F_(10.7)指数是太阳活动的重要指标,准确预测F_(10.7)指数有助于预防和缓解太阳活动对无线电通信、导航和卫星通信等领域的影响.基于F_(10.7)射电流量的特性,在双向长短时记忆网络(Bidirectional Long Short-Term Memory Network,BiLSTM...F_(10.7)指数是太阳活动的重要指标,准确预测F_(10.7)指数有助于预防和缓解太阳活动对无线电通信、导航和卫星通信等领域的影响.基于F_(10.7)射电流量的特性,在双向长短时记忆网络(Bidirectional Long Short-Term Memory Network,BiLSTM)基础上融入注意力机制(Attention),提出了一种基于BiLSTM-Attention的F_(10.7)预报模型.在加拿大DRAO数据集上其平均绝对误差(MAE)为5.38,平均绝对百分比误差(MAPE)控制在5%以内,相关系数(R)高达0.987,与其他RNN模型相比拥有优越的预测性能.针对中国廊坊L&S望远镜观测的F_(10.7)数据集,提出了一种转换平均校准(Conversion Average Calibration,CAC)方法进行数据预处理,处理后的数据与DRAO数据集具有较高的相关性.基于该数据集对比分析了RNN系列模型的预报效果,实验结果表明,BiLSTM-Attention和BiLSTM两种模型在预测F_(10.7)指数方面具有较好的优势,表现出较好的预测性能和稳定性.展开更多
本文基于连续介质力学和理性扩展热力学分析流程,将L-S(Lord and Shulman)热弹性理论与声弹性理论相结合,建立L-S热声弹性理论的基本框架,包括运动学、力学与热力学、本构方程与演化方程、基本场方程四部分。在运动学部分,区分了Lagrang...本文基于连续介质力学和理性扩展热力学分析流程,将L-S(Lord and Shulman)热弹性理论与声弹性理论相结合,建立L-S热声弹性理论的基本框架,包括运动学、力学与热力学、本构方程与演化方程、基本场方程四部分。在运动学部分,区分了Lagrange描述和Euler描述,以及3种不同的状态和构形,同时针对热声弹性情况定义了两类从自然状态到初始状态的转变过程;在力学与热力学部分,给出了质量守恒定律、动量守恒定律、角动量守恒定律、能量守恒定律以及熵产不等式,从而引出经典不可逆热力学的局限性;在本构方程与演化方程部分,介绍了扩展不可逆热力学原理,并基于理性扩展热力学流程,推导了从自然状态到初始状态、从初始状态到最终状态的热声弹性本构方程与演化方程,将热流作为本构自变量并考虑了热流与应变和温度的相关性;在最后一部分给出了基本场方程的运动方程形式和适用于数值模拟的一阶速度-应力-热流-温度微分方程。展开更多
The existence of solutions for singular nonlinear two point boundary value problems subject to Sturm Liouville boundary conditions with p Laplacian operators is studied by the method of upper and lower solution...The existence of solutions for singular nonlinear two point boundary value problems subject to Sturm Liouville boundary conditions with p Laplacian operators is studied by the method of upper and lower solutions. The proof is based on an application of Schauder’s fixed point theorem to a modified problem whose solutions are that of the original one. At the same time, Arzela Ascoli theorem is used to prove that the defined operator N is a compact map.展开更多
Learning a mapping between an input space and an output.space from training data canbe viewed as a problem of function approximation,which means that different criteria result in learningapproaches of different abilit...Learning a mapping between an input space and an output.space from training data canbe viewed as a problem of function approximation,which means that different criteria result in learningapproaches of different abilities.Among them,projection criterion proposed by one of the authors aimsdirectly at optimal generalization.The projection idea leads to three specific learning approaches,projection learning,partial projection learning,and averaged projection learning,and a framework of afamily of projection learning called S-L projection learning is established to discuss infinite kinds oflearning.S-L projection learning has a different form from the three methods,and it is not easy to analyzetheir relationship.This paper focuses on an equivalent form of S-L projection learning,which shows thatit is a transformed version of partial projection learning.展开更多
A convenient synthetic approach leading to protected inositol was described based on regioselective O-alkylation using alkyl halide under solid-liquid PTC condition
文摘F_(10.7)指数是太阳活动的重要指标,准确预测F_(10.7)指数有助于预防和缓解太阳活动对无线电通信、导航和卫星通信等领域的影响.基于F_(10.7)射电流量的特性,在双向长短时记忆网络(Bidirectional Long Short-Term Memory Network,BiLSTM)基础上融入注意力机制(Attention),提出了一种基于BiLSTM-Attention的F_(10.7)预报模型.在加拿大DRAO数据集上其平均绝对误差(MAE)为5.38,平均绝对百分比误差(MAPE)控制在5%以内,相关系数(R)高达0.987,与其他RNN模型相比拥有优越的预测性能.针对中国廊坊L&S望远镜观测的F_(10.7)数据集,提出了一种转换平均校准(Conversion Average Calibration,CAC)方法进行数据预处理,处理后的数据与DRAO数据集具有较高的相关性.基于该数据集对比分析了RNN系列模型的预报效果,实验结果表明,BiLSTM-Attention和BiLSTM两种模型在预测F_(10.7)指数方面具有较好的优势,表现出较好的预测性能和稳定性.
文摘本文基于连续介质力学和理性扩展热力学分析流程,将L-S(Lord and Shulman)热弹性理论与声弹性理论相结合,建立L-S热声弹性理论的基本框架,包括运动学、力学与热力学、本构方程与演化方程、基本场方程四部分。在运动学部分,区分了Lagrange描述和Euler描述,以及3种不同的状态和构形,同时针对热声弹性情况定义了两类从自然状态到初始状态的转变过程;在力学与热力学部分,给出了质量守恒定律、动量守恒定律、角动量守恒定律、能量守恒定律以及熵产不等式,从而引出经典不可逆热力学的局限性;在本构方程与演化方程部分,介绍了扩展不可逆热力学原理,并基于理性扩展热力学流程,推导了从自然状态到初始状态、从初始状态到最终状态的热声弹性本构方程与演化方程,将热流作为本构自变量并考虑了热流与应变和温度的相关性;在最后一部分给出了基本场方程的运动方程形式和适用于数值模拟的一阶速度-应力-热流-温度微分方程。
文摘The existence of solutions for singular nonlinear two point boundary value problems subject to Sturm Liouville boundary conditions with p Laplacian operators is studied by the method of upper and lower solutions. The proof is based on an application of Schauder’s fixed point theorem to a modified problem whose solutions are that of the original one. At the same time, Arzela Ascoli theorem is used to prove that the defined operator N is a compact map.
文摘Learning a mapping between an input space and an output.space from training data canbe viewed as a problem of function approximation,which means that different criteria result in learningapproaches of different abilities.Among them,projection criterion proposed by one of the authors aimsdirectly at optimal generalization.The projection idea leads to three specific learning approaches,projection learning,partial projection learning,and averaged projection learning,and a framework of afamily of projection learning called S-L projection learning is established to discuss infinite kinds oflearning.S-L projection learning has a different form from the three methods,and it is not easy to analyzetheir relationship.This paper focuses on an equivalent form of S-L projection learning,which shows thatit is a transformed version of partial projection learning.
文摘A convenient synthetic approach leading to protected inositol was described based on regioselective O-alkylation using alkyl halide under solid-liquid PTC condition
