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Prediction and Analysis of O_3 based on the ARIMA Model 被引量:2
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作者 李双金 杨宁 +2 位作者 闫奕琪 曹旭东 冀德刚 《Agricultural Science & Technology》 CAS 2015年第10期2146-2148,共3页
The research conducted prediction on changes of atmosphere pollution during July 9, 2014-July 22, 2014 with SPSS based on monitored data of O3 in 13 successive weeks from 6 sites in Baoding City and demonstrated predi... The research conducted prediction on changes of atmosphere pollution during July 9, 2014-July 22, 2014 with SPSS based on monitored data of O3 in 13 successive weeks from 6 sites in Baoding City and demonstrated prediction effect of ARIMA model is good by Ljung-Box Q-test and R2, and the model can be used for prediction on future atmosphere pollutant changes. 展开更多
关键词 Air quality Analysis of time series SPSS arima model
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The Application of ARIMA Model in Forecasting of PDSI in Henan Province
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作者 厉玉昇 《Agricultural Science & Technology》 CAS 2016年第3期760-764,共5页
[Objective] The aim was to establish drought forecasting model with high precision. [Method] With an ARIMA regression model, the research performed Palmer Drought mode(PDSI) time series modeling analysis of Henan Pr... [Objective] The aim was to establish drought forecasting model with high precision. [Method] With an ARIMA regression model, the research performed Palmer Drought mode(PDSI) time series modeling analysis of Henan Province based on PDSI time series and DPS(Data Processing Software) in order to build drought forecasting model. [Result] It is feasible to perform drought forecasting with appropriate parameters. [Conclusion] ARIMA model is practical and more precise in PDSI-based drought analysis and forecasting. 展开更多
关键词 arima model PDSI Forecasting APPLICATION Henan Province
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Prediction of Civil Aviation Passenger Transportation Based on ARIMA Model 被引量:5
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作者 Xinxin Tang Guangming Deng 《Open Journal of Statistics》 2016年第5期824-834,共12页
The passenger transportation, as an important index to describe the scale of aviation passenger transport, prediction and research, can let us understand the future trend of the aviation passenger transport, according... The passenger transportation, as an important index to describe the scale of aviation passenger transport, prediction and research, can let us understand the future trend of the aviation passenger transport, according to it, the airline can make corresponding marketing strategy adjustment. Combining with the knowledge of time series let us understand the characteristics of passenger transportation change, the R software is used to fit the data, so as to establish the ARIMA(1,1,8) model to describe the civil aviation passenger transport developing trend in the future and to make reasonable predictions. 展开更多
关键词 Passenger Transportation arima model Seasonal Trend FORECAST
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Prediction and Analysis of Chinese Rural Households'Consumption Level Based on the ARIMA Model 被引量:2
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作者 YAN Jian-biao LI Qiang 《Asian Agricultural Research》 2011年第3期83-85,88,共4页
By using the software SAS9.2 and the relevant data of consumption level of rural residents in China from 1952 to 2008,the ARIMA model is established.The model is used to analyze and forecast the time series of the con... By using the software SAS9.2 and the relevant data of consumption level of rural residents in China from 1952 to 2008,the ARIMA model is established.The model is used to analyze and forecast the time series of the consumption level of Chinese rural residents.The results show that in the near future,the consumption level of Chinese rural residents will be further raised.In 2012,the level will break through per capita 5000 yuan,almost 100 times more than that in the primary time period.But consumption level does not equal to living standard.To let farmers lead a good life,the government should follow the objective laws;take the overall situation into consideration;coordinate the relations among farmers'consumption level,national subsidies and farmers'production enthusiasm.Therefore,The paper suggests that the historical and objective factors should be attached more importance to.Besides,raising farmers'income and allaying farmers'fear were effective measures in developing the consumptive potential of rural market and promoting the economic sustainable development. 展开更多
关键词 arima model Rural households consumption Economic growth China
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Forecast on Price of Agricultural Futures in China Based on ARIMA Model 被引量:6
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作者 Chunyang WANG 《Asian Agricultural Research》 2016年第11期9-12,16,共5页
The forecast on price of agricultural futures is studied in this paper. We use the ARIMA model to estimate the price trends of agricultural futures,which can help the investors to optimize their investing plans. The s... The forecast on price of agricultural futures is studied in this paper. We use the ARIMA model to estimate the price trends of agricultural futures,which can help the investors to optimize their investing plans. The soybean future contracts are taken as an example to simulate the forecast based on the auto-regression coefficient(p),differential times(d) and moving average coefficient(q). The results show that ARIMA model is better to simulate and forecast the trend of closing prices of soybean futures contract,and it is applicable to forecasting the price of agricultural futures. 展开更多
关键词 Price of agricultural futures arima model Short-term forecast of price
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Forecasting Tesla’s Stock Price Using the ARIMA Model 被引量:1
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作者 Qiangwei Weng Ruohan Liu Zheng Tao 《Proceedings of Business and Economic Studies》 2022年第5期38-45,共8页
The stock market is an important economic information center.The economic benefits generated by stock price prediction have attracted much attention.Although the stock market cannot be predicted accurately,the stock m... The stock market is an important economic information center.The economic benefits generated by stock price prediction have attracted much attention.Although the stock market cannot be predicted accurately,the stock market’s prediction of the trend of stock prices helps in grasping the operation law of the stock market and the influence mechanism on the economy.The autoregressive integrated moving average(ARIMA)model is one of the most widely accepted and used time series forecasting models.Therefore,this paper first compares the return on investment(ROI)of Apple and Tesla,revealing that the ROI of Tesla is much greater than that of Apple,and subsequently focuses on ARIMA model’s prediction on the available time series data,thus concluding that the ARIMA model is better than the Naïve method in predicting the change in Tesla’s stock price trend. 展开更多
关键词 Stock price forecast arima model Naïve method TESLA
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Estimation of Number Of Small Cattle Through ARIMA Models in Turkey
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作者 Senol CELIK 《Journal of Mathematics and System Science》 2015年第11期464-473,共10页
In this study, the number of sheep and goats in Turkey were analysed by time series analysis method, and the number of great cattle for next years predicted through the most appropriate time series model.Time series w... In this study, the number of sheep and goats in Turkey were analysed by time series analysis method, and the number of great cattle for next years predicted through the most appropriate time series model.Time series was formed using the data on the number of sheep and goats belonging to the period between 1930 and 2014 in Turkey It was determined through autocorrelation function graphic that the series weren't stationary at first, but they became stationary after their first difference were calculated. A stagnancy test was performed through extended Dickey-Fuller test. So as to determine the suitability of the model, it was reviewed if autocorrelation and partial autocorrelation graphs were white noise series and also the results of Box-Ljung test were reviwed. Through the "tested models, the model estimations, of which parameter estimates were significant and Akaike information criterion (AIC) was the smallest, were performed. The most appropriate model in terms of both the number of sheep and goats is first-level integrated moving average model stated as ARIMA(0,1,1). In this model, it was estimated that there would be an increase in the number of sheep and goats in Turkey between the years of 2015 and 2020, however, the increase in the number of sheep would be more than the increase in the number of goats. 展开更多
关键词 arima models AUTOCORRELATION the number of sheep the number of goats.
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Forecasting Measles Immunization Coverage Using ARIMA Model 被引量:2
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作者 Rachel T. Alegado Gilbert M. Tumibay 《Journal of Computer and Communications》 2019年第10期157-168,共12页
This study aimed to find a model to forecast monthly measles immunization coverage using Autoregressive Integrated Moving Average (ARIMA). The monthly registered data for measles immunization coverage from January 201... This study aimed to find a model to forecast monthly measles immunization coverage using Autoregressive Integrated Moving Average (ARIMA). The monthly registered data for measles immunization coverage from January 2014 to December 2018 were used for the development of the model. The best model with the smallest Normalized Bayesian Information Criterion (BIC) of 8.673 is ARIMA (0, 1, 0). ARIMA (0, 1, 0) was used to forecast the monthly measles immunization coverage for the next 36 months from January 2018 to December 2020. The results obtained prove that this model can be used for forecasting future immunization coverage and will help decision-makers to establish strategies, priorities, and proper use of immunization resources. 展开更多
关键词 Forecasting MEASLES IMMUNIZATION COVERAGE arima modelING
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Analysis and Forecast of MSW Production Based on the ARIMA Model in Beijing 被引量:1
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作者 Wang Guiqin Zhang Hongyu Dai Zhifeng 《Meteorological and Environmental Research》 CAS 2017年第6期32-35,40,共5页
Based on the data of MSW generation in Beijing from 2004 to 2012,an ARIMA model of time series analysis was established. By contrast of the modeling results of different yearly data,the forecast period was identified ... Based on the data of MSW generation in Beijing from 2004 to 2012,an ARIMA model of time series analysis was established. By contrast of the modeling results of different yearly data,the forecast period was identified to be 10 years. The yearly production of MSW from 2015 to 2025 was forecasted by using SPSS 16. 0 software. Result shows that the forecasting effect of ARIMA( 1,0,1) model is relatively good,and it can be applied to prediction of MSW production in Beijing. In the next 10 years,the amount of MSW produced in Beijing is increasing,but the growth rate is not large. Is expected to 2025,the production of MSW will reach more than 9 million tons. Taking into account the MSW return,it is inferred that the production of MSW in Beijing in 2025 will be close to 10 million tons. In order to reduce the pressure of subsequent waste disposal facilities in Beijing,the government can increase the intensity of the recycling of waste materials. 展开更多
关键词 MSW arima model PRODUCTION FORECAST Time SERIES analysis
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ARIMA MODEL ON WOOD PROPERTIES VARIATION PATTERN OF KOREAN LARCH
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作者 王金满 郭明辉 徐平武 《Journal of Northeast Forestry University》 SCIE CAS CSCD 1996年第4期57-60,共4页
In this paper, according to the theory and method of time-series analysis, the grow ing rings ARIMA model of wood properties variation pattern for Larix olgensis plantation was studied. The model recognition and param... In this paper, according to the theory and method of time-series analysis, the grow ing rings ARIMA model of wood properties variation pattern for Larix olgensis plantation was studied. The model recognition and parameter estimation were discused. The ARIMA model of wood growth ring density, growth ring widith and late wood percentage was obtained. Appling the ARIMA model which obtained from actual test fitted the variation pattem of wood growth ring for Larix olgensis. The result indicated it was an effective method that applied the ARIMA model to study wood growth ring properties variation pattem. By comparing with the actual variation pattem from test data the goodness of fit was good. 展开更多
关键词 LARIX olgensis PLANTATION VARIATION PATTERN Wood properties arima model
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Ecological Resilience Prediction of the Coal Cities in China Based on a Markov-ARIMA Model—Taking Xuzhou as a Case
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作者 XING Qinfeng XUE Weilong WANG Beibei 《Journal of Resources and Ecology》 2026年第2期533-545,共13页
This study takes the ecological resilience of coal cities as the research theme,constructs an index system including 41 constraint factors from the three dimensions of social economy,resources and the environment,and ... This study takes the ecological resilience of coal cities as the research theme,constructs an index system including 41 constraint factors from the three dimensions of social economy,resources and the environment,and takes Xuzhou as a typical case study with data from 2002 to 2023 as the original data.The GM-Markov time series prediction model and ARIMA model are used to fit the developmental prospect of ecological resilience in 2024-2040,with the aim of accurately predicting the future development trend.The results show that Xuzhou will reach the“ideal state”of ecological resilience in 2031 at the earliest and 2032 at the latest.In that state,the case city can better coordinate the contradictory relationship between the“limitation”and“need”of ecological resilience,and realize positive development of the socio-economic,resource and environmental subsystems.Then,the understanding of this research topic is deepened and the following coping strategies are proposed based on the research results:improve the collaborative digital governance co-construction model and lay a solid foundation for ecological resilience,optimize the collaborative digital co-governance mechanism to enhance the efficiency of ecological governance,adhere to the fundamental spirit of shared development and release the dividends of ecological governance. 展开更多
关键词 ecological resilience forecast GM-Markov model arima model
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ARIMA和LSTM模型对变应性鼻炎就诊人数的预测效果比较
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作者 叶文静 陈苗苗 +3 位作者 刘琦 刘克佳 冯天雨 兰欣 《信息与电脑》 2026年第6期45-47,共3页
文章采用自回归移动平均模型(Autoregressive Moving Average Model,ARIMA)与长短期记忆网络(Long Short-Term Memory,LSTM)模型,以花粉浓度和变应性鼻炎就诊人数为变量,来预测变应性鼻炎就诊人数。采集2019年9月—2022年8月西安交通大... 文章采用自回归移动平均模型(Autoregressive Moving Average Model,ARIMA)与长短期记忆网络(Long Short-Term Memory,LSTM)模型,以花粉浓度和变应性鼻炎就诊人数为变量,来预测变应性鼻炎就诊人数。采集2019年9月—2022年8月西安交通大学第一附属医院榆林医院的相关数据,使用Python构建上述两种模型。结果显示,ARIMA模型的均方根误差(Root Mean Square Error,RMSE)为53.86、平均绝对误差(Mean Absolute Error,MAE)为33.61;LSTM模型的MAE为35.37、RMSE为51.96。数据表明,LSTM模型的预测精度更优,可为医院医疗资源配置提供参考。 展开更多
关键词 变应性鼻炎 arima模型 LSTM模型 花粉浓度
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基于VMD-ARIMA的螺杆空压机轴承磨损预测模型
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作者 周亚东 《液压气动与密封》 2026年第2期110-117,共8页
轴承是现代机械设备的核心部件之一,在润滑不充分的情况下,轴承接触面易出现磨损退化,为设备运行带来极大安全隐患。为定量评估螺杆空压机轴承磨损状态,提出一种分解方法和时间序列模型结合的螺杆空压机轴承磨损预测模型。首先,基于VMD(... 轴承是现代机械设备的核心部件之一,在润滑不充分的情况下,轴承接触面易出现磨损退化,为设备运行带来极大安全隐患。为定量评估螺杆空压机轴承磨损状态,提出一种分解方法和时间序列模型结合的螺杆空压机轴承磨损预测模型。首先,基于VMD(Variational Mode Decomposition)方法对螺杆空压机轴承摩擦系数试验数据进行分解,然后通过时间序列分析方法构建VMD-ARIMA(Auto Regressive Integrated Moving Average)模型预测摩擦系数。结果表明:基于VMD-ARIMA模型的预测结果与3组试验数据的平均绝对百分比误差小于0.89%,比传统时间序列模型预测结果的平均绝对百分比误差减少了1.30%,因此,VMD-ARIMA模型在螺杆空压机轴承磨损预测方面具有较好的准确性。 展开更多
关键词 螺杆空压机 磨损预测 VMD分解 arima模型
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2012—2024年灵武市手足口病流行病学特征及ARIMA模型预测分析
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作者 吴亚楠 杨晓燕 +2 位作者 李建鹏 杨帆 张坤 《中华卫生杀虫药械》 2026年第1期119-123,共5页
目的分析宁夏灵武市手足口病流行病学特征及发病趋势,并提出科学防控策略。方法收集灵武市2012—2024年手足口病病例资料,采用描述性流行病学方法,分析灵武市手足口病三间分布特征,并构建自回归移动平均模型(ARIMA)进行预测分析。结果2... 目的分析宁夏灵武市手足口病流行病学特征及发病趋势,并提出科学防控策略。方法收集灵武市2012—2024年手足口病病例资料,采用描述性流行病学方法,分析灵武市手足口病三间分布特征,并构建自回归移动平均模型(ARIMA)进行预测分析。结果2012—2024年灵武市手足口病报告发病率呈波动性,年均报告发病率为77.94/10万,2022年报告发病率最低,为6.06/10万,2019年报告发病率最高,为224.32/10万。全年均有病例报告,发病高峰期主要集中在5—7月和9—11月;从人群分布来看,易感人群以5岁及以下的散居和幼托儿童为主,男童报告发病率高于女童。ARIMA模型显示,2012—2024年手足口病的拟合值与实际观测值高度吻合,平均绝对误差(MAE=18.78)和均方根误差(RMSE=34.79)较小,表明模型拟合效果好,能有效捕捉数据的趋势和季节性特征;预测显示,2025—2027年手足口病仍存在季节性波动,且发病数平稳。结论灵武市手足口病防控应构建以“重点人群、关键时期、科学预警”为核心的联防联控体系,以5岁以下散居与幼托儿童防控为重点,在夏秋季年度双流行高峰来临前做好防控资源调配与应急行动,要强化教育和卫生部门间联动,发挥预警效能。 展开更多
关键词 手足口病 流行特征 arima模型 防控对策
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武咸城际铁路客流时空分布特征与ARIMA客流预测
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作者 王芹芹 《铁道运营技术》 2026年第1期22-26,共5页
客流分析是合理设计列车开行方案和列车运行图的基础与依据。科学合理的列车开行方案与运行图对于提升旅客服务水平,降低运营部门运营成本具有重要意义。以武咸城际铁路为研究对象,旨在系统揭示其客流分布与变化规律,并为运营优化提供... 客流分析是合理设计列车开行方案和列车运行图的基础与依据。科学合理的列车开行方案与运行图对于提升旅客服务水平,降低运营部门运营成本具有重要意义。以武咸城际铁路为研究对象,旨在系统揭示其客流分布与变化规律,并为运营优化提供预测支持。通过分析其开通运营以来的旅客发送量、车站客流分布及列车客座率等指标,重点对比分析了2023年7月运行图调整前后的客流变化。从时间(工作日、周末、节假日)和空间(站间客流OD分布)两个维度梳理了客流分布特征。在此基础上,利用2023年武汉东站(武咸方向)日均客流数据,构建ARIMA时间序列预测模型,并对2024年1月至6月客流进行了短期预测。通过将预测值与实际值对比验证,结果显示模型预测平均相对误差为7%,表明ARIMA模型在城际铁路短期客流预测中具有较高的可靠性,能为列车开行方案优化与运营策略调整提供数据支撑和科学依据。 展开更多
关键词 城际铁路 客流预测 客流特征 arima模型
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基于ARIMA模型的江苏省医疗服务需求预测研究
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作者 刘军军 孙加权 《医院管理论坛》 2026年第2期10-13,9,共5页
目的分析江苏省医疗服务需求现状和变化趋势,并预测未来需求,旨在为合理、有效配置卫生资源提供参考。方法基于2004—2023年江苏省医疗机构诊疗人次和入院人数,构建ARIMA时间序列模型,对2024—2030年江苏省医疗服务需求量进行预测。结果... 目的分析江苏省医疗服务需求现状和变化趋势,并预测未来需求,旨在为合理、有效配置卫生资源提供参考。方法基于2004—2023年江苏省医疗机构诊疗人次和入院人数,构建ARIMA时间序列模型,对2024—2030年江苏省医疗服务需求量进行预测。结果2004—2023年江苏省诊疗人次数、入院人数的实际值与预测值吻合度较高。预测结果显示,2024—2030年的年均诊疗人次为74621.53万次,明显高于2004—2023年的43662.58万次;2024—2030年的年均入院人数为1986.08万人,明显高于2004—2023年的1037.72万人。结论研究验证了ARIMA模型在区域医疗服务需求预测中的有效性,为卫生行政部门推进资源配置优化提供了量化依据。 展开更多
关键词 医疗服务需求 卫生资源配置 arima模型 时间序列预测
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基于ARIMA模型的小型变速水力发电机功率预测
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作者 衣志冲 曾小勇 +1 位作者 刘志国 胡文华 《信息技术》 2026年第2期192-197,共6页
小型变速水力发电机的功率受水流速度、水位等因素影响,且这些因素之间存在复杂的非线性关系,导致预测功率易出现误差。为此,文中提出新的功率预测方法。获取区域控制偏差信号,利用等效控制率及切换控制率控制负荷波动。将现场采集的功... 小型变速水力发电机的功率受水流速度、水位等因素影响,且这些因素之间存在复杂的非线性关系,导致预测功率易出现误差。为此,文中提出新的功率预测方法。获取区域控制偏差信号,利用等效控制率及切换控制率控制负荷波动。将现场采集的功率时间序列组建成自回归积分滑动平均(Autoregressive Integrated Moving Average,ARIMA)模型,利用气象相似日的预测残差组建支持向量回归(Support Vector Regression,SVR)模型,完成发电机功率预测。实验结果表明,采用所提方法进行小型变速水力发电机功率预测后,预测精度得到显著提升,且相关系数最高为0.993。 展开更多
关键词 负荷波动 arima模型 小型变速水力发电机 功率预测
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基于ARIMA模型的湖北省山地区建设项目耕地占用比例预测研究
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作者 李荆荆 邓惠芬 +3 位作者 李彦丹 祝君君 黄凡 匡颖 《湖北大学学报(自然科学版)》 2026年第2期153-165,共13页
湖北省山地区面积占全省土地总面积的56%,山地区的耕地面积仅占全省耕地总面积的12%,耕地资源在山地区尤为稀缺,然而,诸多建设项目由于选址的特殊性,不可避免地面临耕地占用情形。因此,为实现生态优先战略下的土地资源优化配置,亟需探... 湖北省山地区面积占全省土地总面积的56%,山地区的耕地面积仅占全省耕地总面积的12%,耕地资源在山地区尤为稀缺,然而,诸多建设项目由于选址的特殊性,不可避免地面临耕地占用情形。因此,为实现生态优先战略下的土地资源优化配置,亟需探明山地区建设项目占用耕地比例的合理阈值,以达到平衡该区域耕地资源保护和建设项目节约集约用地的目标。基于湖北省2013—2022年交通、能源、水利建设项目以及“十四五”规划建设项目数据,构建自回归移动平均数(ARIMA)时间序列模型来预测建设项目占用耕地比例;结合预测值、历史均值及置信区间上限设定动态阈值;通过“项目通过率—耕地节约率”综合得分来量化评估管控效能。研究结果表明,交通项目未来趋势呈周期性波动,推荐采用预测均值阈值(35.44%),并建议阈值压缩至40%以下;能源项目趋势性上升,推荐采用预测均值阈值(29.67%)作为核心管控基准;水利项目预测值稳定在低位,优先推荐预测均值阈值(5.58%),对新增项目建议上限不超过20%。在耕地保护优先情景下,交通、能源和水利三类项目阈值上限应分别控制在40%、35%、10%;经济发展优先情景下可放宽至45%、38%、15%;平衡发展情景下则建议维持动态阈值策略。本研究构建的建设项目与耕地占用的“预测—校准—反馈”动态框架,希冀为长江经济带生态敏感区内耕地保护目标提供政策依据。 展开更多
关键词 山地建设项目 耕地占用 动态阈值 耕地节约率 arima模型
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基于ARIMA模型的浙江省农产品物流需求分析研究
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作者 余子豪 周志丹 《物流科技》 2026年第3期21-25,共5页
随着经济的不断增长,人们对于健康绿色农产品的需求也在不断增加,农产品物流需求预测对于保障区域农产品供应链的稳定性和效率至关重要。文章旨在通过分析浙江省近40年的农产品产量和产值数据,利用ARIMA模型预测未来10年的产量和产值,... 随着经济的不断增长,人们对于健康绿色农产品的需求也在不断增加,农产品物流需求预测对于保障区域农产品供应链的稳定性和效率至关重要。文章旨在通过分析浙江省近40年的农产品产量和产值数据,利用ARIMA模型预测未来10年的产量和产值,并通过计算物流运输量、冷链物流需求、物流服务价值等指标,分析浙江省农产品未来的物流需求,对于提升浙江省农产品物流系统规模以及促进浙江省冷链物流发展具有重要的参考。 展开更多
关键词 arima模型 农产品物流需求 产量预测 产值预测
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基于ARIMA模型的全球航空碳排放量预测
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作者 王琦 田利军 《中外能源》 2026年第2期8-16,共9页
为应对全球气候变暖背景下航空业碳排放管控需求,把握未来全球航空碳排放趋势,采用自回归差分移动平均模型(ARIMA),对全球航空业未来二氧化碳排放进行建模和预测。基于1940~2024年全球航空碳排放量时间序列数据,采用指数平滑法修复2020~... 为应对全球气候变暖背景下航空业碳排放管控需求,把握未来全球航空碳排放趋势,采用自回归差分移动平均模型(ARIMA),对全球航空业未来二氧化碳排放进行建模和预测。基于1940~2024年全球航空碳排放量时间序列数据,采用指数平滑法修复2020~2022年疫情异常值,构建ARIMA模型并经平稳性与残差检验,确定ARIMA(1,2,1)为最优预测模型。2025~2050年排放趋势多情景预测结果显示:基准情景下2050年排放量达1390.58×10^(6)t,不符合温控目标要求;政策驱动情景在2035年左右达峰,但受SAF产能等限制减排不足;净零情景2050年排放量为278.12×10^(6)t,契合温控要求,但需突破零碳技术商业化和碳移除技术成本瓶颈。未来全球航空业应努力构建跨国协同的政策框架,强化零碳技术研发与产业化支持,完善SAF产业链保障机制,最终实现净零排放目标。 展开更多
关键词 航空碳排放 arima模型 多情景预测 零碳技术 碳移除 净零排放
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