To implement a quantificational evaluation for mechanical kinematic scheme more effectively,a multi-level and multi-objective evaluation model is presented using neural network and fuzzy theory. Firstly,the structure ...To implement a quantificational evaluation for mechanical kinematic scheme more effectively,a multi-level and multi-objective evaluation model is presented using neural network and fuzzy theory. Firstly,the structure of evaluation model is constructed according to evaluation indicator system. Then evaluation samples are generated and provided to train this model. Thus it can reflect the relation between attributive value and evaluation result,as well as the weight of evaluation indicator. Once evaluation indicators of each candidate are fuzzily quantified and fed into the trained network model,the corresponding evaluation result is outputted and the best alternative can be selected. Under this model,expert knowledge can be effectively acquired and expressed,and the quantificational evaluation can be implemented for kinematic scheme with multi-level evaluation indicator system. Several key problems on this model are discussed and an illustration has demonstrated that this model is feasible and can be regarded as a new idea for solving kinematic scheme evaluation.展开更多
With the rise of cloud computing in recent years, a large number of streaming media has yielded an exponential growth in network traffic. With the now present 5G and future 6G, the development of the Internet of Thing...With the rise of cloud computing in recent years, a large number of streaming media has yielded an exponential growth in network traffic. With the now present 5G and future 6G, the development of the Internet of Things (IoT), social networks, video on demand, and mobile multimedia platforms, the backbone network is bound to bear more traffic. The transmission capacity of Single Core Fiber (SCFs) may be limited in the future and Spatial Division Multiplexing (SDM) leveraging multi-core fibers promises to be one of the solutions for the future. Currently, Elastic optical networks (EONs) with multi-core fibers (MCFs) are a kind of SDM-enabled EONs (SDM-EON) used to enhance the capacity of transmission. The resource assignment in MCFs, however, will be subject to Inter-Core Crosstalk (IC-XT), hence, reducing the effectiveness of transmission. This research highlights the routing, modulation level, and spectrum assignment (RMLSA) problems with anycast traffic mode in SDM-EON. A multipath routing scheme is used to reduce the blocking rate of anycast traffic in SDM-EON with the limit of inter-core crosstalk. Hence, an integer linear programming (ILP) problem is formulated and a heuristic algorithm is proposed. Two core-assignment strategies: First-Fit (FF) and Random-Fit (RF) are used and their performance is evaluated through simulations. The simulation results show that the multipath routing method is better than the single-path routing method in terms of blocking ratio and spectrum utilization ratio. Moreover, the FF is better than the RF in low traffic load in terms of blocking ratio (BR), and the opposite in high traffic load. The FF is better than the RF in terms of a spectrum utilization ratio. In an anycast protection problem, the proposed algorithm has a lower BR than previous works.展开更多
While Internet traffic is currently dominated by elastic data transfers, it is anticipated that streaming applications will rapidly develop and contribute a significant amount of traffic in the near future. Therefore,...While Internet traffic is currently dominated by elastic data transfers, it is anticipated that streaming applications will rapidly develop and contribute a significant amount of traffic in the near future. Therefore, it is essential to understand and capture the relation between streaming and elastic traffic behavior. In this paper, we focus on developing simple yet effective approximations to capture this relationship. We study, then, an analytical model to evaluate the end-to-end performance of elastic traffic under multi-queuing system. This model is based on the fluid flow approximation. We assume that network architecture gives the head of priority to real time traffic and shares the remaining capacity between the elastic ongoing flows according to a specific weight.展开更多
分布式新能源以“点多面广”的特征并入各级配电网,电网呈现新能源多层级接入、一体化消纳的特征。为促进新能源的充分消纳与高效利用,提出了一种多层级配电网新能源最大消纳空间测算模型,并将分布式新能源最大消纳空间测算问题转换为...分布式新能源以“点多面广”的特征并入各级配电网,电网呈现新能源多层级接入、一体化消纳的特征。为促进新能源的充分消纳与高效利用,提出了一种多层级配电网新能源最大消纳空间测算模型,并将分布式新能源最大消纳空间测算问题转换为各层级配电网新能源最大消纳空间测算子问题,实现了各层级配电网分布式新能源最大消纳空间的精确测算。首先,以多层级配电网新能源接入量最大为目标函数,基于Distflow潮流模型建立多层级配电网分布式新能源消纳空间测算模型;然后,针对模型非凸以及求解效率低等问题,基于二阶锥松弛将模型转化为混合整数二阶锥规划模型,采用交替方向乘子法(alternating direction method of multipliers,ADMM),将多层级配电网新能源消纳空间测算问题转化为各级配电网新能源最大消纳空间子问题,将消纳空间模型转化为多层级配电网分布式新能源最大消纳空间分解测算模型;最后,以IEEE 6、7、9、10、12、15测试系统为例,验证该方法的有效性。展开更多
基金Supported by the Shanxi Natural Science Foundation under contract number 20041070 and Natural Science Foundation of north u-niversity of China .
文摘To implement a quantificational evaluation for mechanical kinematic scheme more effectively,a multi-level and multi-objective evaluation model is presented using neural network and fuzzy theory. Firstly,the structure of evaluation model is constructed according to evaluation indicator system. Then evaluation samples are generated and provided to train this model. Thus it can reflect the relation between attributive value and evaluation result,as well as the weight of evaluation indicator. Once evaluation indicators of each candidate are fuzzily quantified and fed into the trained network model,the corresponding evaluation result is outputted and the best alternative can be selected. Under this model,expert knowledge can be effectively acquired and expressed,and the quantificational evaluation can be implemented for kinematic scheme with multi-level evaluation indicator system. Several key problems on this model are discussed and an illustration has demonstrated that this model is feasible and can be regarded as a new idea for solving kinematic scheme evaluation.
文摘With the rise of cloud computing in recent years, a large number of streaming media has yielded an exponential growth in network traffic. With the now present 5G and future 6G, the development of the Internet of Things (IoT), social networks, video on demand, and mobile multimedia platforms, the backbone network is bound to bear more traffic. The transmission capacity of Single Core Fiber (SCFs) may be limited in the future and Spatial Division Multiplexing (SDM) leveraging multi-core fibers promises to be one of the solutions for the future. Currently, Elastic optical networks (EONs) with multi-core fibers (MCFs) are a kind of SDM-enabled EONs (SDM-EON) used to enhance the capacity of transmission. The resource assignment in MCFs, however, will be subject to Inter-Core Crosstalk (IC-XT), hence, reducing the effectiveness of transmission. This research highlights the routing, modulation level, and spectrum assignment (RMLSA) problems with anycast traffic mode in SDM-EON. A multipath routing scheme is used to reduce the blocking rate of anycast traffic in SDM-EON with the limit of inter-core crosstalk. Hence, an integer linear programming (ILP) problem is formulated and a heuristic algorithm is proposed. Two core-assignment strategies: First-Fit (FF) and Random-Fit (RF) are used and their performance is evaluated through simulations. The simulation results show that the multipath routing method is better than the single-path routing method in terms of blocking ratio and spectrum utilization ratio. Moreover, the FF is better than the RF in low traffic load in terms of blocking ratio (BR), and the opposite in high traffic load. The FF is better than the RF in terms of a spectrum utilization ratio. In an anycast protection problem, the proposed algorithm has a lower BR than previous works.
文摘While Internet traffic is currently dominated by elastic data transfers, it is anticipated that streaming applications will rapidly develop and contribute a significant amount of traffic in the near future. Therefore, it is essential to understand and capture the relation between streaming and elastic traffic behavior. In this paper, we focus on developing simple yet effective approximations to capture this relationship. We study, then, an analytical model to evaluate the end-to-end performance of elastic traffic under multi-queuing system. This model is based on the fluid flow approximation. We assume that network architecture gives the head of priority to real time traffic and shares the remaining capacity between the elastic ongoing flows according to a specific weight.
文摘分布式新能源以“点多面广”的特征并入各级配电网,电网呈现新能源多层级接入、一体化消纳的特征。为促进新能源的充分消纳与高效利用,提出了一种多层级配电网新能源最大消纳空间测算模型,并将分布式新能源最大消纳空间测算问题转换为各层级配电网新能源最大消纳空间测算子问题,实现了各层级配电网分布式新能源最大消纳空间的精确测算。首先,以多层级配电网新能源接入量最大为目标函数,基于Distflow潮流模型建立多层级配电网分布式新能源消纳空间测算模型;然后,针对模型非凸以及求解效率低等问题,基于二阶锥松弛将模型转化为混合整数二阶锥规划模型,采用交替方向乘子法(alternating direction method of multipliers,ADMM),将多层级配电网新能源消纳空间测算问题转化为各级配电网新能源最大消纳空间子问题,将消纳空间模型转化为多层级配电网分布式新能源最大消纳空间分解测算模型;最后,以IEEE 6、7、9、10、12、15测试系统为例,验证该方法的有效性。
