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Power system is a nonlinear network with many stochastic disturbances. Recently, with large-scale renewable power integration such as wind power and solar energy, it has caused much more stochastic factors in the power system. The traditional deterministic linear analysis methods need to be improved. Therefore, it has important value to use nonlinear differential equations to analyze the stochastic...
Distributed Hash Tables (DHTs) have emerged as the most popular scheme in the P2P network, which have drastically changed the way we share resources and gather information. In order to solve the problem of search flexibility In DHT, an improved lookup and routing protocol based on Content Addressable Networks (CANs) is proposed, which not only preserves CANs' simplicity, but also achieves a resilient...
In a complex heterogeneous wireless sensor networks (HWSN), the individual sensor node is equipped with extremely different battery capacity and computational capability. Node failure is an inevitable phenomenon which leads to decreasing the lifetime and Qos of the networks. Topology control is an energy-efficient technique to prolong the network lifetime and maintain the network Qos. In this paper,...
A new along-track velocity estimation method is proposed for synthetic aperture radar (SAR) ground moving target in the complex image domain. For a target with relatively large along-track velocity, its complex response is a linear frequency-modulated (LFM) signal in the image domain. Its Doppler rate is mainly determined by the along-track velocity, while the effect of the cross-track velocity can...
Short-term load forecast plays a vital role in the electric power industry. In this paper, a deep belief network is proposed for short-term load forecasting. However, the Back-Propagation (BP) algorithm of deep belief network for fine tuning has some inherent drawbacks and limitations, such as slow convergence rate and easy to fall into local minimum. To overcome the drawbacks, several neural network...
This paper propose a mathematical formulation of energy management problem and its implementation in an energy management system (EMS) for isolated neighboring multi-microgrids. Using the model predictive control technique, the optimal operation of the microgrids is determined by utilizing an extended horizon of prediction and evaluation, which allows a proper scheduling of the energy storage units,...
Credit data, the data that describes the attributes of customer credit collected by enterprises or institutions, which contains a wealth of credit information, is the important basis of customer credit scoring. Using data mining technology to analyze the credit data and evaluate credit of customer has become a highly efficient method for customer credit estimation. Related research has become a hot...
Uplink power control (ULPC) plays an important role in LTE system. In this paper, a new ULPC approach based on Biogeography-based Optimization (BBO) is proposed. Only with broadcast parameters such as a and P0, through the BBO Optimization, the cells will be divided into many layers automatically, different compensation offset values allocated at the same time. With the constraint operator of BBO,...
Recently, we propose deep neural network based hidden Markov models (DNN-HMMs) for offline handwritten Chinese text recognition. In this study, we design a novel writer code based adaptation on top of the DNN-HMM to further improve the accuracy via a customized recognizer. The writer adaptation is implemented by incorporating the new layers with the original input or hidden layers of the writer-independent...
It has been widely recognized that relaying is an important method for increasing the reliability and spectral efficiency of communications systems, and it is thus helpful for improving the performance of vehicle-to-vehicle (V2V) communication systems. However, designing and evaluating V2V relay networks require understanding the effect of shadowing, as this critically impacts the performance of the...
Unmanned aerial vehicle (UAV) has been used by the electric utility in many situations such as the power transmission line inspection. When the UAV flying close to the high voltage (HV) power transmission line, there are risks of flashover through the UAV or corona discharge on the UAV because of the electric field disturbance caused by the UAV. To estimate the safe distance between the UAV and transmission...
Visible light communication (VLC) is an advanced and high-efficiency wireless communication technology. As one of the most important light sources in VLC, conventional white LED based on Y3Al5O12:Ce3+ (YAG:Ce) phosphor limits the system transmitting rate severely due to its narrow modulation bandwidth. Considering the short fluorescent lifetime of quantum dots (QDs), QD-LEDs with wide modulation bandwidth...
In this paper, we consider a single sensor classification problem, focusing on classifying the types of the moving vehicles. To improve the classification accuracy with low-time complexity in complex scenes, the acoustic sensor data sets were captured to measure the physical events and a novel hybrid dictionary learning method for vehicle classification is proposed. The efficient hybrid dictionary...
As product of the combination of Internet technology and sensor network, Internet of things (IoT) greatly facilitates the mutual interaction of the information world and physical world. Furthermore, with the rapid development of modern transportation systems, as a typical successful application of IoT in the real life, intelligent traffic system (ITS) has a great significance on management of the...
In recent years, sparse regression has drawn much attention in hyperspectral unmixing. The well known sparse unmixing via variable splitting augmented Lagrangian (SUnSAL) and sparse unmixing via variable splitting augmented Lagrangian and total variation (SUnSAl-TV) aim to find the sparsest abundance of every data vector individually. However, these methods ignore the global structure of all the vectors...
Deep belief networks (DBN) which is an important method in deep learning has a good learning ability to get the characteristics from data. By using DBN to learn the consistency of the innovation sequence in Kalman filtering (KF), the accuracy and robustness of KF can be improved. Through the simulation of the positioning system in Automated Guided Vehicle (AGV), the new algorithm that combines KF...
In view of solving multi-objective path planning in the static environment, there are some faults for ant colony optimization(ACO), such as the long computation and easy to fall into local optimum. To solve these problems, the ACO based on cat swarm optimization (CSO) algorithm searching model (CSOACO) is presented. In this algorithm, the introduction of CSO algorithm search pattern realizes the local...
Malware, a significant threat to maintain a healthy Android ecosystem, always receives considerable attentions. This paper proposes a new dynamic Android malware classification approach by constructing and analyzing the dynamic behavior dependency graphs together with both framework-level function call behaviors and their data dependencies. Features are extracted from behavior graphs of different...
Malware analysis technology is important for Android security. However, existing Android malware analysis approaches, both static approaches and dynamic approaches, have their own advantages and drawbacks. In this paper, by combining static and dynamic approaches, we propose the forced execution technique for Android apps to automatically extract their hidden information such as encoded URLs, promoting...
A dynamic block scale-invariant (DBSI) method for extracting salient feature key points that can be used to perform fast and accurate sparse optical flow computation is presented. With a more in-depth development and analysis of the Dynamic Block-Based feature selection and the Scale-space Extrema Detection stage, we propose a solution that correctly estimated the optical flow 2D motion vectors in...
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