Shandong Province.展开更多
The long-term temporal and spatial dynamics of marine coastal water quality in Tolo Harbor, Hong Kong were explored. The Harbor is divided into three zones represented as Harbor, Buffer, and Channel Subzones. The time...The long-term temporal and spatial dynamics of marine coastal water quality in Tolo Harbor, Hong Kong were explored. The Harbor is divided into three zones represented as Harbor, Buffer, and Channel Subzones. The time range for the study covers the period from the 1970s to the 1990s. The selected indicators for the comprehensive assessment of water quality consist of physical, chemical and biological aspects, including suspended solids(SS), Secchi disk depth(SD), 5-day biochemical oxygen demand(BOD\-5), total nitrogen(TN), total phosphorus(TP), faecal coliform, chlorophyll-a(Chl-a), and the number of red tide occurrences. The results indicated the presence of obvious temporal and spatial trends with regard to changes in water quality. Spatially, water quality in the Channel Subzone is the best, while that in the Harbor Subzone is the worst. On a temporal basis, the average trend from bad to good was 1980s>1990s>1970s as indicated by most of the selected water quality indicators. Water quality during the late 1980s reached its worst level with the lowest SD, the highest BOD\-5, TN, TP, Chl-a concentrations, and the number of red tide occurrences. These long-term temporal-spatial water quality trends were also found in other studies of the Tolo Harbor. The large quantity of pollutants produced as a result of increasing population, industrial and commercial actives, and urbanization and industrialization trends in both Shatin and Tai Po seem to be primarily responsible for the changes in marine coastal water quality.展开更多
To enhance the resolution of parameter estimation with limited samples received by a short passive array,an iterative nonparametric algorithm for estimating the frequencies and direction-of-arrivals(DOAs)of signals is...To enhance the resolution of parameter estimation with limited samples received by a short passive array,an iterative nonparametric algorithm for estimating the frequencies and direction-of-arrivals(DOAs)of signals is proposed.The cost function is constructed using 12-norm Gaussian entropy combined with an additional constraint,12-norm constraint or linear constraint.By minimizing the cost functions in the temporal and the spatial dimensions using corresponding iteration algorithms respectively,the sparse discrete Fourier transforms(DFTs)of temporal and spatial samples are obtained to represent the extrapolated sequences with much larger sizes than the original samples.Then frequency and angle estimates are obtained by performing the traditional simple methods on the extrapolated sequences.It is shown that the proposed algorithm offers increased resolution and significantly reduced sidelobes compared with the periodogram and beamforming based methods.And it achieves high precision compared with the high-resolution method with lower computational burden.Some numerical simulations and real data processing results are presented to verify the effectiveness of the method.展开更多
Background:The Yangtze River floodplain provides important wintering habitats for Hooded Cranes(Grus monacha) in China.Fluctuations in the water level change foraging habitat and food availability,affecting their temp...Background:The Yangtze River floodplain provides important wintering habitats for Hooded Cranes(Grus monacha) in China.Fluctuations in the water level change foraging habitat and food availability,affecting their temporal-spatial patterns of foraging activities.It is of considerable importance to investigate the effect of these fluctuations on food availability for wintering Hooded Cranes and their foraging response to these changes.Understanding their behavior patterns is beneficial in protecting the wintering crane population and restoring their wintering habitats.Methods:A field survey of the winter behavior of cranes was carried out at Shengjin Lake from November in 2013 to April in 2014.Habitat variables,as well as the spatial distribution and behavior patterns of wintering cranes at their foraging sites during five stages of water level fluctuation were collected.Based on this data we analyzed the relationship of foraging behavior relative to water level fluctuations and habitat types.Results:The foraging habitats used by Hooded Cranes varied at the different water level stages.As the water level decreased,the use of meadows and mudflats increased.When the water dropped to its lowest level,the use by the Hooded Crane in the mudflats reached a peak.There were statistically significant differences in time budget in the three types of habitats over the five stages of the water level.In the mudflats,the foraging behavior and maintenance behavior varied significantly with the water level,while the alert behavior showed little variation.Analysis of a generalized linear model showed that the five water level stages and three habitat types had a significant effect on foraging behavior,while the combined effect of these two variables was significant on the foraging time budget and the length of foraging activity of the Hooded Crane.Conclusions:With the decrease in the water level,the use of mudflats by Hooded Cranes increased correspondingly.Food availability in different habitats was affected by changes in the water level.The Hooded Crane adjusted its foraging patterns and made full use of the three available types of habitat in order to acquire enough food in response to fluctuations in the water level.展开更多
This study applied GIS-based statistical analytic techniques to investigate the influence of accident Severity Index(SI)on temporal-spatial patterns of accident hotspots related to the specific time intervals of day a...This study applied GIS-based statistical analytic techniques to investigate the influence of accident Severity Index(SI)on temporal-spatial patterns of accident hotspots related to the specific time intervals of day and seasons.Road Traffic Accident(RTA)data in 3 years(2015-2017)in Hanoi,Vietnam were used to analyze and test this approach.Firstly,the RTA data were divided into four seasons in accordance with Hanoi's weather conditions and the time intervals such as the daytime,nighttime,or peak hours.Then,the Kernel Density Estimation(KDE)method was applied to analyze hotspots according to the time intervals and seasons.Finally,the results were presented by using the comap technique.This study considered both analyses with and without SI.The accident SI measures the seriousness of an accident.The approach method is to give higher weights to the more serious accidents,but not with the extremely high values calculated on a direct rate to the accident expenditures.The results showed that both analyses determined the relatively similar hotspots,but the rankings of some hotspots were quite different due to the integration of SI.It is better to take into account SI in determining RTA hotspots because the gained results are more precise and the rankings of hotspots are more accurate.From there,the traffic authorities can easily understand the causes behind each accident and provide reasonable solutions to solve the most dangerous hotspots in case of limited budget and resources appropriately.This is also the first study about this issue in Vietnam,so the contribution of the article will help the traffic authorities easily solve this problem not only in Hanoi but also in other cities.展开更多
With the increasing proportion of wind power integration, the volatility of wind power brings huge challenges to the safe and stable operation of the electric power system. At present, the indexes commonly used to eva...With the increasing proportion of wind power integration, the volatility of wind power brings huge challenges to the safe and stable operation of the electric power system. At present, the indexes commonly used to evaluate the volatility of wind power only consider its overall characteristics, such as the standard deviation of wind power, the average of power variables, etc., while ignoring the detailed volatility of wind power, that is, the features of the frequency distribution of power variables. However, how to accurately describe the detailed volatility of wind power is the key foundation to reduce its adverse influences. To address this, a quantitative method for evaluating the detailed volatility of wind power at multiple temporal-spatial scales is proposed. First, the volatility indexes which can evaluate the detailed fluctuation characteristics of wind power are presented, including the upper confidence limit, lower confidence limit and confidence interval of power variables under the certain confidence level. Then, the actual wind power data from a location in northern China is used to illustrate the application of the proposed indexes at multiple temporal(year–season–month–day) and spatial scales(wind turbine–wind turbines–wind farm–wind farms) using the calculation time windows of 10 min, 30 min, 1 h, and 4 h. Finally, the relationships between wind power forecasting accuracy and its corresponding detailed volatility are analyzed to further verify the effectiveness of the proposed indexes. The results show that the proposed volatility indexes can effectively characterize the detailed fluctuations of wind power at multiple temporal-spatial scales. It is anticipated that the results of this study will serve as an important reference for the reserve capacity planning and optimization dispatch in the electric power system which with a high proportion of renewable energy.展开更多
Road silt loading(sL)is an important parameter in the fugitive road dust(FRD)emissions.In this study,the improved Testing Re-entrained Aerosol Kinetic Emissions from Roads(TRAKER)combined with the AP-42 method was fir...Road silt loading(sL)is an important parameter in the fugitive road dust(FRD)emissions.In this study,the improved Testing Re-entrained Aerosol Kinetic Emissions from Roads(TRAKER)combined with the AP-42 method was firstly developed to quickly measure and estimate the sLs of paved roads in Beijing,China.The annual average sLs in Beijing was 0.59±0.31 g/m^(2)in 2020,and decreased by 22.4%compared with that in 2019.The seasonal variations of sLs followed the order of spring>winter>summer>autumn in the two years.The seasonal mean road sLs on the same type road in the four seasons presented a decline trend from^(2)019 to 2020,especially on the Expressway,decreasing 47.4%-72.7%.The road sLs on the different type roads in the same season followed the order of Major arterial∼Minor arterial∼Branch road>Express road,and Township road∼Country highway>Provincial highway∼National highway.The emission intensities of PM10 and PM_(2.5)from FRD in Beijing in 2020 were lower than those in 2019.The PM10 and PM_(2.5)emission intensities at the four planning areas in the two years all presented the order of the capital functional core area>the urban functional expansion area>the urban development new area>the ecological conservation and development area.The annual emissions of PM10 and PM_(2.5)from FRD in Beijing in 2020 were 74,886 ton and 18,118 ton,respectively,decreasing by∼33.3%compared with those in 2019.展开更多
Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time se...Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.展开更多
By using the variation coefficient,Gini coefficient and Theil coefficient,this paper makes preliminary exploration of temporalspatial change features and driving mechanism for regional differences of domestic tourism ...By using the variation coefficient,Gini coefficient and Theil coefficient,this paper makes preliminary exploration of temporalspatial change features and driving mechanism for regional differences of domestic tourism in China from 1995 to 2009.According to the results,we drew the following conclusions:(1)The regional difference of domestic tourism in China tends to be narrowing generally,and is less than that of inbound tourism,playing an important role in narrowing the overall gap of regional tourism in China.(2)The regional internal difference features:inter-provincial difference in the eastern region and difference among the eastern,central and western regions are comparatively obvious and demonstrate a significantly shrinking tendency,the change tendency is consistent with the change tendency of overall difference and exercises a decisive role in overall difference,whereas the inter-provincial difference in the central and western regions is small and relatively stable,having less influence on the overall difference.(3)The temporal-spatial change in regional difference is featured by:low-level provinces occupy a majority and are concentrated in the central and western regions,showing a tendency of narrowing difference;high-level provinces are concentrated in the eastern region,showing a tendency of spreading to the central and western regions;spatial pattern of regional difference demonstrates 4 types,i.e."proliferation type","polarization type","quiescence type"and"collapse type."(4)The driving force for regional difference of domestic tourism in China comes down to 3 aspects:regional socio-economic attribute,regional transport accessibility level and regional development policy.展开更多
基金funded by the National Natural Science Foundation of China(NSFC)(No.62066024)funded by Basic Scientific Research Projects of Higher Education Institutions in Liaoning Province(LJ212411632063)the National Undergraduate Training Program for Innovation and Entrepreneurship(S202511632045).
文摘The accuracy of photovoltaic(PV)power prediction is significantly influenced by meteorological and environmental factors.To enhance ultra-short-term forecasting precision,this paper proposes an interpretable feedback prediction method based on a parallel dual-stream Temporal Convolutional Network-Bidirectional Long Short-Term Memory(TCN-BiLSTM)architecture incorporating a spatiotemporal attention mechanism.Firstly,during data preprocessing,the optimal historical time window is determined through autocorrelation analysis while highly correlated features are selected as model inputs using Pearson correlation coefficients.Subsequently,a parallel dual-stream TCN-BiLSTM model is constructed where the TCN branch extracts localized transient features and the BiLSTM branch captures long-term periodic patterns,with spatiotemporal attention dynamically weighting spatiotemporal dependencies.Finally,Shapley Additive explanations(SHAP)additive analysis quantifies feature contribution rates and provides optimization feedback to the model.Validation using operational data from a PV power station in Northeast China demonstrates that compared to conventional deep learning models,the proposed method achieves a 17.6%reduction in root mean square error(RMSE),a 5.4%decrease in training time consumption,and a 4.78%improvement in continuous ranked probability score(CRPS),exhibiting significant advantages in both prediction accuracy and generalization capability.This approach enhances the application effectiveness of ultra-short-term PV power forecasting while simultaneously improving prediction accuracy and computational efficiency.
基金Hubei Social Science Foundation Project“Research on the Relationship Between Rail Transit and Intensive and Sustainable Development of Large Cities”(2020052)。
文摘As metropolitan areas expand spatially,they encounter constraints imposed by the fixed daily time budget.Rail transit enhances transport efficiency,reduces costs,and facilitates the formation of a“transit economic field”centered on rail networks,thereby alleviating such temporal-spatial pressures.This paper adopts an integrated temporal-spatial analytical framework.Following a conceptual clarification of the transit economic field,it dissects the mechanisms through which rail transit improves mobility and examines how this field influences urban spatial patterns,temporal dynamics,and their interrelationships.It constructs a theoretical framework to explain the co-development of transit economic fields and cities,supplemented by empirical case studies.The key findings are as follows:Firstly,the transit economic field represents a high-density development model that expands both horizontally and vertically around rail networks.It mitigates temporal-spatial conflicts.Secondly,with rail networks as the core,the field integrates diverse spatial functions,facilitating the establishment of economic connections and stabilizing temporal-spatial relationships.Thirdly,the transit economic field contributes to the preservation of urban natural ecosystems and enhances urban livability.Overall,this research can provide insights for promoting rail transit-oriented development transitions in large cities and urban agglomerations.
基金Supported by National Program on Key Basic Research Project of China (2011CB403206)National Key Technology Research and Development Program during the 12~(th) Five-year Plan Period of China(2012BAC19B04)~~
文摘[Objective] This study aimed to analyze the temporal-spatial variation of Inner Mongolian grassland degradation during past three decades. [Method] The dis- tribution characteristics of grassland were described by land use types supervised classification with TM/ETM. Then, temporal-spatial changes of grassland coverage were quantified by the mean of maximum vegetation coverage in last 30 years. Lastly, the grassland degradation reasons were explored through statistic analysis between the grassland coverage and precipitation, temperature and grazing intensity. [Result] The grassland degradation index of Inner Mongolia was increased from 1.38 to 1.68, and the smallest was 1.28 in 2005s. Grassland degradation and improve- ment were concurrent after 1980s, but grassland degradation was the major change trend for Inner Mongolia grassland. The area of grassland degradation was enlarged from 18.08×10^4 km2 in 1980s to 22.47×10^4 km2 in 2010s on the whole and distribu- tion range was shifted from central-eastern to west in Inner Mongolia that mainly distributed on Hulun Buir and Xilin Gol grassland in 1980s and Ordos and Alax grassland in 2010s. The grassland area of degradation had a rising trend form 1980s to 1995s, then reduced to 10.8x104 km2 in 2005s, and decreased in 2010s, which mainly speared in the west of Xilin Gol grassland. [Conclusion] Inner Mongo-lian grassland degradation were become more seriously in last 30 years because that temperature, precipitation and graze intensities change, which not performance on decreasing coverage but grassland areas.
基金Supported by Tianjin Science and Technology Development Project (060YFGNC1900)National Key Technology R&D Program in the 11th Five-year Plan of China(2012BAD38B01)~~
文摘[Objective] The aim was to study on temporal-spatial distribution model of cold chain logistics for vegetables. [Method] Broccoli was taken as an example. Detailedly, time-space distribution model of cold chain logistics for broccoli was proposed from standpoints of costs and benefits based on changes of time and space, and a comprehensive evaluation was made on timeliness, efficiency, risks, added- value of products and satisfaction of information in cold-chain logistics. [Result] The efficiency of cold chain logistics for vegetable can be greatly improved by temporal- spatial distribution model of cold chain logistics. [Conclusion] Costs and benefits of vegetables in temporal-apstial distribution could be evaluated by the model.
文摘目的探究MR 3D CUBE与常规磁共振成像(MRI)在膝关节前交叉韧带损伤中的应用价值。方法选取2022年1月至2024年4月本院收治的136例膝关节前交叉韧带损伤患者,根据患者损伤程度分为Ⅰ级、Ⅱ级和Ⅲ级;患者均进行MR 3D CUBE与常规MRI检查;Kappa检验分析MR 3D CUBE、常规MRI与关节镜诊断的一致性;以关节镜检查结果为金标准,采用四格表分析MR 3D CUBE与常规MRI对膝关节前交叉韧带不同损伤分级的诊断价值;膝关节前交叉韧带损伤治疗效果的影响因素采用Logistic回归分析。结果MR 3D CUBE、常规MRI与关节镜诊断的一致性较好(Kappa=0.664、0.832,P<0.05)。MR 3D CUBE在诊断膝关节前交叉韧带损伤Ⅰ级时准确度为91.91%,Ⅱ级时准确度为91.18%,Ⅲ级时准确度为94.85%;常规MRI在诊断膝关节前交叉韧带损伤Ⅰ级时准确度为85.29%,Ⅱ级时准确度为83.09%,Ⅲ级时准确度为87.50%,MR 3D CUBE在诊断膝关节前交叉韧带损伤Ⅲ级时准确度显著高于常规MRI(P<0.05)。不良组和良好组病程和既往损伤比较有差异(P<0.05)。多因素Logistic回归分析得知,病程和既往损伤是影响膝关节前交叉韧带损伤患者治疗效果的危险因素(P<0.05)。结论MR 3D CUBE与常规MRI均能诊断膝关节前交叉韧带损伤,但MR 3D CUBE诊断效能高于常规MRI,可在临床应用。
基金Project supported by the National Key Basic Research Support Foundation of China (No. G1999011801) the Knowledge Innovation Program of Chinese Acacemy of Sciences (Nos. KZCX2-413 and ISSASIP0110).
文摘In global change research, changes of soil organic carbon (SOC) reservoirs intropical and subtropical regions are still unknown. The temporal-spatial variability of SOC stockswas determined in a basin of over 579 km^2 in subtropical China from 1981to 2002. ArcGIS8.l softwarewas utilized for spatial analysis of semivariance, ordinary kriging (OK), and probability kriging(PK). Grid and hierarchical approaches were employed for the sampling scenario in 2002 with 106Global Position System (GPS) established spots sampled. Bulk topsoil samples (0—30 cm) werecollected at three random sites on each spot. The SOC content for 1981 came from the SOC map of theSecond National Soil Survey. Geostatistical results of the nugget to sill ratio (0.215-0.640)in therehabilitating ecosystem indicated a moderate spatial dependence for SOC on this large scale. Therange of SOC changed from 2.04 km in 1981 to 7.15 km in 2002. The mean topsoil SOC increased by 4.6%from 10.63 g kg^(-1) (1981) to 11.12 g kg^(-1)(2002). However, during this 21-year period 25.2% ofthe total basin area experienced a decrease in SOC. Also, the probability kriging results showedthat the geometric mean probabilities of SOC <= 6.0 g kg^(-1), <= 11.0 g kg^(-1) and > 15.0 gkg^(-1) were 0.188, 0.534 and 0.378, respectively in 2002, comparing to 0.234, 0.416 and 0.234 inthat order in 1981, respectively. The SOC storage in the topsoil increased by 17.0% during this timewith the main increase occurring in forests and cultivated land,which amounted to 82.5% and 17.0%of the total increase, respectively.
基金National Key Developing Program for Basic Sciences, No. G1999043505
文摘Sand-dust storm is a special natural disaster that frequently occurs in deserts and their surrounding areas. With the data published onSurface Meteorological Monthly Bulletin andSurface Chart during 1971–1996, the temporal-spatial distribution and annual variation of sand-dust storms are analyzed on the basis of the case study of atmospheric processes. Furthermore, the tracks and source areas of sand-dust storms are determined with the aid of GIS. The results show that except some parts of Qinghai Province and Inner Mongolia as well as Beijing, sand-dust storms decrease apparently in time and space in recent decades in China. Sand-dust storms occur most frequently in spring, especially in April. According to their source areas, sand-dust storms are classified into two types, i.e., the inner-source and outer-source sand-dust storms. Most of the outer-source sand-dust storms move along the north and west tracks. The north-track outer-source sand-dust storms always intrude into China across the Sino-Mongolian border from Hami, a city in the eastern part ofXinjiang, to Xilin Gol, a league in Inner Mongolia, while the west-track ones intrude into China from both southern and northern Xinjiang. The source lands of inner-source sand-dust storms concentrate in the Taklimakan Desert and its surrounding areas in southern Xinjiang, southern part of the Junggar Basin in north of Xinjiang, the Hexi Corridor in western Gansu Province, the dry deserts of Inner Mongolia and the Qaidam Basin in Qinghai.
基金The National Natural Science Foundation of China (No. 20477029)the National Basic Research Program (973) of China (No.2004CB418506)the Basic Research Program of Educational Department of Liaoning Government (No. 05L262)
文摘Heavy metal contamination in soils has been of wide concern in China in the last several decades. The heavy metal contamination was caused by sewage irrigation, mining and inappropriate utilization of various agrochemicals and pesticides and so on. The Shenyang Zhangshi irrigation area （SZIA） in China is a representative area of heavy metal contamination of soils resulting from sewage irrigation for about 30 years duration. This study investigated the spatial distribution and temporal variation of soil cadmium contamination in the SZIA. The soil samples were collected from the SZIA in 1990 and 2004; Cd of soils was analyzed and then the spatial distribution and temporal variation of Cd in soils was modelled using kriging methods. The kriging map showed that long-term sewage irrigation had caused serious Cd contamination in topsoil and subsoil. In 2004, the Cd mean concentrations were 1.698 and 0.741 mg/kg, and the maxima 10.150 and 7.567 mg/kg in topsoils （0-20 cm） and subsoils （20-40 cm） respectively. These values are markedly more than the Cd levels in the second grade soil standard in China. In 1990, the Cd means were 1.023 and 0.331 mg/kg, and the maxima 9.400 and 3.156 mg/kg, in topsoils and subsoils respectively. The soil area in 1990 with Cd more than 1.5 mg/kg was 2701 and 206.4 hnl2 in topsoils and subsoils respectively; and in 2004, it was 7592 and 1583 hm^2, respectively. Compared with that in 1990, the mean and maximum concentration of Cd, as well as the soil area with Cd more than 1.5 mg/kg had all increased in 2004, both in topsoils and subsoils.
基金National Natural Science Foundation of China, No.40271103 Natural Science Foundation of Anhui Provincial Education Department, No.2005KJ202/021
文摘The Huaihe River basin of Anhui is not only a transitional zone of physical geography, but also a convergent area of many cultures in China. It is one of the sensitive ecotones to global changes and the birthplace of Chinese civilization. Using the field archaeological data and the sporo-pollens and the age data of the drilling cores, we analysed Neolithic cultural development and environmental evolution in the Huaihe River basin of Anhui. According to the combination of some research results in archaeology with environmental evolution research, this paper discusses the relationship between culture and environment in the Huaihe River basin of Anhui. The Neolithic cultural development was strongly impacted by the environmental change. The primitive culture （Shishanzi） was developed in the beginning of the Holocene Megathermal Period with distinct regional feature of the culture. From 6.5 kaBP to 5.5 kaBP, the climate changed warmer and wetter. The frequent occurrence of flood and waterlog due to such a climate regime and high sea level caused the earth＇s surface environment deteriorated in the Huaihe River basin of Anhui and the interruption of the Neolithic cultural development, hence a lack of archaeological sites. From 5.5 kaBP to 4.0 kaBP, the climate changed from wet to dry, the natural environment was propitious to human survival. Dawenkou Culture and Longshan Culture flourished in this period. The Neolithic cultural development, the number of the sites and their distribution characteristics of the sites in the study area differed apparently from those in Central China and Shandong Province.
文摘The long-term temporal and spatial dynamics of marine coastal water quality in Tolo Harbor, Hong Kong were explored. The Harbor is divided into three zones represented as Harbor, Buffer, and Channel Subzones. The time range for the study covers the period from the 1970s to the 1990s. The selected indicators for the comprehensive assessment of water quality consist of physical, chemical and biological aspects, including suspended solids(SS), Secchi disk depth(SD), 5-day biochemical oxygen demand(BOD\-5), total nitrogen(TN), total phosphorus(TP), faecal coliform, chlorophyll-a(Chl-a), and the number of red tide occurrences. The results indicated the presence of obvious temporal and spatial trends with regard to changes in water quality. Spatially, water quality in the Channel Subzone is the best, while that in the Harbor Subzone is the worst. On a temporal basis, the average trend from bad to good was 1980s>1990s>1970s as indicated by most of the selected water quality indicators. Water quality during the late 1980s reached its worst level with the lowest SD, the highest BOD\-5, TN, TP, Chl-a concentrations, and the number of red tide occurrences. These long-term temporal-spatial water quality trends were also found in other studies of the Tolo Harbor. The large quantity of pollutants produced as a result of increasing population, industrial and commercial actives, and urbanization and industrialization trends in both Shatin and Tai Po seem to be primarily responsible for the changes in marine coastal water quality.
基金supported by the Program for New Century Excellent Talents in University(NCET-06-0856)the National Natural Science Foundation of China(60772068)
文摘To enhance the resolution of parameter estimation with limited samples received by a short passive array,an iterative nonparametric algorithm for estimating the frequencies and direction-of-arrivals(DOAs)of signals is proposed.The cost function is constructed using 12-norm Gaussian entropy combined with an additional constraint,12-norm constraint or linear constraint.By minimizing the cost functions in the temporal and the spatial dimensions using corresponding iteration algorithms respectively,the sparse discrete Fourier transforms(DFTs)of temporal and spatial samples are obtained to represent the extrapolated sequences with much larger sizes than the original samples.Then frequency and angle estimates are obtained by performing the traditional simple methods on the extrapolated sequences.It is shown that the proposed algorithm offers increased resolution and significantly reduced sidelobes compared with the periodogram and beamforming based methods.And it achieves high precision compared with the high-resolution method with lower computational burden.Some numerical simulations and real data processing results are presented to verify the effectiveness of the method.
基金supported by the National Natural Science Foundation of China(Grant no.31172117,31472020)the Graduate Student Innovation Research Projects of Anhui University(YQH100269)
文摘Background:The Yangtze River floodplain provides important wintering habitats for Hooded Cranes(Grus monacha) in China.Fluctuations in the water level change foraging habitat and food availability,affecting their temporal-spatial patterns of foraging activities.It is of considerable importance to investigate the effect of these fluctuations on food availability for wintering Hooded Cranes and their foraging response to these changes.Understanding their behavior patterns is beneficial in protecting the wintering crane population and restoring their wintering habitats.Methods:A field survey of the winter behavior of cranes was carried out at Shengjin Lake from November in 2013 to April in 2014.Habitat variables,as well as the spatial distribution and behavior patterns of wintering cranes at their foraging sites during five stages of water level fluctuation were collected.Based on this data we analyzed the relationship of foraging behavior relative to water level fluctuations and habitat types.Results:The foraging habitats used by Hooded Cranes varied at the different water level stages.As the water level decreased,the use of meadows and mudflats increased.When the water dropped to its lowest level,the use by the Hooded Crane in the mudflats reached a peak.There were statistically significant differences in time budget in the three types of habitats over the five stages of the water level.In the mudflats,the foraging behavior and maintenance behavior varied significantly with the water level,while the alert behavior showed little variation.Analysis of a generalized linear model showed that the five water level stages and three habitat types had a significant effect on foraging behavior,while the combined effect of these two variables was significant on the foraging time budget and the length of foraging activity of the Hooded Crane.Conclusions:With the decrease in the water level,the use of mudflats by Hooded Cranes increased correspondingly.Food availability in different habitats was affected by changes in the water level.The Hooded Crane adjusted its foraging patterns and made full use of the three available types of habitat in order to acquire enough food in response to fluctuations in the water level.
文摘This study applied GIS-based statistical analytic techniques to investigate the influence of accident Severity Index(SI)on temporal-spatial patterns of accident hotspots related to the specific time intervals of day and seasons.Road Traffic Accident(RTA)data in 3 years(2015-2017)in Hanoi,Vietnam were used to analyze and test this approach.Firstly,the RTA data were divided into four seasons in accordance with Hanoi's weather conditions and the time intervals such as the daytime,nighttime,or peak hours.Then,the Kernel Density Estimation(KDE)method was applied to analyze hotspots according to the time intervals and seasons.Finally,the results were presented by using the comap technique.This study considered both analyses with and without SI.The accident SI measures the seriousness of an accident.The approach method is to give higher weights to the more serious accidents,but not with the extremely high values calculated on a direct rate to the accident expenditures.The results showed that both analyses determined the relatively similar hotspots,but the rankings of some hotspots were quite different due to the integration of SI.It is better to take into account SI in determining RTA hotspots because the gained results are more precise and the rankings of hotspots are more accurate.From there,the traffic authorities can easily understand the causes behind each accident and provide reasonable solutions to solve the most dangerous hotspots in case of limited budget and resources appropriately.This is also the first study about this issue in Vietnam,so the contribution of the article will help the traffic authorities easily solve this problem not only in Hanoi but also in other cities.
基金supported in part by the National Key R&D Program of China (No.2017YFE0109000)the project of China Datang Corporation Ltd
文摘With the increasing proportion of wind power integration, the volatility of wind power brings huge challenges to the safe and stable operation of the electric power system. At present, the indexes commonly used to evaluate the volatility of wind power only consider its overall characteristics, such as the standard deviation of wind power, the average of power variables, etc., while ignoring the detailed volatility of wind power, that is, the features of the frequency distribution of power variables. However, how to accurately describe the detailed volatility of wind power is the key foundation to reduce its adverse influences. To address this, a quantitative method for evaluating the detailed volatility of wind power at multiple temporal-spatial scales is proposed. First, the volatility indexes which can evaluate the detailed fluctuation characteristics of wind power are presented, including the upper confidence limit, lower confidence limit and confidence interval of power variables under the certain confidence level. Then, the actual wind power data from a location in northern China is used to illustrate the application of the proposed indexes at multiple temporal(year–season–month–day) and spatial scales(wind turbine–wind turbines–wind farm–wind farms) using the calculation time windows of 10 min, 30 min, 1 h, and 4 h. Finally, the relationships between wind power forecasting accuracy and its corresponding detailed volatility are analyzed to further verify the effectiveness of the proposed indexes. The results show that the proposed volatility indexes can effectively characterize the detailed fluctuations of wind power at multiple temporal-spatial scales. It is anticipated that the results of this study will serve as an important reference for the reserve capacity planning and optimization dispatch in the electric power system which with a high proportion of renewable energy.
基金This research was funded by the Development and Demonstration of Road Dust Monitoring and Management System(No.Z191100009119011)the National Research Program for Key Issues in Air Pollution Control China(No.DQGG0201)the National Key Research and Development program of China(No.2018YFC0213203).
文摘Road silt loading(sL)is an important parameter in the fugitive road dust(FRD)emissions.In this study,the improved Testing Re-entrained Aerosol Kinetic Emissions from Roads(TRAKER)combined with the AP-42 method was firstly developed to quickly measure and estimate the sLs of paved roads in Beijing,China.The annual average sLs in Beijing was 0.59±0.31 g/m^(2)in 2020,and decreased by 22.4%compared with that in 2019.The seasonal variations of sLs followed the order of spring>winter>summer>autumn in the two years.The seasonal mean road sLs on the same type road in the four seasons presented a decline trend from^(2)019 to 2020,especially on the Expressway,decreasing 47.4%-72.7%.The road sLs on the different type roads in the same season followed the order of Major arterial∼Minor arterial∼Branch road>Express road,and Township road∼Country highway>Provincial highway∼National highway.The emission intensities of PM10 and PM_(2.5)from FRD in Beijing in 2020 were lower than those in 2019.The PM10 and PM_(2.5)emission intensities at the four planning areas in the two years all presented the order of the capital functional core area>the urban functional expansion area>the urban development new area>the ecological conservation and development area.The annual emissions of PM10 and PM_(2.5)from FRD in Beijing in 2020 were 74,886 ton and 18,118 ton,respectively,decreasing by∼33.3%compared with those in 2019.
基金Projects(61271321,61573253,61401303)supported by the National Natural Science Foundation of ChinaProject(14ZCZDSF00025)supported by Tianjin Key Technology Research and Development Program,China+1 种基金Project(13JCYBJC17500)supported by Tianjin Natural Science Foundation,ChinaProject(20120032110068)supported by Doctoral Fund of Ministry of Education of China
文摘Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.
基金National Natural Science Foundation of China(Grant No.41271134)the Humanities and Social Science Research Foundation of Ministry of Education(Grant No.10YJC790245)
文摘By using the variation coefficient,Gini coefficient and Theil coefficient,this paper makes preliminary exploration of temporalspatial change features and driving mechanism for regional differences of domestic tourism in China from 1995 to 2009.According to the results,we drew the following conclusions:(1)The regional difference of domestic tourism in China tends to be narrowing generally,and is less than that of inbound tourism,playing an important role in narrowing the overall gap of regional tourism in China.(2)The regional internal difference features:inter-provincial difference in the eastern region and difference among the eastern,central and western regions are comparatively obvious and demonstrate a significantly shrinking tendency,the change tendency is consistent with the change tendency of overall difference and exercises a decisive role in overall difference,whereas the inter-provincial difference in the central and western regions is small and relatively stable,having less influence on the overall difference.(3)The temporal-spatial change in regional difference is featured by:low-level provinces occupy a majority and are concentrated in the central and western regions,showing a tendency of narrowing difference;high-level provinces are concentrated in the eastern region,showing a tendency of spreading to the central and western regions;spatial pattern of regional difference demonstrates 4 types,i.e."proliferation type","polarization type","quiescence type"and"collapse type."(4)The driving force for regional difference of domestic tourism in China comes down to 3 aspects:regional socio-economic attribute,regional transport accessibility level and regional development policy.
