电网故障下双馈风力发电机控制改进与仿真

随着风电装机规模的不断增加,作为未来能源互联网中重要的一环,风电机组应对电网故障的能力越加显得重要。针对双馈风力发电机组在电网故障下的暂态特性,提出了一种基于电网故障类型区分、控制器设计和辅助设备穿越的综合控制策略。相比于传统的控制方法,克服了控制误差大和响应滞后的问题,真正实现了系统的精细化控制。基于MATLAB和VC++联合建模,利用MEX技术搭建了电网故障下的1.5 MW双馈风力发电系统模型,仿真结果验证了所提出的综合控制策略在电网故障下提高双馈风力发电机控制的有效性。     

双参数优先级递推式变采样周期调度算法

针对资源受限的网络控制系统,提出了一种基于双参数优先级的递推式变采样周期动态调度算法。计算控制回路的网络需求度和网络紧急度双参数,并以控制回路误差的绝对值建立二次平方根映射函数来确定双参数权重,实现对传感器优先级的调度。同时,综合分析控制回路性能递推动态调节各控制回路的采样周期,在保证控制系统的稳定的前提下完成调度调节。仿真表明该调度算法提高了网络控制系统的控制质量。     

自适应的无线融断网络路由算法研究

无线融断网络具有长延时、高动态拓扑、链路不稳定等特点,伴随着网络联接缺乏源端到目的端的持续性,为解决网络通信困难的问题,将多头绒泡菌的智能性和自适应性引入,提出一种自适应的无线融断网络路由算法。搭建无线融断网络模型,推导出链路容量的数学表达;设计下一跳节点的选择策略和最佳路由选择策略,实现在融断网络环境下的数据尽力投递。仿真实验表明,该算法能够在网络开销率较低的情况下,达到良好的数据投递,且平均延迟小。     

Model averaging estimation for conditional volatility models with an application to stock market volatility forecast

This paper is concerned with model averaging estimation for conditional volatility models. Given a set of candidate models with different functional forms, we propose a model averaging estimator and forecast for conditional volatility, and construct the corresponding weight-choosing criterion. Under some regulatory conditions, we show that the weight selected by the criterion asymptotically minimizes the true Kullback–Leibler divergence, which is the distributional approximation error, as well as the Itakura–Saito distance, which is the distance between the true and estimated or forecast conditional volatility. Monte Carlo experiments support our newly proposed method. As for the empirical applications of our method, we investigate a total of nine major stock market indices and make a 1-day-ahead volatility forecast for each data set. Empirical results show that the model averaging forecast achieves the highest accuracy in terms of all types of loss functions in most cases, which captures the movement of the unknown true conditional volatility.     

Incorporating textual and management factors into financial distress prediction: A comparative study of machine learning methods

Financial distress prediction (FDP) has been widely considered as a promising approach to reducing financial losses. While financial information comprises the traditional factors involved in FDP, nonfinancial factors have also been examined in recent studies. In light of this, the purpose of this study is to explore the integrated factors and multiple models that can improve the predictive performance of FDP models. This study proposes an FDP framework to reveal the financial distress features of listed Chinese companies, incorporating financial, management, and textual factors, and evaluating the prediction performance of multiple models in different time spans. To develop this framework, this study employs the wrapper-based feature selection method to extract valuable features, and then constructs multiple single classifiers, ensemble classifiers, and deep learning models in order to predict financial distress. The experiment results indicate that management and textual factors can supplement traditional financial factors in FDP, especially textual ones. This study also discovers that integrated factors collected 4 years prior to the predicted benchmark year enable a more accurate prediction, and the ensemble classifiers and deep learning models developed can achieve satisfactory FDP performance. This study makes a novel contribution as it expands the predictive factors of financial distress and provides new findings that can have important implications for providing early warning signals of financial risk.     

A comparison of conditional predictive ability of implied volatility and realized measures in forecasting volatility

In a conditional predictive ability test framework, we investigate whether market factors influence the relative conditional predictive ability of realized measures (RMs) and implied volatility (IV), which is able to examine the asynchronism in their forecasting accuracy, and further analyze their unconditional forecasting performance for volatility forecast. Our results show that the asynchronism can be detected significantly and is strongly related to certain market factors, and the comparison between RMs and IV on average forecast performance is more efficient than previous studies. Finally, we use the factors to extend the empirical similarity (ES) approach for combination of forecasts derived from RMs and IV.     

初探地理国情普查与省级基础测绘的协同生产

本文主要讲述地理国情普查与基础测绘的主要技术工艺及其协同生产的方式方法。明确基础测绘与地理国情项目的区别与联系,在实际作业中突出重点、避免重复,可以事半功倍。     

七届二中全会是党的一次“城市工作会议”解析

1949年3月,中共中央召开的七届二中全会围绕城市工作的开展进行了详细分析,被毛泽东称为进城前的一次"城市工作会议"。会议确立了城市工作在党内的重心地位,提出大家进城后必须以生产建设为重心,学会管理和建设城市,这些建政思想为新中国成立后国民经济的恢复和发展奠定了基础,也为新中国的建立和建设做出了卓越的历史贡献。