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The modulation recognition technology of communication signals has been an important theme of wireless communication. Based on the parameters abstraction of time domain statistical feature and fractal feature, the feature vector samples is formed. The artificial neural network is the research hot spots of pattern recognition. An artificial neural network is proposed for an automatic recognition of...
In the area of artificial neural networks, the Back Propagation (BP) learning algorithm has proved to be efficient in many engineering applications especially in pattern recognition, signal processing and system control. Although the BP learning has been a significant research area of neural network, it has also been known as an algorithm with a poor convergence rate. Many attempts have been made...
Due to the increased competition in the telecommunications, customer relation and churn management is one of the most crucial aspects for companies in this sector. Over the last decades, researchers have proposed many approaches to detect and model historical events of churn. Traditional approaches, like neural networks, aim to identify behavioral pattern related to the customers. This kind of supervised...
Accurate demand forecasting is one of the most crucial issues in inventory management of spare parts in process industries. The problem of modeling future consumption becomes especially difficult for lumpy patterns, which characterized by intervals in which there is no demand and, periods with actual demand occurrences with large variation in demand levels. However, many of these methods may perform...
The main activity carried out by the geophysicist when interpreting seismic data, in terms of both importance and time spent is tracking (or picking) seismic events. In practice, this activity turns out to be rather challenging, particularly when the targeted event is interrupted by discontinuities such as geological faults or exhibits lateral changes in seismic character. In recent years, several...
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