Papers are being solicited for a special track on Neural Networks and Data Mining at the 37th
International FLAIRS Conference. This special track will be devoted to
neural networks and data mining with the aim of presenting new and
important contributions in these areas. Papers and contributions are
encouraged for any work related to neural networks, data mining, or the
intersection thereof.
Topics of interest may include (but are not limited to):
Applications such as Pattern Recognition, Control and Process Monitoring, Biomedical Applications, Robotics, Text Mining, Diagnostic Problems, Power Systems, Signal Processing; Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cybersecurity, remote sensing, earth sciences, bioinformatics, and astronomy.
Neural networks such as new developments in Back Propagation, RBF, SVM, Deep Learning, Ensemble Methods, Kernel Approaches; Hybrid approaches such as Neural Networks/Genetic Algorithms, Causal Nets trained with Backpropagation, Neural Network/Fuzzy Logic and Acceleration of neural network models via software or hardware.
Other modeling algorithms such as hidden Markov models, decision trees, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches; graph modeling, pattern discovery, and anomaly detection; feature extraction and selection; post-processing techniques such as visualization, summarization, or trending; preprocessing and data reduction;and knowledge engineering or warehousing.
Topics of interest may include (but are not limited to):
Applications such as Pattern Recognition, Control and Process Monitoring, Biomedical Applications, Robotics, Text Mining, Diagnostic Problems, Power Systems, Signal Processing; Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cybersecurity, remote sensing, earth sciences, bioinformatics, and astronomy.
Neural networks such as new developments in Back Propagation, RBF, SVM, Deep Learning, Ensemble Methods, Kernel Approaches; Hybrid approaches such as Neural Networks/Genetic Algorithms, Causal Nets trained with Backpropagation, Neural Network/Fuzzy Logic and Acceleration of neural network models via software or hardware.
Other modeling algorithms such as hidden Markov models, decision trees, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches; graph modeling, pattern discovery, and anomaly detection; feature extraction and selection; post-processing techniques such as visualization, summarization, or trending; preprocessing and data reduction;and knowledge engineering or warehousing.