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In this paper, a novel optimization method is proposed to minimize the fuel consumption for plug-in hybrid electric vehicles (PHEVs). First, the quadratic relationship between fuel rate and battery power is constructed. Then, based on the above relationship, the optimal battery power sequence can be gained by quadratic programming (QP). In addition, to find the optimal engine on-off command, genetic...
In this paper, we propose a throughput-maximum resource provision scheme in the OFDMA-based Wireless Virtual Network (WVN). The proposed scheme takes the dynamics of both traffic arrivals and wireless channels into consideration. Furthermore, we consider a more flexible service contract where average resource provision is guaranteed for each slice. As it is practically impossible to know future traffic...
User viewing feature can be extracted from TV user's channel viewing data for improving the targeted TV advertising. In this paper, we propose a basic viewing feature extraction algorithm in small sample environment to prove the algorithm logic and check the analysis process quickly. However if the viewing behavior data come from mass TV audience, it requires higher speed feature extraction algorithm...
A novel RB-WC-FI-FB (robust worst-case frequency invariance forward-backward) wideband beam former is proposed in this paper. It is developed to improve the robustness against estimation errors of direction of arrival (DOA) and limited sample number, as well as reduce the number of constraints. By incorporating forward-backward estimation and worst-case performance optimization method into the linearly...
The integration of renewable energy sources(RES) and electric vehicles' charging and swapping facilities can effectively improve the efficiency of clean energy utilization and carbon emission reduction. How to establish a reasonable energy exchange model of PV-based battery switch stations (BSSs) is still an important research field which is being studied. This paper focuses on the model building...
TBB (Thread Building Blocking) is currently a representative parallel computing platform of multi-core processors. The ant colony algorithm is used to solve combinatorial optimization problem of discrete-time systems. With the expansion of the problem scale, it often results in rapid increase of calculation. Based on TBB a parallel ant colony algorithm was researched and developed to improve the efficiency...
In the conventional regularized learning, training time increases as the training set expands. Recent work on L2 linear SVM challenges this common sense by proposing the inverse time dependency on the training set size. In this paper, we first put forward a Primal Gradient Solver (PGS) to effectively solve the convex regularized learning problem. This solver is based on the stochastic gradient descent...
Dimension reduction (DR) algorithms are generally categorized into feature extraction and feature selection algorithms. In the past, few works have been done to contrast and unify the two algorithm categories. In this work, we introduce a matrix trace oriented optimization framework to provide a unifying view for both feature extraction and selection algorithms. We show that the unified view of DR...
In recent years, BitTorrent file distribution network has been more and more widely used for media file distribution. Its build-in resource scheduling policies (local rare first, tit-for-tat, etc.) work well in file distribution in single swarm environments. However, the resource scheduling policy is missing in multiple swarms environments and the resource utilization has not been optimized. In this...
Dimension reduction for large-scale text data is attracting much attention lately due to the rapid growth of World Wide Web. We can consider dimension reduction algorithms in two categories: feature extraction and feature selection. An important problem remains: it has been difficult to integrate these two algorithm categories into a single framework, making it difficult to reap the benefit of both...
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