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Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems / Edition 1 – Paperback
Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems / Edition 1
Studies in Computational Intelligence: Observational Calculi and Association Rules (Paperback)
Observational calculi were introduced in the 1960’s as a tool of logic of discovery. Formulas of observational calculi correspond to assertions on analysed data. Truthfulness of suitable assertions can lead to acceptance of new scientific hypotheses. The general goal was to automate the process of discovery of scientific knowledge using mathematical logic and statistics. The GUHA method for producing true formulas of observational calculi relevant to the given problem of scientific discovery was developed. Theoretically interesting and practically important results on observational calculi were achieved. Special attention was paid to formulas – couples of Boolean attributes derived from columns of the analysed data matrix. Association rules introduced in the 1990’s can be seen as a special case of such formulas. New results on logical calculi and association rules were achieved. They can be seen as a logic of association rules. This can contribute to solving contemporary challenging problems of data mining research and practice. The book covers thoroughly the logic of association rules and puts it into the context of current research in data mining. Examples of applications of theoretical results to real problems are presented. New open problems and challenges are listed. Overall, the book is a valuable source of information for researchers as well as for teachers and students interested in data mining. • Author: Jan Rauch • ISBN:9783642445330 • Format:Paperback • Publication Date:2015-01-29
Studies in Computational Intelligence: Mining for Strategic Competitive Intelligence : Foundations and Applications (Series #406) (Hardcover)
This book provides an introduction to the use of automated methods for gathering competitive strategic intelligence. It examines the gathering of knowledge that appears of paramount importance to organizations. Introduction.- Research Foundations.- Competitive Intelligence Capturing Systems.- Research Topics and Applications.- Conclusion. • Author: Cai-Nicolas Ziegler • ISBN:9783642277139 • Forma
t:Hardcover • Publication Date:2012-03-14
Studies in Computational Intelligence: Granular Neural Networks, Pattern Recognition and Bioinformatics (Series #712) (Hardcover)
Introduction to Granular Computing, Pattern Recognition and Data Mining.- Classification using Fuzzy Rough Granular Neural Networks.- Clustering using Fuzzy Rough Granular Self-Organizing Map.- Fuzzy Rough Granular Neural Network and Unsupervised Feature Selection. • Author: Sankar K Pal,Shubhra S Ray,Avatharam Ganivada • ISBN:9783319571133 • Format:Hardcover • Publication Date:2017-06-02
Artificial Neural Networks in Pattern Recognition : 7th Iapr Tc3 Workshop, Annpr 2016, Ulm, Germany, September 28-30, 2016, Proceedings (Paperback)
Learning sequential data with the help of linear systems.- A spiking neural network for personalised modelling of Electrogastogrophy (EGG).- Improving generalization abilities of maximal average margin classifiers.- Finding small sets of random Fourier features for shift-invariant kernel approximation.- Incremental construction of low-dimensional data representations.- Soft-constrained nonparametric density estimation with artificial neural networks.- Density based clustering via dominant sets.- Co-training with credal models.- Interpretable classifiers in precision medicine: feature selection and multi-class categorization.- On the evaluation of tensor-based representations for optimum-pathforest classification.- On the harmony search using quaternions.- Learning parameters in deep belief networks through firefly algorithm.- Towards effective classification of imbalanced data with convolutional neural networks.- On CPU performance optimization of restricted Boltzmann machine and convolutional RBM.- Comparing incremental learning strategies for convolutional neural networks.- Approximation of graph edit distance by means of a utility matrix.- Time series classification in reservoir- and model-space: a comparison.- Objectness scoring and detection proposals in forward-Looking sonar images with convolutional neural networks.- Background categorization for automatic animal detection in aerial videos using neural networks.- Predictive segmentation using multichannel neural networks in Arabic OCR system.- Quad-tree based image segmentation and feature extraction to recognize online handwritten Bangla characters.- A hybrid recurrent neural network/dynamic probabilistic graphical model predictor of the disulfide bonding state of cysteines from the primary structure of proteins.- Using radial basis function neural networks for continuous anddiscrete pain estimation from bio-physiological signals.- Active learning for speech event detection in HCI.- Emotion recognition in speech with deep learning architectures.- On gestures and postural behavior as a modality in ensemble methods.- Machine learning driven heart rate detection with camera photoplethysmography in time domain. • ISBN:9783319461816 • Format:Paperback • Publication Date:2016-09-09
Pattern Recognition and Neural Networks (Paperback)
This 1996 book explains the statistical framework for pattern recognition and machine learning, now in paperback. Ripley brings together two crucial ideas in pattern recognition: statistical methods and machine learning via neural networks. He brings unifying principles to the fore, and reviews the state of the subject. Ripley also includes many examples to illustrate real problems in pattern recognition and how to overcome them. Pattern Recognition and Neural Networks (Paperback)
