With the fast development of Internet and its data scale, B2B (Business to Business), whose speed and high availability advantage is based on Internet, is eroding more and more market share of traditional business. In...
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To enhance classification performance by making use of easily available unlabelled data to overcome the scarcity of labelled data, this paper proposes an Embedded Co-Adaboost algorithm that integrates multi-view learn...
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To enhance classification performance by making use of easily available unlabelled data to overcome the scarcity of labelled data, this paper proposes an Embedded Co-Adaboost algorithm that integrates multi-view learning into the Adaboost learning framework and at the same time leverages the advantages of Co-training algorithm for performance enhancement. Experimental results demonstrate the effectiveness of the proposed algorithm in terms of the convergence rate, the accuracy, and the steady performance as compared to the original AdaBoost algorithm, without relying on redundant and sufficient feature sets. As a algorithm application in software engineering, the Embedded Co-AdaBoost has been applied to the classification of software document relations to improve the quality of the architecture design documents and the reusability of design knowledge.
With the fast development of Internet and data volume increase in Internet, Internet is playing more important role in information spreading in recent years. It is reported that social network is a typical complex net...
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The paper discusses two important classification techniques, Fisher's linear discriminated analysis (FLDA) and Support Vector Machine (SVM). First, we propose a theoretical discussion, and then implement FLDA and ...
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The paper discusses two important classification techniques, Fisher's linear discriminated analysis (FLDA) and Support Vector Machine (SVM). First, we propose a theoretical discussion, and then implement FLDA and SVM on several datasets of two classes and multiclass, a comparative experimental analysis among these two techniques aims at exploring and assessing the performance of FLDA and SVM classifiers. To sustain such analysis, the two classification techniques are compared with different training data sets and testing data sets. Different performance indicators have been used to support our experimental studies in a detailed and accurate way such as the classification accuracy. The results obtained on different datasets conclude that FLDA and SVM are valid and effective approaches for pattern classification and conclude their different performance and problems with different size datasets. Meanwhile, the paper employs a non-traditional method to get the training and testing data set, and concludes detailed pros and cons from the experiment results.
To further enhance emergency management skills of an organisation's emergency response personnel, emergency response training, especially 3D emergency drill, is currently becoming more and more important in the pe...
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ISBN:
(纸本)9781467313971
To further enhance emergency management skills of an organisation's emergency response personnel, emergency response training, especially 3D emergency drill, is currently becoming more and more important in the petrochemical sector. So, a novel 3D emergency drills system is designed and developed based on ACP approach, which can be used for mocking emergency response plan drills and evaluating the plan. A case study reveals that the performance of the system is good and the system can meet the needs of emergency response training and optimizing emergency response plan in petrochemical plants.
The present work focuses on the node deployment algorithm of Wireless Sensor Networks. The Central Voronoi Tessellation algorithm is employed to optimize the node position. The energy consumption of the whole sensor n...
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Fault diagnosis based on the wavelet packet decomposition, one-against-one support vector machine (SVM) and genetic algorithm (GA) is proposed in order to realize the real-time sensor fault diagnosis accurately. The i...
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In order to solve the challenging problem of diagnosis for sensor bias and drift faults, a method of sensor fault diagnosis based on the least squares support vector machine (LS-SVM) online prediction is proposed. In ...
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When Multi-DSP parallel architecture transfers to distributed memory way from shared memory way, its parallelism with fine-grained become weak, and it's difficult to offer SIFT's complex computing and satisfy ...
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Problems of uncertain chaotic systems with fast terminal sliding mode control are discoursed. Aim at the uncertainty parameters of chaotic systems, proposed a fast terminal sliding mode control method, and the corresp...
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ISBN:
(纸本)9781467325813
Problems of uncertain chaotic systems with fast terminal sliding mode control are discoursed. Aim at the uncertainty parameters of chaotic systems, proposed a fast terminal sliding mode control method, and the corresponding sliding surface and controller are designed, which make the state variables of the system fast convergence to the equilibrium point in the limited time. And the examples are given to verify the feasibility of the system.
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