Classification under Streaming Emerging New Classes: A Solution using Completely Random Trees

This paper investigates an important problem in stream mining, i.e., classification under streaming emerging new classes or SENC. The common approach is to treat it as a classification problem and solve it using either a supervised learner or a semi-supervised learner. We propose an alternative approach by using unsupervised learning as the basis to solve this problem. The SENC problem can be decomposed into three sub problems: detecting emerging new classes, classifying for known classes, and updating models to enable classification of instances of the new class and detection of more emerging new classes. The proposed method employs completely random trees which have been shown to work well in unsupervised learning and supervised learning independently in the literature. This is the first time, as far as we know, that completely random trees are used as a single common core to solve all three sub problems: unsupervised learning, supervised learning and model update in data streams. We show that the proposed unsupervised-learning-focused method often achieves significantly better outcomes than existing classification-focused methods

Research on the influence of virtual modeling and testing–based rubber track system on vibration performance of engineering vehicles

The rubbertrack system can be quickly swapped on the tyres, exerting a smaller ground pressure while generating a greater adhesion to solve the problem vehicles faced in traversing rough and difficult terrain. This paper will discuss the influence of rubber track system on the ride comfort of engineering vehicles with rigid suspension. First, a multi-body dynamic model of the rubber track system and a mathematical model of contact between the ground and the track are established, and then the macro commands are programmed to add many complex contact forces. Moreover, by using the method of physical prototype obstacle testing, the correctness of the simulation model is validated. The ride comfort of the engineering vehicle when equipped with rubber track system is explored by the method of the multi-body dynamics and real vehicle test. The research shows that a flexible roller wheel system can significantly improve the ride comfort of the engineering vehicle when compared to wheeled vehicles. When the vehicle speed is low, the weighted root-meansquare acceleration of the wheeled vehicle and tracked vehicle is almost the same. At the same time, it is verified that the ride comfort of the steelchain tracked vehicles is worse than that of rubber tracked vehicles, due to the polygon effect. Through the multi-body dynamics simulation of the virtual prototype, we can predict and evaluate the ride comfort of vehicles, saving the cost of testing and obtaining the actual experimental data, which has great significance for the research and development of vehicles