Trend forecasting is an important aspect in fault diagnosis and work state supervision. The principle, where Grey theory is applied in fault forecasting, is that the forecast system is considered as a Grey system; the...Trend forecasting is an important aspect in fault diagnosis and work state supervision. The principle, where Grey theory is applied in fault forecasting, is that the forecast system is considered as a Grey system; the existing known information is used to infer the unknown information's character, state and development trend in a fault pattern, and to make possible forecasting and decisions for future development. It involves the whitenization of a Grey process. But the traditional equal time interval Grey GM (1,1) model requires equal interval data and needs to bring about accumulating addition generation and reversion calculations. Its calculation is very complex. However, the non equal interval Grey GM (1,1) model decreases the condition of the primitive data when establishing a model, but its requirement is still higher and the data were pre processed. The abrasion primitive data of plant could not always satisfy these modeling requirements. Therefore, it establishes a division method suited for general data modeling and estimating parameters of GM (1,1), the standard error coefficient that was applied to judge accuracy height of the model was put forward; further, the function transform to forecast plant abrasion trend and assess GM (1,1) parameter was established. These two models need not pre process the primitive data. It is not only suited for equal interval data modeling, but also for non equal interval data modeling. Its calculation is simple and convenient to use. The oil spectrum analysis acted as an example. The two GM (1,1) models put forward in this paper and the new information model and its comprehensive usage were investigated. The example shows that the two models are simple and practical, and worth expanding and applying in plant fault diagnosis.展开更多
Extensive spatiotemporal analyses of long-trend surface ozone in the Yangtze River Delta(YRD)region and itsmeteorology-related and emission-related have not been systematically analyzed.In this study,by using 8-year-l...Extensive spatiotemporal analyses of long-trend surface ozone in the Yangtze River Delta(YRD)region and itsmeteorology-related and emission-related have not been systematically analyzed.In this study,by using 8-year-long(2015–2022)surface ozone observation data,we attempted to reveal the variation ofmultiple timescale components using the Kolmogorov–Zurbenko filter,and the effects of meteorology and emissions were quantitatively isolated using multiple linear regression with meteorological variables.The results showed that the short-term,seasonal,and long-term components accounted for daily maximum 8-hr average O_(3)(O_(3–8)hr)concentration,46.4%,45.9%,and 1.0%,respectively.The meteorological impacts account for an average of 71.8%of O_(3–8)hr,and the YRD’s eastern and northern sections aremeteorology-sensitive areas.Based on statistical analysis technology with empirical orthogonal function,the contribution of meteorology,local emission,and transport in the long-term component of O_(3–8)hr were 0.21%,0.12%,and 0.6%,respectively.The spatiotemporal analysis indicated that a distinct decreasing spatial pattern could be observed from coastal cities towards the northwest,influenced by the monsoon and synoptic conditions.The central urban agglomeration north and south of the YRD was particularly susceptible to local pollution.Among the cities studied,Shanghai,Anqing,and Xuancheng,located at similar latitudes,were significantly impacted by atmospheric transmission—the contribution of Shanghai,the maximum accounting for 3.6%.展开更多
SUN Gen nian (Shaanxi Normal University, Xi’an 710062,P.R.China) ABSTRACE:Modern inbound tourism in China has been developing for 20 years, a trend line of inbound tourists in statistical data began to show. This pap...SUN Gen nian (Shaanxi Normal University, Xi’an 710062,P.R.China) ABSTRACE:Modern inbound tourism in China has been developing for 20 years, a trend line of inbound tourists in statistical data began to show. This paper introduces the concept of tourism background trend line, and explores its two functions as a barometer in demonstrating fluctuation in the tourism economy and as a forecaster in forecasting tourism development. The tourism background trend line is a new concept, the word "background" derived from environment science, refers to the trend line" which reflects the dynamic curve or dynamic equation of tourism development without considering the impact of unexpected incidents. The introduction of this concept was inspired by Karl Marx’s comments on the relation between value and price. Tourism background trend line reflects the summary of multiple factors involving tourism resources, tourism demand, population growth, the scale and speed of economic development, and the spatial interaction between tourism origins and destimations. It demonstrates the natural and stable trend and the temporal law of tourism development in a country or region. The tourism statistical curve is at random, susceptible to disruptions and disturbances from serious political, economic and environmental happenings, but it always fluctuates around the background line. Tourism background line can reveal the potential of a country’s tourism development. Compared with the statistical line, it can be used as a barometer" indicating ups and downs of tourism industry in the past. When naturally extended, the background trend line also can be used for forecasting the trend of tourism development in future. In this paper, 4 tourism background trend lines of China’s inbound tourists, i.e. foreign tourists, Hong Kong/Macao/Taiwan tourists, overseas Chinese tourists and total tourists from abroad, were established with statistical data from 1978 to 1996. And the impacts of the Political Event in 1989(or Tiananmen Square Incident) on China’s inbound tourism were evaluated. The result shows that the impact of the Event was not limited within one year, but it stretched over 3 years. The total loss was 20 million in tourist arrivals and ＄ 1620 million in foreign currency income. The paper also studied the trend of China’s inbound tourism in the next 4 years.展开更多
Knowing the pattern of surface winds on the seas and oceans and how it changes over time is of great importance. In this research, the monthly surface wind fields on the Indian Ocean have been studied and analyzed for...Knowing the pattern of surface winds on the seas and oceans and how it changes over time is of great importance. In this research, the monthly surface wind fields on the Indian Ocean have been studied and analyzed for a 35-year period (1981-2015), using NCEP/NCAR data reanalysis. The results show that transition from cold to warm pattern happens in May and that the summer monsoon pattern begins in June and continues until August. The wind speed pattern tends to the winter monsoon from November on. The maximum average wind speed in June is 13 m/s and its minimum is 2 m/s in October. Direction of prevailing winds is the southwest in the summer. The highest wind speed happens in the latitude of 10 - 15 degrees. Analysis of the wind distribution shows that the wind speed of 2 - 5 m/s happens in about 60% of the cases. There is probability of blowing 0.5 - 4 m/s wind for all months;but this probability is higher in the autumn (October and November) than that in the summer (July and August). Probability of the monthly over 5 m/s winds shows a definitely opposite distribution;that is, wind speed in July and August is higher than that in October. A long-term survey on the speed of surface water wind and sea surface temperature shows an opposite changing trend in wind speed and sea surface temperature during a 55-year statistical period. Wind speed reduced, while the sea surface temperature was increasing. The wind speed gradient in the upper levels of atmosphere graph has been increasing;this phenomenon confirms the effects of global warming and ocean warming on the monsoon system patterns in the Indian Ocean. Keywords展开更多
With acceleration of economic globalization,ecological problem becomes increasingly prominent,and forestry and forest issues become world concerns.Since 1992 United Nations Conference on Environment and Development,su...With acceleration of economic globalization,ecological problem becomes increasingly prominent,and forestry and forest issues become world concerns.Since 1992 United Nations Conference on Environment and Development,sustainable forest management(SFM)becomes a subject of times,and hot issues,such as climate change,assessment of forest resource,biomass energy of forestry,combating illegal timber and relevant international forest product trade,gradually become world concerns.This paper sum up these hot issues,analyzes background and current situations of forestry development,and discusses the development trends of global forestry.展开更多
This paper introduced the laundry capsule’s characteristics, current situation, and the development of its technical standards. analyzed the problems that encountered in the development of laundry capsules.In additio...This paper introduced the laundry capsule’s characteristics, current situation, and the development of its technical standards. analyzed the problems that encountered in the development of laundry capsules.In addition, the future of Laundry capsule in China were prospected.展开更多
为提高月径流时间序列预测精度,改进最小二乘孪生支持向量回归机(Least Squares Twin Support Vector Regression,LSTSVR)性能,首次基于高斯核函数、多项式核函数、线性核函数构建混合核函数,提出4种季节趋势分解(Seasonal and Trend de...为提高月径流时间序列预测精度,改进最小二乘孪生支持向量回归机(Least Squares Twin Support Vector Regression,LSTSVR)性能,首次基于高斯核函数、多项式核函数、线性核函数构建混合核函数,提出4种季节趋势分解(Seasonal and Trend decomposition using Loess,STL)-小波包变换(Wavelet Packet Transform,WPT)-裂狐优化(Rüppell's Fox Optimizer,RFO)算法-混合核最小二乘孪生支持向量回归机(Hybrid Kernel Least Squares Twin Support Vector Regression,HLSTSVR)模型,并构建STL-WPT-RFO-LSTSVR、STL-WPT-RFO-混合核最小二乘支持向量回归机(Hybrid Kerllel Least Squares Twin Suppart Vector Regression,HLSSVR)、STL-WPT-RFO-最小二乘支持向量回归机(Least Squares Support Vector Regression,LSSVR)等17种对比分析模型,通过云南省高桥、凤屯水文站月径流时间序列预测实例对21种模型进行验证。首先利用STL-WPT二次分解技术对月径流序列进行分解处理,合理划分训练集和验证集;然后基于高斯核函数、多项式核函数、线性核函数,采用“三三”线性组合和“两两”线性组合的方式构建4种混合核函数对月径流分解分量进行空间映射;最后利用RFO寻优HLSTSVR/LSTSVR/HLSSVR/LSSVR最佳超参数,利用最佳超参数建立21种模型对实例月径流序列各分解分量进行训练、预测和重构。结果表明:①4种STL-WPT-RFO-HLSTSVR模型能适应不同尺度的月径流数据分布,具有较好的模型性能和较小的预测误差,其中STL-WPT-RFO-HLSTSVR(高斯+多项式+线性)模型对高桥、凤屯站月径流预测的平均绝对百分比误差MAPE分别为2.85%、2.19%,决定系数R2均为0.9994,预测精度最高、效果最好;②混合核函数兼顾了不同核函数优势,能在模型复杂度与泛化能力之间取得平衡,显著提升模型性能和预测精度;③STL-WPT二次分解技术能有效解决复杂时间序列的非平稳性、非线性和多尺度特征,较STL更具分解优势;④组合模型融合了STL-WPT、RFO和HLSTSVR优点,具有较好的普适性和参考价值。展开更多
目的采用文献计量分析方法对全球2019—2023年乙型肝炎功能性治愈相关文献进行分析,帮助研究人员了解该领域的研究热点和趋势。方法检索2019—2023年Web of Science核心合集的科学引文索引扩展版(Science Citation Index Expanded,SCI-E...目的采用文献计量分析方法对全球2019—2023年乙型肝炎功能性治愈相关文献进行分析,帮助研究人员了解该领域的研究热点和趋势。方法检索2019—2023年Web of Science核心合集的科学引文索引扩展版(Science Citation Index Expanded,SCI-Expanded)收录的乙型肝炎功能性治愈主题相关文献。利用VOSviewer和CiteSpace可视化分析工具,从发文趋势、国际科研合作网络、关键词共现聚类和突现等角度进行深入分析,并结合相关文献的具体内容进行阐述,分析研究热点和趋势。结果共纳入600篇相关文献,关键词共现及主题聚类提示乙肝功能性治愈目前主要聚焦的研究方向为功能性治愈预测与监测的血清生物标志物、功能性治愈与免疫、核苷类似物停药、干扰素治疗、功能性治愈的远期预后。ESI高被引原始研究论文的内容与上述聚类大致符合,但更多地集中于功能性治愈的新药。关键词突现显示2019年以来,研究热点从病毒学机制和血清标志物,到核苷类似物停药和干扰素治疗,再到免疫学机制与新药的变迁。结论乙型肝炎功能性治愈的病毒学机制、血清标志物、免疫学机制、核苷类似物的停药、干扰素治疗、治愈后的远期预后是研究热点和趋势。展开更多
文摘Trend forecasting is an important aspect in fault diagnosis and work state supervision. The principle, where Grey theory is applied in fault forecasting, is that the forecast system is considered as a Grey system; the existing known information is used to infer the unknown information's character, state and development trend in a fault pattern, and to make possible forecasting and decisions for future development. It involves the whitenization of a Grey process. But the traditional equal time interval Grey GM (1,1) model requires equal interval data and needs to bring about accumulating addition generation and reversion calculations. Its calculation is very complex. However, the non equal interval Grey GM (1,1) model decreases the condition of the primitive data when establishing a model, but its requirement is still higher and the data were pre processed. The abrasion primitive data of plant could not always satisfy these modeling requirements. Therefore, it establishes a division method suited for general data modeling and estimating parameters of GM (1,1), the standard error coefficient that was applied to judge accuracy height of the model was put forward; further, the function transform to forecast plant abrasion trend and assess GM (1,1) parameter was established. These two models need not pre process the primitive data. It is not only suited for equal interval data modeling, but also for non equal interval data modeling. Its calculation is simple and convenient to use. The oil spectrum analysis acted as an example. The two GM (1,1) models put forward in this paper and the new information model and its comprehensive usage were investigated. The example shows that the two models are simple and practical, and worth expanding and applying in plant fault diagnosis.
基金supported by the National Natural Science Foundation of China(No.42075177)the National Key Research and Development Program of China(No.2017YFC0210003).
文摘Extensive spatiotemporal analyses of long-trend surface ozone in the Yangtze River Delta(YRD)region and itsmeteorology-related and emission-related have not been systematically analyzed.In this study,by using 8-year-long(2015–2022)surface ozone observation data,we attempted to reveal the variation ofmultiple timescale components using the Kolmogorov–Zurbenko filter,and the effects of meteorology and emissions were quantitatively isolated using multiple linear regression with meteorological variables.The results showed that the short-term,seasonal,and long-term components accounted for daily maximum 8-hr average O_(3)(O_(3–8)hr)concentration,46.4%,45.9%,and 1.0%,respectively.The meteorological impacts account for an average of 71.8%of O_(3–8)hr,and the YRD’s eastern and northern sections aremeteorology-sensitive areas.Based on statistical analysis technology with empirical orthogonal function,the contribution of meteorology,local emission,and transport in the long-term component of O_(3–8)hr were 0.21%,0.12%,and 0.6%,respectively.The spatiotemporal analysis indicated that a distinct decreasing spatial pattern could be observed from coastal cities towards the northwest,influenced by the monsoon and synoptic conditions.The central urban agglomeration north and south of the YRD was particularly susceptible to local pollution.Among the cities studied,Shanghai,Anqing,and Xuancheng,located at similar latitudes,were significantly impacted by atmospheric transmission—the contribution of Shanghai,the maximum accounting for 3.6%.
基金Under the auspices of National Natural Science Foundation of China.
文摘SUN Gen nian (Shaanxi Normal University, Xi’an 710062,P.R.China) ABSTRACE:Modern inbound tourism in China has been developing for 20 years, a trend line of inbound tourists in statistical data began to show. This paper introduces the concept of tourism background trend line, and explores its two functions as a barometer in demonstrating fluctuation in the tourism economy and as a forecaster in forecasting tourism development. The tourism background trend line is a new concept, the word "background" derived from environment science, refers to the trend line" which reflects the dynamic curve or dynamic equation of tourism development without considering the impact of unexpected incidents. The introduction of this concept was inspired by Karl Marx’s comments on the relation between value and price. Tourism background trend line reflects the summary of multiple factors involving tourism resources, tourism demand, population growth, the scale and speed of economic development, and the spatial interaction between tourism origins and destimations. It demonstrates the natural and stable trend and the temporal law of tourism development in a country or region. The tourism statistical curve is at random, susceptible to disruptions and disturbances from serious political, economic and environmental happenings, but it always fluctuates around the background line. Tourism background line can reveal the potential of a country’s tourism development. Compared with the statistical line, it can be used as a barometer" indicating ups and downs of tourism industry in the past. When naturally extended, the background trend line also can be used for forecasting the trend of tourism development in future. In this paper, 4 tourism background trend lines of China’s inbound tourists, i.e. foreign tourists, Hong Kong/Macao/Taiwan tourists, overseas Chinese tourists and total tourists from abroad, were established with statistical data from 1978 to 1996. And the impacts of the Political Event in 1989(or Tiananmen Square Incident) on China’s inbound tourism were evaluated. The result shows that the impact of the Event was not limited within one year, but it stretched over 3 years. The total loss was 20 million in tourist arrivals and ＄ 1620 million in foreign currency income. The paper also studied the trend of China’s inbound tourism in the next 4 years.
文摘Knowing the pattern of surface winds on the seas and oceans and how it changes over time is of great importance. In this research, the monthly surface wind fields on the Indian Ocean have been studied and analyzed for a 35-year period (1981-2015), using NCEP/NCAR data reanalysis. The results show that transition from cold to warm pattern happens in May and that the summer monsoon pattern begins in June and continues until August. The wind speed pattern tends to the winter monsoon from November on. The maximum average wind speed in June is 13 m/s and its minimum is 2 m/s in October. Direction of prevailing winds is the southwest in the summer. The highest wind speed happens in the latitude of 10 - 15 degrees. Analysis of the wind distribution shows that the wind speed of 2 - 5 m/s happens in about 60% of the cases. There is probability of blowing 0.5 - 4 m/s wind for all months;but this probability is higher in the autumn (October and November) than that in the summer (July and August). Probability of the monthly over 5 m/s winds shows a definitely opposite distribution;that is, wind speed in July and August is higher than that in October. A long-term survey on the speed of surface water wind and sea surface temperature shows an opposite changing trend in wind speed and sea surface temperature during a 55-year statistical period. Wind speed reduced, while the sea surface temperature was increasing. The wind speed gradient in the upper levels of atmosphere graph has been increasing;this phenomenon confirms the effects of global warming and ocean warming on the monsoon system patterns in the Indian Ocean. Keywords
基金Supported by Digital Management Platform and Capacity Building of Chinese Academy of Forestry Foundation(CAFYBB2011006-06)
文摘With acceleration of economic globalization,ecological problem becomes increasingly prominent,and forestry and forest issues become world concerns.Since 1992 United Nations Conference on Environment and Development,sustainable forest management(SFM)becomes a subject of times,and hot issues,such as climate change,assessment of forest resource,biomass energy of forestry,combating illegal timber and relevant international forest product trade,gradually become world concerns.This paper sum up these hot issues,analyzes background and current situations of forestry development,and discusses the development trends of global forestry.
文摘This paper introduced the laundry capsule’s characteristics, current situation, and the development of its technical standards. analyzed the problems that encountered in the development of laundry capsules.In addition, the future of Laundry capsule in China were prospected.
文摘为提高月径流时间序列预测精度,改进最小二乘孪生支持向量回归机(Least Squares Twin Support Vector Regression,LSTSVR)性能,首次基于高斯核函数、多项式核函数、线性核函数构建混合核函数,提出4种季节趋势分解(Seasonal and Trend decomposition using Loess,STL)-小波包变换(Wavelet Packet Transform,WPT)-裂狐优化(Rüppell's Fox Optimizer,RFO)算法-混合核最小二乘孪生支持向量回归机(Hybrid Kernel Least Squares Twin Support Vector Regression,HLSTSVR)模型,并构建STL-WPT-RFO-LSTSVR、STL-WPT-RFO-混合核最小二乘支持向量回归机(Hybrid Kerllel Least Squares Twin Suppart Vector Regression,HLSSVR)、STL-WPT-RFO-最小二乘支持向量回归机(Least Squares Support Vector Regression,LSSVR)等17种对比分析模型,通过云南省高桥、凤屯水文站月径流时间序列预测实例对21种模型进行验证。首先利用STL-WPT二次分解技术对月径流序列进行分解处理,合理划分训练集和验证集;然后基于高斯核函数、多项式核函数、线性核函数,采用“三三”线性组合和“两两”线性组合的方式构建4种混合核函数对月径流分解分量进行空间映射;最后利用RFO寻优HLSTSVR/LSTSVR/HLSSVR/LSSVR最佳超参数,利用最佳超参数建立21种模型对实例月径流序列各分解分量进行训练、预测和重构。结果表明:①4种STL-WPT-RFO-HLSTSVR模型能适应不同尺度的月径流数据分布,具有较好的模型性能和较小的预测误差,其中STL-WPT-RFO-HLSTSVR(高斯+多项式+线性)模型对高桥、凤屯站月径流预测的平均绝对百分比误差MAPE分别为2.85%、2.19%,决定系数R2均为0.9994,预测精度最高、效果最好;②混合核函数兼顾了不同核函数优势,能在模型复杂度与泛化能力之间取得平衡,显著提升模型性能和预测精度;③STL-WPT二次分解技术能有效解决复杂时间序列的非平稳性、非线性和多尺度特征,较STL更具分解优势;④组合模型融合了STL-WPT、RFO和HLSTSVR优点,具有较好的普适性和参考价值。
文摘目的采用文献计量分析方法对全球2019—2023年乙型肝炎功能性治愈相关文献进行分析,帮助研究人员了解该领域的研究热点和趋势。方法检索2019—2023年Web of Science核心合集的科学引文索引扩展版(Science Citation Index Expanded,SCI-Expanded)收录的乙型肝炎功能性治愈主题相关文献。利用VOSviewer和CiteSpace可视化分析工具,从发文趋势、国际科研合作网络、关键词共现聚类和突现等角度进行深入分析,并结合相关文献的具体内容进行阐述,分析研究热点和趋势。结果共纳入600篇相关文献,关键词共现及主题聚类提示乙肝功能性治愈目前主要聚焦的研究方向为功能性治愈预测与监测的血清生物标志物、功能性治愈与免疫、核苷类似物停药、干扰素治疗、功能性治愈的远期预后。ESI高被引原始研究论文的内容与上述聚类大致符合,但更多地集中于功能性治愈的新药。关键词突现显示2019年以来,研究热点从病毒学机制和血清标志物,到核苷类似物停药和干扰素治疗,再到免疫学机制与新药的变迁。结论乙型肝炎功能性治愈的病毒学机制、血清标志物、免疫学机制、核苷类似物的停药、干扰素治疗、治愈后的远期预后是研究热点和趋势。
