As internet services newly emerge with diversity and complexity, great challenges and demands are presented to the Open Flow controlled software defined optical networks(SDON) to achieve better match between services ...As internet services newly emerge with diversity and complexity, great challenges and demands are presented to the Open Flow controlled software defined optical networks(SDON) to achieve better match between services and SDON. With this aim, this paper proposes a naive Echo-State-Network(Naive-ESN) based services awareness algorithm of the software defined optical network, where the naive ESN model adopts the ring topology structure and generates the probability output result to determine the Qo S policy of SDON. Moreover, the Naive-ESN engine is also designed in controller node of SDON to perform services awareness by obtaining service traffic features from data plan, together with some necessary extension of the Open Flow protocol. Test results show that the proposed approach is able to improved services-oriented supporting ability of SDON.展开更多
火电机组在现代电力系统中承担着大量的调峰调频任务,通过运行参数建立出力预测模型有助于快速稳定地调整功率。提出一种改进的深度回声状态网络(Deep Echo State Networks,DESN)用于建立机组出力预测模型。该改进型具备可变的记忆能力...火电机组在现代电力系统中承担着大量的调峰调频任务,通过运行参数建立出力预测模型有助于快速稳定地调整功率。提出一种改进的深度回声状态网络(Deep Echo State Networks,DESN)用于建立机组出力预测模型。该改进型具备可变的记忆能力以应对调整部分运行参数作用于机组出力变化存在的延时性,并根据运行参数聚类生成输入权重进一步挖掘运行参数与出力之间的映射信息。利用华北地区某火电机组不同工作状况下的两种数据集验证了模型效果。结果表明,改进得到的KM-VML-DESN相较于深度回声状态网络、多层感知机、长短期记忆网络等具备更强的预测性能。展开更多
基金supported by the Science and Technology Project of State Grid Corporation of China:“Research on the Power-Grid Services Oriented “IP+Optical” Coordination Choreography Technology”.
文摘As internet services newly emerge with diversity and complexity, great challenges and demands are presented to the Open Flow controlled software defined optical networks(SDON) to achieve better match between services and SDON. With this aim, this paper proposes a naive Echo-State-Network(Naive-ESN) based services awareness algorithm of the software defined optical network, where the naive ESN model adopts the ring topology structure and generates the probability output result to determine the Qo S policy of SDON. Moreover, the Naive-ESN engine is also designed in controller node of SDON to perform services awareness by obtaining service traffic features from data plan, together with some necessary extension of the Open Flow protocol. Test results show that the proposed approach is able to improved services-oriented supporting ability of SDON.
文摘火电机组在现代电力系统中承担着大量的调峰调频任务,通过运行参数建立出力预测模型有助于快速稳定地调整功率。提出一种改进的深度回声状态网络(Deep Echo State Networks,DESN)用于建立机组出力预测模型。该改进型具备可变的记忆能力以应对调整部分运行参数作用于机组出力变化存在的延时性,并根据运行参数聚类生成输入权重进一步挖掘运行参数与出力之间的映射信息。利用华北地区某火电机组不同工作状况下的两种数据集验证了模型效果。结果表明,改进得到的KM-VML-DESN相较于深度回声状态网络、多层感知机、长短期记忆网络等具备更强的预测性能。
