نتایج جستجو برای: loss minimization
تعداد نتایج: 475131 فیلتر نتایج به سال:
Power packet dispatching system has been proposed for smart power management in the form of discretized packet. In this paper, we discuss routing optimization packets on network routers. We propose a cost metric delivery by circuit analysis router network. Using metric, formulate problem as general shortest path from source node to load node. The result numerical simulations shows that algorith...
Single-Solution Hypervolume Maximization and its use for Improving Generalization of Neural Networks
This paper introduces the hypervolume maximization with a single solution as an alternative to the mean loss minimization. The relationship between the two problems is proved through bounds on the cost function when an optimal solution to one of the problems is evaluated on the other, with a hyperparameter to control the similarity between the two problems. This same hyperparameter allows highe...
Consolidation of shunt capacitors plays an important role in radial distribution networks. Among many of their merits, line loss and total harmonic distortion (THD) reduction, voltage profile improvement and reactive power compensation can be the salient specifications of shunt capacitors. Studies show that non-optimal locations shunt capacitor units lead to increase loss, together with bad eff...
Distributed Generations (DGs) are utilized to supply the active and reactive power in the transmission and distribution systems. These types of power sources have many benefits such as power quality enhancement, voltage deviation reduction, power loss reduction, load shedding reduction, reliability improvement, etc. In order to reach the above benefits, the optimal placement and sizing of DG is...
Neural autoregressive sequence models are used to generate sequences in a variety of natural language processing (NLP) tasks, where they evaluated according sequence-level task losses. These typically trained with maximum likelihood estimation, which ignores the loss, yet empirically performs well as surrogate objective. Typical approaches directly optimizing loss such policy gradient and minim...
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