The simulation of wind power time series is a key process in renewable power allocation planning,operation mode calculation,and safety assessment.Traditional single-point modeling methods discretely generate wind powe...The simulation of wind power time series is a key process in renewable power allocation planning,operation mode calculation,and safety assessment.Traditional single-point modeling methods discretely generate wind power at each moment;however,they ignore the daily output characteristics and are unable to consider both modeling accuracy and efficiency.To resolve this problem,a wind power time series simulation model based on typical daily output processes and Markov algorithm is proposed.First,a typical daily output process classification method based on time series similarity and modified K-means clustering algorithm is presented.Second,considering the typical daily output processes as status variables,a wind power time series simulation model based on Markov algorithm is constructed.Finally,a case is analyzed based on the measured data of a wind farm in China.The proposed model is then compared with traditional methods to verify its effectiveness and applicability.The comparison results indicate that the statistical characteristics,probability distributions,and autocorrelation characteristics of the wind power time series generated by the proposed model are better than those of the traditional methods.Moreover,modeling efficiency considerably improves.展开更多
In ATM networks, bursty sources can be described as the Interrupted Bernoulli Process(IBP). With the use of the thin process theory, the Probability Generating Function(PGF) of the IBP is obtained. An iterative algori...In ATM networks, bursty sources can be described as the Interrupted Bernoulli Process(IBP). With the use of the thin process theory, the Probability Generating Function(PGF) of the IBP is obtained. An iterative algorithm, which can be used to calculate the IBP probability distribution, is presented. The bursty source’s equivalent description is discussed. It is proposed that the leaky bucket output process can be approximately described as the IBP. The accuracy of the analytical results has been largely validated by means of the simulation approach. Moreover, how to improve its accuracy is discussed. The smoothing function of the leaky bucket algorithm is quantitatively analyzed.展开更多
Scholars have used the method of thinking aloud to conduct experiments on the relationship between mother tongue thinking and college students' spoken English output process.Referring to the experimental data,this...Scholars have used the method of thinking aloud to conduct experiments on the relationship between mother tongue thinking and college students' spoken English output process.Referring to the experimental data,this essay try to do a further study on mother tongue thinking' function of each oral output process,especially the function of the idea-organizing.It is designed to enable non-English major college students consciously to take advantage of the positive transfer of mother tongue thinking and take the initiative to adapt to the English thinking pattern in order to achieve the objective of improving their English oral communication skills and ensure the effectiveness of language learning.展开更多
Ever since Schmidt proposed the noticing hypothesis in 1990, the role of consciousness in second language input and output processing has attracted increasing attention from various researchers. In many studies, wheth...Ever since Schmidt proposed the noticing hypothesis in 1990, the role of consciousness in second language input and output processing has attracted increasing attention from various researchers. In many studies, whether or not consciousness is used is deemed as an important factor leading to changes in language learners performance. Current research procedures on measuring consciousness in second language acquisition field are not very satisfactory. The present study, by making use of Levelt s L1 speech pr...展开更多
随着以风电和光伏为代表的新能源渗透率的快速增长,新型电力系统与气象系统间的耦合程度不断加深,系统运行场景分析与生成面临严峻挑战。极端气象事件的频发导致新能源波动加剧,系统运行场景不确定性激增,而现有方法对气象事件与新能源...随着以风电和光伏为代表的新能源渗透率的快速增长,新型电力系统与气象系统间的耦合程度不断加深,系统运行场景分析与生成面临严峻挑战。极端气象事件的频发导致新能源波动加剧,系统运行场景不确定性激增,而现有方法对气象事件与新能源出力间关系的考虑不足,难以准确刻画极端气象事件影响下的新能源出力特性。为此,提出了一种计及极端气象的长时间尺度系统运行场景生成方法。该方法根据极端气象事件时空分布特性对气象因素进行建模,基于插入多个短时间尺度气象事件的年时间序列,通过高斯过程回归(Gaussian process regression,GPR)模型与Copula函数、数据-知识联合驱动方法结合拟合生成完整的年气象场景,然后将气象场景映射到新能源出力场景,最后通过求解机组组合问题得到系统运行场景。使用SG-126节点算例系统对所提方法进行验证,结果表明该方法能够有效考虑极端气象事件给系统运行带来的影响。展开更多
随着我国城市交通的不断发展,非机动电动车的数量不断上升,绿色出行的同时,交通事故也日益增多。为了保证非机动电动车骑行人在道路上的安全,国家逐步制定法规,要求出行需佩戴头盔,各地交通部门执行检查与处罚,对骑行人佩戴头盔的自动...随着我国城市交通的不断发展,非机动电动车的数量不断上升,绿色出行的同时,交通事故也日益增多。为了保证非机动电动车骑行人在道路上的安全,国家逐步制定法规,要求出行需佩戴头盔,各地交通部门执行检查与处罚,对骑行人佩戴头盔的自动检测也提上了日程。提出用改进YOLOv5算法视频识别头盔佩戴情况,通过自组织非机动电动车骑行人头盔佩戴情况的数据集,选取聚类算法修改初始锚定框参数。然后,改进算法来适应样本集合,利用聚合输出网络提高判别的准确率。其中,采用迁移学习来减少训练资源的消耗。经各种场景实验测试的结果表明,在每秒30帧视频流下,检测的均值平均精度(mean average precision,mAP)达到了94.53%,满足对头盔佩戴检测精度和速度的要求。展开更多
基金supported by the China Datang Corporation project“Study on the performance improvement scheme of in-service wind farms”,the Fundamental Research Funds for the Central Universities(2020MS021)the Foundation of State Key Laboratory“Real-time prediction of offshore wind power and load reduction control method”(LAPS2020-07).
文摘The simulation of wind power time series is a key process in renewable power allocation planning,operation mode calculation,and safety assessment.Traditional single-point modeling methods discretely generate wind power at each moment;however,they ignore the daily output characteristics and are unable to consider both modeling accuracy and efficiency.To resolve this problem,a wind power time series simulation model based on typical daily output processes and Markov algorithm is proposed.First,a typical daily output process classification method based on time series similarity and modified K-means clustering algorithm is presented.Second,considering the typical daily output processes as status variables,a wind power time series simulation model based on Markov algorithm is constructed.Finally,a case is analyzed based on the measured data of a wind farm in China.The proposed model is then compared with traditional methods to verify its effectiveness and applicability.The comparison results indicate that the statistical characteristics,probability distributions,and autocorrelation characteristics of the wind power time series generated by the proposed model are better than those of the traditional methods.Moreover,modeling efficiency considerably improves.
文摘In ATM networks, bursty sources can be described as the Interrupted Bernoulli Process(IBP). With the use of the thin process theory, the Probability Generating Function(PGF) of the IBP is obtained. An iterative algorithm, which can be used to calculate the IBP probability distribution, is presented. The bursty source’s equivalent description is discussed. It is proposed that the leaky bucket output process can be approximately described as the IBP. The accuracy of the analytical results has been largely validated by means of the simulation approach. Moreover, how to improve its accuracy is discussed. The smoothing function of the leaky bucket algorithm is quantitatively analyzed.
文摘Scholars have used the method of thinking aloud to conduct experiments on the relationship between mother tongue thinking and college students' spoken English output process.Referring to the experimental data,this essay try to do a further study on mother tongue thinking' function of each oral output process,especially the function of the idea-organizing.It is designed to enable non-English major college students consciously to take advantage of the positive transfer of mother tongue thinking and take the initiative to adapt to the English thinking pattern in order to achieve the objective of improving their English oral communication skills and ensure the effectiveness of language learning.
文摘Ever since Schmidt proposed the noticing hypothesis in 1990, the role of consciousness in second language input and output processing has attracted increasing attention from various researchers. In many studies, whether or not consciousness is used is deemed as an important factor leading to changes in language learners performance. Current research procedures on measuring consciousness in second language acquisition field are not very satisfactory. The present study, by making use of Levelt s L1 speech pr...
文摘随着以风电和光伏为代表的新能源渗透率的快速增长,新型电力系统与气象系统间的耦合程度不断加深,系统运行场景分析与生成面临严峻挑战。极端气象事件的频发导致新能源波动加剧,系统运行场景不确定性激增,而现有方法对气象事件与新能源出力间关系的考虑不足,难以准确刻画极端气象事件影响下的新能源出力特性。为此,提出了一种计及极端气象的长时间尺度系统运行场景生成方法。该方法根据极端气象事件时空分布特性对气象因素进行建模,基于插入多个短时间尺度气象事件的年时间序列,通过高斯过程回归(Gaussian process regression,GPR)模型与Copula函数、数据-知识联合驱动方法结合拟合生成完整的年气象场景,然后将气象场景映射到新能源出力场景,最后通过求解机组组合问题得到系统运行场景。使用SG-126节点算例系统对所提方法进行验证,结果表明该方法能够有效考虑极端气象事件给系统运行带来的影响。
文摘随着我国城市交通的不断发展,非机动电动车的数量不断上升,绿色出行的同时,交通事故也日益增多。为了保证非机动电动车骑行人在道路上的安全,国家逐步制定法规,要求出行需佩戴头盔,各地交通部门执行检查与处罚,对骑行人佩戴头盔的自动检测也提上了日程。提出用改进YOLOv5算法视频识别头盔佩戴情况,通过自组织非机动电动车骑行人头盔佩戴情况的数据集,选取聚类算法修改初始锚定框参数。然后,改进算法来适应样本集合,利用聚合输出网络提高判别的准确率。其中,采用迁移学习来减少训练资源的消耗。经各种场景实验测试的结果表明,在每秒30帧视频流下,检测的均值平均精度(mean average precision,mAP)达到了94.53%,满足对头盔佩戴检测精度和速度的要求。
