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UAVs (Unmanned Aerial Vehicles) have been widely used in power line inspections, but low autonomous cruise capacity of UAVs requires strict condition for operators and site while landing during UAV power line inspections. This paper presents an autonomous landing control technique for UAVs when charging at the electric towers based on vision positioning method. The proposed system consists of three...
This paper introduces a new method to solve the cross-domain recognition problem. Different from the traditional domain adaption methods which rely on a global domain shift for all classes between the source and target domains, the proposed method is more flexible to capture individual class variations across domains. By adopting a natural and widely used assumption that the data samples from the...
Although a number of features derived from linear speech production theory have been investigated as speech emotion indicators, the recognition accuracy still stays unsatisfactory for realistic applications. In this paper, Teager Mel, a novel speech emotion feature is proposed based on Teager Energy Operator (TEO) and the Mel perception characteristics. Due to such advantages as nonlinear and simple,...
This paper presents a new power quality detection method based on the improved HHT in microgrid. Hilbert-Huang Transform (HHT) can distill these disturbing signals automatically and time-frequency spectrum can be obtained. However, in the application of this method there are serious end effects that mixed mode phenomenon will appear, affecting the detecting results. In order to suppress the end effects,...
In this paper we propose a weighted version of recently developed least squares twin support vector machine (LSTSVM) for pattern classification, in which different weights are put on the error variables in order to eliminate the impact of noise data and obtain the robust estimation. Here, we offer the formulations of the proposed weighted LSTSVM (WLSTSVM) in both linear and nonlinear cases. Comparative...
Recently, LSTSVM as a new binary SVM classifier based on nonparallel twin hyperplanes has shown a good classification performance, but the research on multi-class classification has still rarely been reported. In this paper, a multi-class LSTSVM classifier based on optimal directed acyclic graph is proposed. The idea of kernel parameter choice is used to realize the class separability criterion, an...
Information on the vehicular traffic density in an intelligent transport system (ITS) is presently obtained mainly through loop detectors (LD), traffic radars and surveillance cameras. However, the difficulties and cost of installing loop detectors and traffic radars tend to be significant. Currently, a more advanced method of circumventing this is to develop a sort of virtual loop detector (VLD)...
In order to identify the inverse model for nonlinear dynamic systems, a multiple support vector machines (MSVM) based method was presented. According to their differential orders for the dynamic system, the input and output variables were allocated into multiple calculational subspaces. Taking advantage of its nonlinear regression performance, each subspace was represented by the least squares support...
Training a support vector machine (SVM) on a large-scale sample set is a challenging problem. This paper proposes a sample reduction strategy to pretreat training samples which is realized by a two step procedure: instance reduction and attribute reduction, and the classification model of the SVM is also offered. The experimental results show that the proposed reduction algorithm can effectively remove...
Based on multi-spectral digital image texture feature, a new method for discriminating tea categories was put forward. The images which have three waveband images (Red, Green, NIR) were recorded by multi-spectral digital imager (MS3100). Eight filters were designed based on discrete cosine transform (DCT), and the NIR image was processed by the 8 filters, then the Standard deviation (Sd) of original...
Studying the molecular basis of syndrome in traditional Chinese medicine (TCM) is a research hotspot and a challenge for medicine society. In this paper, we combine clinical epidemiology, proteome technique and data mining research to investigate the molecular basis of syndrome. We do a clinical epidemiology survey of coronary heart disease to collect case patients and control patients. We also analysis...
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