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Aiming at the problem of low accuracy in intrusion detection system, this paper established a genetic support vector machine (SVM) model according to the features of genetic algorithm and support vector machine algorithm. The model firstly optimizes the support vector parameters according to genetic algorithm, then we build the intrusion detection model with support vector machine optimized and use...
This paper presents an improved vision-based algorithm for detecting and recognizing vehicle logos in images captured by road surveillance cameras. Vehicle logo recognition is quite a challenging task considering the low resolution of the logos, the wide range of variability in illumination and the interference of the air-intake grille. However, our system, assessed on a set of 1386 vehicle images...
Based on principal component analysis (PCA) and support vector machine (SVM), a new method for the fault diagnosis of TE Process is proposed. The fault recognition based on kernel principal component analysis (KPCA) is analyzed and SVM is employed as a classifier for fault classification. To establish a more efficient SVM model, genetic algorithm (GA) is used to determine the optimal kernel parameter...
We present a method for action recognition that combines and thus shares the advantages of both local and global representation of the video sequence. The dense Harris corners are first extracted as the local interest points, which are then masked by the motion history image (MHI). Next, a set of rectangular filters with different orientations and rotation points are applied on these masked local...
In this paper, Takagi-Sugeno fuzzy classification system (T-S FCS) using particle swarm optimization (PSO) and support vector machine (SVM) for parameters optimization is proposed. The T-S FCS is constructed by fuzzy if-then rules whose consequents are linear state equations. The antecedents of T-S FCS are determined by the fuzzy membership of the input feature vectors. The prespecified values during...
This paper uses genetic algorithm to optimize the relevance vector machine algorithm to extract the characteristic vector of fault classification, and by contrasting with relevance vector machine, the support vector machine and BP neural network method, it is know that the relevance vector machine optimized by genetic algorithm (ga) can more accurately classify the fault type of conclusion.
Fish freshness is an important index of fishes and fish products which indicates their qualities. Rapid detection of fish freshness has very important guiding significance for processing, storage and marketing of fishes and fish products. Aiming at the disadvantages of fish freshness detection techniques at present, a rapid and nondestructive fish freshness detection method was proposed in this paper...
According to the nonlinear, non-stationary and modulated by high frequency characteristics of vibration signals of hoister, a method of multi-faults classification is studied based on Improved Local Mean Decomposition (LMD) and Multi-class Support Vector Machines (MSVM). Firstly, based on prolongation of SVR, the improved LMD algorithm is used to remove the end effects of LMD. The feature sets of...
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