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131.
严重事故的预防和缓解是新一代核电厂的重要安全问题。本文主要讨论核电厂严重事故研究和管理中确定严重事故主导事故序列时应考虑的准则问题,包括定性和定量准则以及准则相应的意义。以此为基础,本文整理形成一套推荐中国核电厂进行严重事故主导序列筛选时采用的准则,并以1000MW非能动先进压水堆(AP1000)标准设计为研究对象进行应用尝试。分析表明,严重事故选取准则应从定性和定量两方面阐述。从定性的角度,严重事故的选取应根据核电厂状态划分,在超设计基准事故范围内,选取可能导致堆芯损伤和安全壳旁路,并且在后果上具有包络性的事故序列。从定量的角度,应确定导致核电厂严重事故风险的绝对筛选值和相对筛选值,同时还要包络陡边效应,补充确定论分析和工程经验的成果结论。根据建议准则选取的AP1000严重事故主导序列与其概率安全分析报告中进行重点分析的严重事故序列基本吻合。 相似文献
132.
四角锥系空间桁架的临界荷载 总被引：1，自引：0，他引：1
根据刚度等效的原理,将四角锥系空间桁架比拟为实腹梁,分析桁架的等效弯、扭刚度对其临界荷载的影响,导出桁架的临界荷载计算公式。多个典型实际算例的计算结果与有限元结果的误差在±5％以内,满足工程设计计算精度要求。 相似文献
133.
基于Nakazawa教授提供的有关20世纪70年代到2008年相关船舶数据,对船舶特定输出功率(SOP)进行定量分析,探讨船舶运输效率的发展趋势和制约因素. 相似文献
134.
提出并初步实现了基于电力线载波的三级架构的远程无线抄表系统,其中基于S3C2410处理器的集中器的设计开发为远程抄表系统的核心。该集中器可用于家用三表的远程抄表,与传统的人工抄表、电话线抄表相比,极大地提高了效率。同时在设计中增加了除电力线外的其他通信接口,便于因地制宜地采用符合实际的通信方式。 相似文献
135.
《高技术通讯(英文版)》2024,30(2):188-198
Power line communication(PLC)has the potential to become the preferred technique for provi-ding broadband communication to homes and offices with advantage of eliminating the need for new wiring infrastructure and reducing the cost.But it suffers from the impulsive noise because it intro-duces significant time variance into the power line channel.In this paper,a polar codes based or-thogonal frequency division multiplexing(OFDM)PLC system is proposed to deal with the impulsive noise and thereby improve the transmission performance.Firstly,the impulsive noise is modelled with a multi-damped sine function by analyzing the time behavior of impulse events.Then the polar codes are used to combat the impulsive noise of PLC channel,and a low complexity bit-flipping de-coding method based on CRC-aided successive cancellation list(CA-SCL)decoding algorithm is pro-posed.Simulations evaluate the proposed decoding algorithm and the results validate the suggested polar codes based OFDM-PLC scheme which can improve the BER performance of PLC with impul-sive interference. 相似文献
136.
为了不断提高民航飞行学员养成训练过程中的有效性和科学性,客观量化飞行员的认知分配方式和认知负荷成为综合评价飞行操纵绩效的重要评估手段。本论文设计了一种基于模拟飞行软件结合屏幕眼动仪的多通道参数采集方法获取受试者执行矩形起落航线训练科目过程中的飞行参数和眼动数据,通过布林带理论建立飞行操纵绩效评价模型,重点从兴趣区注视时间百分比、静止注视熵和注视访问平均时间等数据维度出发分析了飞行员的认知分配策略、认知灵活性与复杂性、认知负荷状态,对比不同操纵绩效的飞行员在起落航线的认知特征。研究结果表明：不同飞行绩效的飞行员认知特征基本一致,但飞行绩效优的飞行员表现为认知分配掌控精确性、状态稳定性和灵活性更佳,认知负荷水平更低,因任务难度变化引起的认知负荷波动更小。 相似文献
137.
Xiaohang Ren;Wenting Jiang;Qiang Ji;Pengxiang Zhai; 《Journal of forecasting》2024,43(7):2809-2821
In this paper, we propose a novel imaging method to forecast the daily price data of West Texas Intermediate (WTI) crude oil futures. We use convolutional neural networks (CNNs) for future price trend prediction and obtain higher prediction accuracy than other benchmark forecasting methods. The results show that images can contain more nonlinear information, which is beneficial for energy price forecasting. Nonlinear factors also have a strong influence during drastic fluctuations in crude oil prices. In the robustness tests, we find that the image-based CNN is the most stable approach and can be applied in various futures forecasting scenarios. In the prediction of low-frequency models for high-frequency data, the CNN method still retains considerable predictive power, indicating the possibility of transfer learning of our novel approach. By unleashing the power of the picture, we open up a whole new perspective for forecasting future energy trends. 相似文献
138.
Philip Hans Franses;Jiahui Zou;Wendun Wang; 《Journal of forecasting》2024,43(8):3194-3202
This paper puts forward a new and simple method to combine forecasts, which is particularly useful when the forecasts are strongly correlated. It is based on the Mincer Zarnowitz regression, and a subsequent determination using Shapley values of the weights of the forecasts in a new combination. For a stylized case, it is proved that such a Shapley-value-based combination improves upon an equal-weight combination. Simulation experiments and a detailed illustration show the merits of the Shapley-value-based forecast combination. 相似文献
139.
Gongyue Jiang;Gaoxiu Qiao;Lu Wang;Feng Ma; 《Journal of forecasting》2024,43(6):2378-2398
From the cross-market perspective, this paper investigates crude oil volatility index (OVX) forecasts by proposing a hybrid method, which combines the data-driven SVR technique and parametric models. In terms of parametric models, we utilize GARCH-type models with jumps, and the forecasting effects of five non-parametric jumps (including interday and intraday jump tests) of stock market are also explored. Empirical results show that our approach can substantially increase forecasting accuracy. In addition, the model confidence set test and robust test reaffirm the superiority of the novel hybrid method. From the assessment of economic significance, the advantages of the hybrid method for volatility index forecasting are further confirmed. All these findings imply that jumps of stock market can be helpful in forecasting OVX, especially after the introduction of the hybrid method. Our work can certainly provide a new insight for volatility forecasting and cross-market research. 相似文献
140.
Partha Sengupta;Christopher H. Wheeler; 《Journal of forecasting》2024,43(7):2448-2477
Models developed by banks to forecast losses in their credit card portfolios have generally performed poorly during the COVID-19 pandemic, particularly in 2020, when large forecast errors were observed at many banks. In this study, we attempt to understand the source of this error and explore ways to improve model fit. We use account-level monthly performance data from the largest credit card banks in the U.S. between 2008 and 2018 to build models that mimic the typical model design employed by large banks to forecast credit card losses. We then fit these on data from 2019 to 2021. We find that COVID-period model errors can be reduced significantly through two simple modifications: (1) including measures of the macroeconomic environment beyond indicators of the labor market, which served as the primary macro drivers used in many pre-pandemic models and (2) adjusting macro drivers to capture persistent/sustained changes, as opposed to temporary volatility in these variables. These model improvements, we find, can be achieved without a significant reduction in model performance for the pre-COVID period, including the Great Recession. Moreover, in broadening the set of macro influences and capturing sustained changes, we believe models can be made more robust to future downturns, which may bear little resemblance to past recessions. 相似文献