A new efficient coupling relationship description method has been developed to provide an automated and visualized way to multidisciplinary design optimization (MDO) modeling and solving. The disciplinary relation mat...A new efficient coupling relationship description method has been developed to provide an automated and visualized way to multidisciplinary design optimization (MDO) modeling and solving. The disciplinary relation matrix (DRM) is proposed to describe the coupling relationship according to disciplinary input/output variables, and the MDO definition has been reformulated to adopt the new interfaces. Based on these, a universal MDO solving procedure is proposed to establish an automated and efficient way for MDO modeling and solving. Through a simple and convenient initial configuration, MDO problems can be solved using any of available MDO architectures with no further effort. Several examples are used to verify the proposed MDO modeling and solving process. Result shows that the DRM method has the ability to simplify and automate the MDO procedure, and the related MDO framework can evaluate the MDO problem automatically and efficiently.展开更多
Smart cities have different contradicting goals having no apparent solution.The selection of the appropriate solution,which is considered the best compromise among the candidates,is known as complex problem-solving.Sm...Smart cities have different contradicting goals having no apparent solution.The selection of the appropriate solution,which is considered the best compromise among the candidates,is known as complex problem-solving.Smart city administrators face different problems of complex nature,such as optimal energy trading in microgrids and optimal comfort index in smart homes,to mention a few.This paper proposes a novel architecture to offer complex problem solutions as a service(CPSaaS)based on predictive model optimization and optimal task orchestration to offer solutions to different problems in a smart city.Predictive model optimization uses a machine learning module and optimization objective to compute the given problem’s solutions.The task orchestration module helps decompose the complex problem in small tasks and deploy them on real-world physical sensors and actuators.The proposed architecture is hierarchical and modular,making it robust against faults and easy to maintain.The proposed architecture’s evaluation results highlight its strengths in fault tolerance,accuracy,and processing speed.展开更多
This paper establishes a mathematical model of the reliability optimization design for the safe-arming system of an air-faced missile, and presents a solving method for the model. The computational results provide a v...This paper establishes a mathematical model of the reliability optimization design for the safe-arming system of an air-faced missile, and presents a solving method for the model. The computational results provide a valuable reference for the reliability design for the safe-arming system of an air-faced missile.展开更多
间接边界积分方程法IBIEM(indirect boundary integral equation method)求解波动问题时控制方程基本解构造依赖经验判断和试算,导致宽频散射求解不够稳定。本文通过粒子群优化-人工神经网络建立IBIEM控制方程基本解构造模型,以数据驱...间接边界积分方程法IBIEM(indirect boundary integral equation method)求解波动问题时控制方程基本解构造依赖经验判断和试算,导致宽频散射求解不够稳定。本文通过粒子群优化-人工神经网络建立IBIEM控制方程基本解构造模型,以数据驱动代替经验判断,处理基本解构造过程中的不确定性。以二维峡谷对平面SH波散射IBIEM模拟为例验证所建模型的可靠性。结果表明,所建IBIEM控制方程基本解构造模型可对虚拟波源位置和数量的最优设置进行有效预测,兼顾计算效率和精度,大幅提高IBIEM求解波动问题时的稳定性和高效性;虚拟波源位置和数量最优设置方案受入射波频率和场地几何条件影响显著,且表现出非单调变化特征,依据经验设置基本解可靠性较差,以数据驱动的预测模型具有明显优势。本文所建方法可为IBIEM求解其他类型场地地震波动问题提供参考。展开更多
传统TCP(transmission control protocol)本是为有线网络设计,它假设包丢失全是由网络拥塞引起,这个假设不能适应于MANET (mobile ad hoc network),因为MANET 中除了拥塞丢包以外,还存在由于较高比特误码率、路由故障等因素引起的丢包现...传统TCP(transmission control protocol)本是为有线网络设计,它假设包丢失全是由网络拥塞引起,这个假设不能适应于MANET (mobile ad hoc network),因为MANET 中除了拥塞丢包以外,还存在由于较高比特误码率、路由故障等因素引起的丢包现象.当出现非拥塞因素丢包时,传统 TCP 将错误地触发拥塞控制,从而引起TCP 性能低下.任何改进机制都可以分为发现问题和解决问题两个阶段.首先概括了 MANET 中影响 TCP 性能的若干问题;然后针对发现问题和解决问题两个阶段,详细地对每一阶段中存在的各种可行方法进行了分类、分析和比较;最后指出了 MANET 中 TCP 性能优化的研究方向.展开更多
基金supported by the National Natural Science Foundation of China(51505385)Shanghai Aerospace Science and Technology Innovation Foundation(SAST2015010)the Defense Basic Research Program(JCKY2016204B102)
文摘A new efficient coupling relationship description method has been developed to provide an automated and visualized way to multidisciplinary design optimization (MDO) modeling and solving. The disciplinary relation matrix (DRM) is proposed to describe the coupling relationship according to disciplinary input/output variables, and the MDO definition has been reformulated to adopt the new interfaces. Based on these, a universal MDO solving procedure is proposed to establish an automated and efficient way for MDO modeling and solving. Through a simple and convenient initial configuration, MDO problems can be solved using any of available MDO architectures with no further effort. Several examples are used to verify the proposed MDO modeling and solving process. Result shows that the DRM method has the ability to simplify and automate the MDO procedure, and the related MDO framework can evaluate the MDO problem automatically and efficiently.
基金This research was supported by Energy Cloud R&D Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Science,ICT(2019M3F2A1073387)this research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(2018R1D1A1A09082919)this research was supported by Institute for Information&communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.2018-0-01456,AutoMaTa:Autonomous Management framework based on artificial intelligent Technology for adaptive and disposable IoT).Any correspondence related to this paper should be addressed to Dohyeun Kim.
文摘Smart cities have different contradicting goals having no apparent solution.The selection of the appropriate solution,which is considered the best compromise among the candidates,is known as complex problem-solving.Smart city administrators face different problems of complex nature,such as optimal energy trading in microgrids and optimal comfort index in smart homes,to mention a few.This paper proposes a novel architecture to offer complex problem solutions as a service(CPSaaS)based on predictive model optimization and optimal task orchestration to offer solutions to different problems in a smart city.Predictive model optimization uses a machine learning module and optimization objective to compute the given problem’s solutions.The task orchestration module helps decompose the complex problem in small tasks and deploy them on real-world physical sensors and actuators.The proposed architecture is hierarchical and modular,making it robust against faults and easy to maintain.The proposed architecture’s evaluation results highlight its strengths in fault tolerance,accuracy,and processing speed.
文摘This paper establishes a mathematical model of the reliability optimization design for the safe-arming system of an air-faced missile, and presents a solving method for the model. The computational results provide a valuable reference for the reliability design for the safe-arming system of an air-faced missile.
文摘间接边界积分方程法IBIEM(indirect boundary integral equation method)求解波动问题时控制方程基本解构造依赖经验判断和试算,导致宽频散射求解不够稳定。本文通过粒子群优化-人工神经网络建立IBIEM控制方程基本解构造模型,以数据驱动代替经验判断,处理基本解构造过程中的不确定性。以二维峡谷对平面SH波散射IBIEM模拟为例验证所建模型的可靠性。结果表明,所建IBIEM控制方程基本解构造模型可对虚拟波源位置和数量的最优设置进行有效预测,兼顾计算效率和精度,大幅提高IBIEM求解波动问题时的稳定性和高效性;虚拟波源位置和数量最优设置方案受入射波频率和场地几何条件影响显著,且表现出非单调变化特征,依据经验设置基本解可靠性较差,以数据驱动的预测模型具有明显优势。本文所建方法可为IBIEM求解其他类型场地地震波动问题提供参考。
