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气温与医院感染关系的研究及时间序列分析建模 被引量:1
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作者 张欣 甘爱群 《江西医药》 CAS 2022年第10期1684-1687,共4页
目的探讨气温观测数据(包括日最高气温、日最低气温、日平均气温、温差及温较差)与医院感染关联,建立预测模型,发现潜在规律,为医院感染防控提供更多方向。方法选择萍乡市某三级甲等医院收集2015年至2019年为期5年的医院感染病例资料,... 目的探讨气温观测数据(包括日最高气温、日最低气温、日平均气温、温差及温较差)与医院感染关联,建立预测模型,发现潜在规律,为医院感染防控提供更多方向。方法选择萍乡市某三级甲等医院收集2015年至2019年为期5年的医院感染病例资料,同步收集气温观测数据,通过单因素相关分析,多元逐步线性回归分析两者间关联性,利用数据建立时间序列自回归移动平均结合模型(ARIMA)季节性处理的ARIMA(p,d,q)(P,D,Q)s模型,预测模型合理性,绘制相应效果图。结果平均温度与医院感染例数分布基本类似,院感例数与温度较差呈正相关(r=0.141,P<0.05),与最高温度呈正相关(r=0.101,P<0.05)。与平均温度呈正相关(r=0.081,P<0.05)。多因素逐步线性回归结果显示,医院感染日例数与温度较差、最高温度、平均温度有关(P<0.05)。建立模型:ARIMA(0,1,2,)(0,1,1)12,表达式:ln(CHDt)=0.603εt-1+0.397εt-2+0.994εt-1+0.994*0.603εt-2+0.994*0.397εt-3。残差序列是随机的,以上均提示模型ARIMA(0,1,2,)(0,1,1)12是较理想的。对效果较好。残差白噪声检验无统计学意义(box值10.511,p=0.786>0.05),下一步进行预测,模型预测均在95%可信区间内,与实际情况较为一致。结论温差大、气温高可能与医院感染发生存在相关,ARIMA(0,1,2,)(0,1,1)12预测效果较好,可起到一定警示作用。 展开更多
关键词 医院感染 温度较差 时间序列分析
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Observed trends in diurnal temperature range over Nigeria 被引量:1
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作者 DIKE Victor Nnamdi LIN Zhaohui +1 位作者 WANG Yuxi NNAMCHI Hyacinth 《Atmospheric and Oceanic Science Letters》 CSCD 2019年第2期131-139,共9页
The long-term trend of diurnal temperature range(DTR)over Nigeria was examined using daily station-based datasets for the period 1971–2013.The results show that the regionally averaged DTR has decreased significantly... The long-term trend of diurnal temperature range(DTR)over Nigeria was examined using daily station-based datasets for the period 1971–2013.The results show that the regionally averaged DTR has decreased significantly(-0.34°C per decade)over the Nigerian Sahel(north of 10°N),but there has been a slight increasing trend(0.01°C per decade)over the Nigerian Guinea Coast.The annual decreasing trend of DTR in the Nigerian Sahel is mainly attributable to the significant increasing trend in daily minimum temperature(Tmin,0.51°C per decade),which far outstrips the rate of increase in the daily maximum(Tmax,0.17°C per decade).In contrast,the comparable trends in Tmin(0.19°C per decade)and Tmax(0.20°C per decade)may explain the non-significant trend of the DTR averaged over the Guinea Coast region.It is observed that the DTR has decreased more in boreal summer(June–July–August)than in boreal winter(December–January–February)for the regions.Furthermore,it is found that the significant DTR declining trend over the Nigerian Sahel is closely associated with an increasing trend of annual and summer precipitation in the region,but the increasing DTR trend in the Nigerian Guinea Coast region can be attributed to the decreasing trend of cloud cover over the region. 展开更多
关键词 Diurnal temperature range maximum/minimum temperature TREND NIGERIA
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Correlation between Atmospheric Water Vapor and Diurnal Temperature Range over China 被引量:1
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作者 ZHAO Tian-Bao 《Atmospheric and Oceanic Science Letters》 CSCD 2014年第4期369-375,共7页
Diurnal temperature range (DTR) is an im- portant measure in studies of climate change and variability. The changes of DTR in different regions are affected by many different factors. In this study, the degree of co... Diurnal temperature range (DTR) is an im- portant measure in studies of climate change and variability. The changes of DTR in different regions are affected by many different factors. In this study, the degree of correlation between the DTR and atmospheric precipitable water (PW) over China is explored using newly homogenized surface weather and sounding observations. The results show that PW changes broadly reflect the geographic patterns of DTR long-term trends over most of China during the period 1970-2012, with significant anticorrelations of trend patterns between the DTR and PW, especially over those regions with higher magnitude DTR trends. PW can largely explain about 40% or more (re 0.40) of the DTR changes, with a d(PW)/d(DTR) slope of -2% to -10% K^-1 over most of northwestern and southeastern China, despite certain seasonal dependencies. For China as whole, the significant anticorrelations between the DTR and PW anomalies range from -0.42 to -0.75, with a d(PW)/d(DTR) slope of-6% to -11% K^-1. This implies that long-term DTR changes are likely to be associated with opposite PW changes, approximately following the Clausius-Clapeyron equation. Furthermore, the relationship is more significant in the warm season than in the cold season. Thus, it is possible that PW can be considered as one potential factor when exploring long-term DTR changes over China. It should be noted that the present study has a largely statistical focus and that the underlying physical processes should therefore be examined in future work. 展开更多
关键词 atmospheric water vapor precipitable water diurnal temperature range anticorrelation China
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