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• Classification and Analysis Topologies Known Artificial Neurons and Neural Networks.- Classification and Analysis of Multicriteria Optimization Methods.- Formation of Hybrid Artificial Neural Networks Topologies.- Development of Hybrid Neural Networks.- Intelligence Methods of Forecasting.- Intelligent System of Thyroid Pathology Diagnostics.- Intelligent Automated Road Management Systems.- Fire Surveillance Information Systems.
• (source: Nielsen Book Data)

This book is intended for specialists as well as students and graduate students in the field of artificial intelligence, robotics and information technology. It is will also appeal to a wide range of readers interested in expanding the functionality of artificial intelligence systems. One of the pressing problems of modern artificial intelligence systems is the development of integrated hybrid systems based on deep learning. Unfortunately, there is currently no universal methodology for developing topologies of hybrid neural networks (HNN) using deep learning. The development of such systems calls for the expansion of the use of neural networks (NS) for solving recognition, classification and optimization problems. As such, it is necessary to create a unified methodology for constructing HNN with a selection of models of artificial neurons that make up HNN, gradually increasing the complexity of their structure using hybrid learning algorithms. .
(source: Nielsen Book Data)

• Cluster Analysis in Big Data Mining.- Deep Neural Networks and Hybrid GMDH
• Neuro-fuzzy Networks in Big Data Analysis.- Pattern Recognition in Big Data Analysis.- Intellectual analysis of systemic world conflicts and global forecast for the 21st century.

The book is devoted to the analysis of big data in order to extract from these data hidden patterns necessary for making decisions about the rational behavior of complex systems with the different nature that generate this data. To solve these problems, a group of new methods and tools is used, based on the self-organization of computational processes, the use of crisp and fuzzy cluster analysis methods, hybrid neural-fuzzy networks, and others. The book solves various practical problems. In particular, for the tasks of 3D image recognition and automatic speech recognition large-scale neural networks with applications for Deep Learning systems were used. Application of hybrid neuro-fuzzy networks for analyzing stock markets was presented. The analysis of big historical, economic and physical data revealed the hidden Fibonacci pattern about the course of systemic world conflicts and their connection with the Kondratieff big economic cycles and the Schwabe-Wolf solar activity cycles. The book is useful for system analysts and practitioners working with complex systems in various spheres of human activity.

• Introduction: Special Classes of Extended Phase Spaces of Distributions.- Qualitative Methods for Classes of Nonlinear Systems: Constructive Existence Results.- Regularity of Solutions for Nonlinear Systems.- Uniform Global Attractors for Non-Autonomous Dissipative Dynamical Systems.- Uniform Trajectory Attractors for Non-autonomous Nonlinear Systems.- Indirect Lyapunov Method for Autonomous Dynamical Systems.
• (source: Nielsen Book Data)

Here, the authors present modern methods of analysis for nonlinear systems which may occur in fields such as physics, chemistry, biology, or economics. They concentrate on the following topics, specific for such systems:(a) constructive existence results and regularity theorems for all weak solutions; (b) convergence results for solutions and their approximations; (c) uniform global behavior of solutions in time; and(d) pointwise behavior of solutions for autonomous problems with possible gaps by the phase variables. The general methodology for the investigation of dissipative dynamical systems with several applications including nonlinear parabolic equations of divergent form, nonlinear stochastic equations of parabolic type, unilateral problems, nonlinear PDEs on Riemannian manifolds with or without boundary, contact problems as well as particular examples is established. As such, the book is addressed to a wide circle of mathematical, mechanical and engineering readers.
(source: Nielsen Book Data)

• Neural Networks
• . Neural Networks with Feedback and Self-organization Introduction
• Fuzzy Inference Systems and Fuzzy Neural Networks
• Application of Fuzzy Logic Systems and Fuzzy Neural Networks in Forecasting Problems in Macroeconomics and Finance
• Fuzzy Neural Networks in Classification Problems
• Inductive Modeling Method (gmdh) in Problems of Intellectual Data Analysis and Forecasting
• The Cluster Analysis in Intellectual Systems
• Genetic Algorithms and Evolutionary Programing
• Problem of Fuzzy Portfolio optimization Under Uncertainty And Its Solution With Application of Computational Intelligence Methods.

This monograph is dedicated to the systematic presentation of main trends, technologies and methods of computational intelligence (CI). The book pays big attention to novel important CI technology- fuzzy logic (FL) systems and fuzzy neural networks (FNN). Different FNN including new class of FNN- cascade neo-fuzzy neural networks are considered and their training algorithms are described and analyzed. The applications of FNN to the forecast in macroeconomics and at stock markets are examined. The book presents the problem of portfolio optimization under uncertainty, the novel theory of fuzzy portfolio optimization free of drawbacks of classical model of Markovitz as well as an application for portfolios optimization at Ukrainian, Russian and American stock exchanges. The book also presents the problem of corporations bankruptcy risk forecasting under incomplete and fuzzy information, as well as new methods based on fuzzy sets theory and fuzzy neural networks and results of their application for bankruptcy risk forecasting are presented and compared with Altman method. This monograph also focuses on an inductive modeling method of self-organization - the so-called Group Method of Data Handling (GMDH) which enables to construct the structure of forecasting models almost automatically. The results of experimental investigations of GMDH for forecasting at stock exchanges are presented. The final chapters are devoted to theory and applications of evolutionary modeling (EM) and genetic algorithms. The distinguishing feature of this monograph is a great number of practical examples of CI technologies and methods application for solution of real problems in technology, economy and financial sphere, in particular forecasting, classification, pattern recognition, portfolio optimization, bankruptcy risk prediction under uncertainty which were developed by authors and published in this book for the first time. All CI methods and algorithms are presented from the general system approach and analysis of their properties, advantages and drawbacks that enables practitioners to choose the most adequate method for their own problems solution. .

• I. Operator inclusions and variation inequalities for earth data processing
• II. Differential-operator inclusions and evolution variation inequalities for earth data processing.

Here, the authors present modern mathematical methods to solve problems of differential-operator inclusions and evolution variation inequalities which may occur in fields such as geophysics, aerohydrodynamics, or fluid dynamics. For the first time, they describe the detailed generalization of various approaches to the analysis of fundamentally nonlinear models and provide a toolbox of mathematical equations. These new mathematical methods can be applied to a broad spectrum of problems. Examples of these are phase changes, diffusion of electromagnetic, acoustic, vibro-, hydro- and seismoacoustic waves, or quantum mechanical effects. This is the first of two volumes dealing with the subject.

• Auxiliary Statements
• Differential-Operator Inclusions with W-Lambda-pseudomonotone Maps.-Evolution Variation Inequalities
• Vortical Flow Pattern Past a Square Prism: Numerical Model and Control Algorithms.

Here, the authors present modern mathematical methods to solve problems of differential-operator inclusions and evolution variation inequalities which may occur in fields such as geophysics, aerohydrodynamics, or fluid dynamics. For the first time, they describe the detailed generalization of various approaches to the analysis of fundamentally nonlinear models and provide a toolbox of mathematical equations. These new mathematical methods can be applied to a broad spectrum of problems. Examples of these are phase changes, diffusion of electromagnetic, acoustic, vibro-, hydro- and seismoacoustic waves, or quantum mechanical effects. This is the second of two volumes dealing with the subject.

• The subject domain of system analysis.- Basic notions of system analysis.- Disclosing uncertainties in system analysis problems.- Disclosing uncertainties in problems of interaction and counteraction of coalitions.- Information analysis of system problems.- Structural-functional analysis of complex hierarchical systems.- Problems and methods of system analysis of multifactor risks.- System control of complex objects.- Foresight system methodology.-.
• (source: Nielsen Book Data)

This book offers the foundations of system analysis as an applied scientific methodology assigned for the investigation of complex and highly interdisciplinary problems. It presents the basic definitions and the methodological and theoretical basis of formalization and solution processes in various subject domains. It describes in detail the methods of formalizing the system tasks and reducing them to a solvable form under real-world conditions.
(source: Nielsen Book Data)

• The subject domain of system analysis.- Basic notions of system analysis.- Disclosing uncertainties in system analysis problems.- Disclosing uncertainties in problems of interaction and counteraction of coalitions.- Information analysis of system problems.- Structural-functional analysis of complex hierarchical systems.- Problems and methods of system analysis of multifactor risks.- System control of complex objects.- Foresight system methodology.-.
• (source: Nielsen Book Data)

This book offers the foundations of system analysis as an applied scientific methodology assigned for the investigation of complex and highly interdisciplinary problems. It presents the basic definitions and the methodological and theoretical basis of formalization and solution processes in various subject domains. It describes in detail the methods of formalizing the system tasks and reducing them to a solvable form under real-world conditions.
(source: Nielsen Book Data)

• Part 1. Introduction / Vitamin D Deficiency: Historical Perspectives / Kumaravel Rajakumar and Michael F. Holick
• Perspective: Evolution of Human Skin Color: How Low Levels of Vitamin D Drove Natural Selection / Scott T. Weiss
• Part 2. Vitamin D Mechanisms of Relevance to Lung Diseases / Vitamin D and Lung Development in Early Life / Virender K. Rehan and John S. Torday
• Vitamin D and the Innate Immune Response / Aria Vazirnia and Philip T. Liu
• Vitamin D and Regulatory T Cells / Zoë Urry, Sarah Dimeloe and Catherine M. Hawrylowicz
• Dendritic Cell Modulation by the Vitamin D System / Luciano Adorini, Gilles Laverny and Giuseppe Penna
• Vitamin D Modulates Airway Smooth Muscle Function / Audreesh Banerjee and Reynold A. Panettieri Jr.
• Vitamin D: Genetics and Genomic Effects / Kelan G. Tantisira
• Part 3. Disease Associations / Acute Respiratory Infections / Jonathan M. Mansbach and Carlos A. Camargo Jr.
• The Role of Vitamin D in the Development, Exacerbation, and Severity of Asthma and Allergic Diseases / Augusto A. Litonjua
• Vitamin D and Chronic Obstructive Pulmonary Disease / Wim Janssens, An Lehouck, Marc Decramer and Ghislaine Gayan-Ramirez
• Cystic Fibrosis / Helen M. Buntain and Anne B. Chang
• Tuberculosis / Adrian R. Martineau
• Lung Cancer / David C. Christiani and C. Matthew Kinsey.

In this sequel to two earlier volumes, the authors now focus on the long-time behavior of evolution inclusions, based on the theory of extremal solutions to differential-operator problems. This approach is used to solve problems in climate research, geophysics, aerohydrodynamics, chemical kinetics or fluid dynamics. As in the previous volumes, the authors present a toolbox of mathematical equations. The book is based on seminars and lecture courses on multi-valued and non-linear analysis and their geophysical application.
(source: Nielsen Book Data)