The hydraulic system's reliability is a key factor to ensure the reliable operation of equipment and it is very important to evaluate reliability of hydraulic system. The paper describes a reliability prediction m...
详细信息
Object-level saliency detection is an important branch of visual saliency. Most previous methods are based on the contrast hypothesis which regards the regions presenting high contrast in a certain context as salient....
详细信息
In order to overcome the difficulty of constructing the multi-state system's reliability optimization model, and the shortage of premature convergence of PSO (Particle Swarm Optimization) algorithm, a new reliabil...
详细信息
Aiming at the absorption effect of fog suspended in the atmosphere on light, the paper established the removing-fog compensation adaptive model which can improve the atmospheric visibility and restore the normal work ...
详细信息
When wind farm accepts grid scheduling, target load needs to dispatch to each wind turbine to complete. In order to improve the power control capability of the wind farm in the case of random wind fluctuations, a wind...
详细信息
ISBN:
(纸本)9781849197588
When wind farm accepts grid scheduling, target load needs to dispatch to each wind turbine to complete. In order to improve the power control capability of the wind farm in the case of random wind fluctuations, a wind farm power control strategy, based on wind wheel rotation energy storage of variable speed wind turbine, is proposed. Firstly, a wind turbine energy storage assessment model is established, and an energy storage state evaluation method, which considers the balance of wind turbine rotational energy and regulating ability, is proposed. Based on this, a mathematical model of wind farm energy storage optimum is pretended, and a solving strategy based on genetic algorithm is designed, too. Finally, the platform for the implementation of the proposed control strategy is introduced. The control strategy proposed in this paper can effectively enhance the ability of the wind turbines' power control and reduce the impact of the uncertainty wind speed to the power response of the wind farm.
Object-level saliency detection is an important branch of visual saliency. In this paper, we propose a novel method which can conduct object-level saliency detection in both images and videos in a unified way. We empl...
详细信息
In this work, we present a new framework for large scale online kernel classification, making kernel methods efficient and scalable for large-scale online learning tasks. Unlike the regular budget kernel online learni...
详细信息
ISBN:
(纸本)9781577356332
In this work, we present a new framework for large scale online kernel classification, making kernel methods efficient and scalable for large-scale online learning tasks. Unlike the regular budget kernel online learning scheme that usually uses different strategies to bound the number of support vectors, our framework explores a functional approximation approach to approximating a kernel function/matrix in order to make the subsequent online learning task efficient and scalable. Specifically, we present two different online kernel machine learning algorithms: (i) the Fourier Online Gradient Descent (FOGD) algorithm that applies the random Fourier features for approximating kernel functions;and (ii) the Nyström Online Gradient Descent (NOGD) algorithm that applies the Nyström method to approximate large kernel matrices. We offer theoretical analysis of the proposed algorithms, and conduct experiments for large-scale online classification tasks with some data set of over 1 million instances. Our encouraging results validate the effectiveness and efficiency of the proposed algorithms, making them potentially more practical than the family of existing budget kernel online learning approaches.
Link duration determines the performance of many vehicular applications, especially for urban vehicular wireless communication networks. However, the theoretical analysis on link properties is always complicated, sinc...
详细信息
ISBN:
(纸本)9781450320733
Link duration determines the performance of many vehicular applications, especially for urban vehicular wireless communication networks. However, the theoretical analysis on link properties is always complicated, since parameters that should be considered include the inter-vehicle distance, the vehicle speed, the turning ratios in the intersection, the influence of traffic lights in the intersections, and the signal decay caused by the roadside buildings etc. To reduce the analytical complexity, most of the previous works proposed preliminary analysis on link duration property by considering some parameters. Even though some works considered all parameters, their assumptions on the parameters setting were somewhat ideal. For example, the events of meeting traffic lights for two consecutive vehicles in a communication route path were always assumed independent with each other, which is different from the actual situations. This paper proposes a discrete Markov process-based analytical model on link duration by considering a relatively complete set of parameters, including the influence of the inter-vehicle distance, vehicle speed, turning ratios in the intersection, traffic lights in the intersection, and the non-line-of-sight transmission for the intersection. Especially, the theoretical study on the link duration is based on a more realistic traffic lights scenario description model. Finally, simulations are carried to verify the accuracy of our analytical work.
In this paper, we present a scene text extraction approach which can realize text localization and segmentation simultaneously. Two popular paradigms (machine learning method and rule-based method) are combined to ach...
详细信息
In this paper, a discriminant manifold learning method based on Locally Linear Embedding (LLE), which is named Locally Linear Representation Fisher Criterion (LLRFC), is proposed for the classification of tumor gene e...
详细信息
暂无评论