Computational Intelligence and Predictive Analysis for Medical Science,
Автор: Helms, Volkhard Название: Principles of Computational Cell Biology ISBN: 3527333584 ISBN-13(EAN): 9783527333585 Издательство: Wiley Рейтинг: Цена: 11880.00 р. Наличие на складе: Поставка под заказ.
Описание: This successful text, now in its 2nd ed. , provides an ideal introduction into the possibilities of modeling on a cell biology level. It extends the strengths of the first edition even further while keeping faithful to the trusted hands-on concept and keeping math to the minimum.
Автор: Slawomir Wierzcho?; Mieczyslaw K?opotek Название: Modern Algorithms of Cluster Analysis ISBN: 3319887521 ISBN-13(EAN): 9783319887524 Издательство: Springer Рейтинг: Цена: 25155.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides the reader with a basic understanding of the formal concepts of the cluster, clustering, partition, cluster analysis etc. The book explains feature-based, graph-based and spectral clustering methods and discusses their formal similarities and differences. Understanding the related formal concepts is particularly vital in the epoch of Big Data; due to the volume and characteristics of the data, it is no longer feasible to predominantly rely on merely viewing the data when facing a clustering problem. Usually clustering involves choosing similar objects and grouping them together. To facilitate the choice of similarity measures for complex and big data, various measures of object similarity, based on quantitative (like numerical measurement results) and qualitative features (like text), as well as combinations of the two, are described, as well as graph-based similarity measures for (hyper) linked objects and measures for multilayered graphs. Numerous variants demonstrating how such similarity measures can be exploited when defining clustering cost functions are also presented. In addition, the book provides an overview of approaches to handling large collections of objects in a reasonable time. In particular, it addresses grid-based methods, sampling methods, parallelization via Map-Reduce, usage of tree-structures, random projections and various heuristic approaches, especially those used for community detection.
Автор: Adam E Gaw?da; Janusz Kacprzyk; Leszek Rutkowski; Название: Advances in Data Analysis with Computational Intelligence Methods ISBN: 3319885162 ISBN-13(EAN): 9783319885162 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Поставка под заказ.
Описание: This book is a tribute to Professor Jacek ?urada, who is best known for his contributions to computational intelligence and knowledge-based neurocomputing. It is dedicated to Professor Jacek ?urada, Full Professor at the Computational Intelligence Laboratory, Department of Electrical and Computer Engineering, J.B. Speed School of Engineering, University of Louisville, Kentucky, USA, as a token of appreciation for his scientific and scholarly achievements, and for his longstanding service to many communities, notably the computational intelligence community, in particular neural networks, machine learning, data analyses and data mining, but also the fuzzy logic and evolutionary computation communities, to name but a few.At the same time, the book recognizes and honors Professor ?urada’s dedication and service to many scientific, scholarly and professional societies, especially the IEEE (Institute of Electrical and Electronics Engineers), the world’s largest professional technical professional organization dedicated to advancing science and technology in a broad spectrum of areas and fields.The volume is divided into five major parts, the first of which addresses theoretic, algorithmic and implementation problems related to the intelligent use of data in the sense of how to derive practically useful information and knowledge from data. In turn, Part 2 is devoted to various aspects of neural networks and connectionist systems. Part 3 deals with essential tools and techniques for intelligent technologies in systems modeling and Part 4 focuses on intelligent technologies in decision-making, optimization and control, while Part 5 explores the applications of intelligent technologies.
Описание: A detailed description of up-to-date methods used for computer processing and interpretation of medical images is given. The scope of the book include images acquisition, storing with compression, processing, analysis, recognition and also its automatic understanding In introduction general overview of the computer vision methods designed for medical images is presented. Next sources of medical images are presented with their general characteristics. Both traditional (like X-ray) and very modern (like PET) sources of medical images are presented. The main emphasis is placed on such properties of medical images given by particular medical imaging methods which are important form the point of view of its computer processing, analysis and recognition. The consecutive parts of the book describe compression and processing methods, including many methods developed by authors especially for medical images. After parts describing analysis and recognition of medical images come most important part, in which the new method of automatic understanding of medical images is given. This new method of image interpretation, described in previous works of the same authors with applications for simple 2D images now is generalized for 3D images and for complex medical images with many objects observed and with complicated relations between these objects.
Описание: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.
Автор: Vladik Kreinovich; Songsak Sriboonchitta; Nopasit Название: Predictive Econometrics and Big Data ISBN: 3319890182 ISBN-13(EAN): 9783319890180 Издательство: Springer Рейтинг: Цена: 41925.00 р. Наличие на складе: Поставка под заказ.
Описание: This book presents recent research on predictive econometrics and big data. Gathering edited papers presented at the 11th International Conference of the Thailand Econometric Society (TES2018), held in Chiang Mai, Thailand, on January 10-12, 2018, its main focus is on predictive techniques – which directly aim at predicting economic phenomena; and big data techniques – which enable us to handle the enormous amounts of data generated by modern computers in a reasonable time. The book also discusses the applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that employs mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. It is therefore important to develop data processing techniques that explicitly focus on prediction. The more data we have, the better our predictions will be. As such, these techniques are essential to our ability to process huge amounts of available data.
Автор: D.P. Acharjya; Satchidananda Dehuri; Sugata Sanyal Название: Computational Intelligence for Big Data Analysis ISBN: 3319165976 ISBN-13(EAN): 9783319165974 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing.
Автор: Adam E Gaw?da; Janusz Kacprzyk; Leszek Rutkowski; Название: Advances in Data Analysis with Computational Intelligence Methods ISBN: 3319679457 ISBN-13(EAN): 9783319679457 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book is a tribute to Professor Jacek Żurada, who is best known for his contributions to computational intelligence and knowledge-based neurocomputing. It is dedicated to Professor Jacek Żurada, Full Professor at the Computational Intelligence Laboratory, Department of Electrical and Computer Engineering, J.B. Speed School of Engineering, University of Louisville, Kentucky, USA, as a token of appreciation for his scientific and scholarly achievements, and for his longstanding service to many communities, notably the computational intelligence community, in particular neural networks, machine learning, data analyses and data mining, but also the fuzzy logic and evolutionary computation communities, to name but a few.
At the same time, the book recognizes and honors Professor Żurada's dedication and service to many scientific, scholarly and professional societies, especially the IEEE (Institute of Electrical and Electronics Engineers), the world's largest professional technical professional organization dedicated to advancing science and technology in a broad spectrum of areas and fields.
The volume is divided into five major parts, the first of which addresses theoretic, algorithmic and implementation problems related to the intelligent use of data in the sense of how to derive practically useful information and knowledge from data. In turn, Part 2 is devoted to various aspects of neural networks and connectionist systems. Part 3 deals with essential tools and techniques for intelligent technologies in systems modeling and Part 4 focuses on intelligent technologies in decision-making, optimization and control, while Part 5 explores the applications of intelligent technologies.
Автор: Christian Moewes; Andreas N?rnberger Название: Computational Intelligence in Intelligent Data Analysis ISBN: 3642430856 ISBN-13(EAN): 9783642430855 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Complex systems and their phenomena are ubiquitous as they can befound in biology, finance, the humanities, management sciences,medicine, physics and similar fields.For many problems in these fields, there are no conventional ways tomathematically or analytically solve them completely at low cost.
Автор: D.P. Acharjya; Satchidananda Dehuri; Sugata Sanyal Название: Computational Intelligence for Big Data Analysis ISBN: 3319362003 ISBN-13(EAN): 9783319362007 Издательство: Springer Рейтинг: Цена: 14365.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing.
Fundamentals of Sentiment Analysis and Its Applications.- Fundamentals of Sentiment Analysis: Concepts and Methodology.- The Comprehension of Figurative Language: What is the Influence of Irony and Sarcasm on NLP Techniques?.- Probabilistic Approaches for Sentiment Analysis: Latent Dirichlet Allocation for Ontology Building and Sentiment Extraction.- Description Logic Class Expression Learning Applied to Sentiment Analysis.- Capturing Digest Emotions by Means of Fuzzy Linguistic Aggregation.- Hyperelastic-based Adaptive Dynamics Methodology in Knowledge Acquisition for Computational Intelligence on Ontology Engineering of Evolving Folksonomy Driven Environment.- Sentiment-Oriented Information Retrieval: Affective Analysis of Documents Based on the SenticNet Framework.- Interpretability of Computational Models for Sentiment Analysis.- Chinese Micro-blog Emotion Classification by Exploiting Linguistic Features and SVMperf.- Social Media and News Sentiment Analysis for Advanced Investment Strategies.- Context Aware Customer Experience Management: A Development Framework Based on Ontologies and Computational Intelligence.- An Overview of Sentiment Analysis in Social Media and Its Applications in Disaster Relief.- Big Data Sentiment Analysis for Brand Monitoring in Social Media Streams by Cloud Computing.- Neuro-Fuzzy Sentiment Analysis for Customer Review Rating Prediction.- OntoLSA: An Integrated Text Mining System for Ontology Learning and Sentiment Analysis.- Knowledge-based Tweet Classification for Disease Sentiment Monitoring.
Описание: Experimental data analysis is at the core of scientific inquiry, and computers have taken this function to a new level. This volume is an interactive guide to complex modern analytical processes from non-linear curve fitting to clustering and machine learning.
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