Computational Intelligence

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We propose a particle filter-based learning method, PF-LR, for learning logistic regression models from evolving data streams. The method inherently handles concept drifts in a data stream and is able to learn an ï źensemble of logistic regression ...

This article proposes a framework for community discovery in temporal multiplex networks by extending the evolutionary clustering approach to encompass both time and multiple dimensions. In this extended framework, the problem of finding community ...

Spider monkey optimization SMO algorithm, which simulates the food searching behavior of a swarm of spider monkeys, is a new addition to the class of swarm intelligent techniques for solving unconstrained optimization problems. The purpose of this ...

The application of machine learning techniques to forecast financial time series is not a recent development, yet it continues to attract considerable attention because of the difficulty of the problem that is compounded by the nonlinear and ...

To meet the requirements of modern radar maneuvering target tracking system and remedy the defects of interacting multiple model based on particle filter, noninteracting multiple model NIMM and enhanced particle swarm optimized particle filter EPSO-PF ...

One of the most critical issues that developers face in developing automatic systems for electronic markets is that of endowing the agents with appropriate trading strategies. In this article, we examine the problem in the foreign exchange FX market, ...

Community detection is an important methodology for understanding the intrinsic structure and function of complex networks. Because overlapping community is one of the characteristics of real-world networks and should be considered for community ...