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Autonomous underwater vehicles (AUVs) work in complex marine environments, and sensors play an important role in AUV systems. Therefore, research on sensor failure diagnosis technology is important for improving the reliability of AUV systems. In this paper, a new method combining phase space reconstruction and extreme learning machine (ELM) is proposed. This method is applied to predict sensor output...
Aiming at the main problems of low loading rate of vehicles, poor arrangement efficiency of routes, high costs for distribution and collecting the parts without the time window provided by a certain vendor in the milk-run process of enterprise operation, a new mathematical model called Time Window Priority Model (TWPM) is established based on the concept of the milk run system in order to solve vehicle...
To achieve the analysis of characteristic and forecasting of the mobile communication traffic, a mobile communication traffic modeling and forecasting method by Least Squares Support Vector Machine(LS-SVM) is proposed. With this method, an on-line forecasting scheme is designed to realize short-time forecasting of the mobile communication traffic. The traffic data is provided by China Mobile Communications...
Traffic forecasting is an important task which is required by overload warning and capacity planning for mobile networks. Based on analysis of real data collected by China Mobile Communications Corporation (CMCC) Heilongjiang Co. Ltd, this paper proposes to use the multiplicative seasonal ARIMA models for mobile communication traffic forecasting. Experiments and test results show that the whole solution...
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