Books in Mathematics

11-20 of 2729 results in All results

Decision Making Models

1st Edition
August 1, 2024
Tofigh Allahviranloo + 2 more
English
Paperback
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eBook
9 7 8 - 0 - 4 4 3 - 1 6 1 4 8 - 3

Decision Making Models: A Perspective of Fuzzy Logic and Machine Learning presents the latest developments in the field of uncertain mathematics and decision science. The book aims to deliver a systematic exposure to soft computing techniques in fuzzy mathematics as well as artificial intelligence in the context of real-life problems and is designed to address recent techniques to solving uncertain problems encountered specifically in decision sciences. Researchers, professors, software engineers, and graduate students working in the fields of applied mathematics, software engineering, and artificial intelligence will find this book useful to acquire a solid foundation in fuzzy logic and fuzzy systems.Other areas of note include optimization problems and artificial intelligence practices, as well as how to analyze IoT solutions with applications and develop decision-making mechanisms realized under uncertainty.

The Role of Blockchain in Disaster Management

1st Edition
July 1, 2024
Ayan Kumar Das + 3 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 1 3 4 7 2 - 2
eBook
9 7 8 - 0 - 4 4 3 - 1 3 4 7 3 - 9

The Role of Blockchain in Disaster Management explores the architecture and implementation of existing blockchain-based IoT frameworks for the detection and prevention of disasters, along with the management of relative supply chains to protect against mismanagement of essential materials. The distributed nature of Blockchain helps to protect data from internal or external attacks, especially in disaster areas or times of crisis when database systems become overloaded and vulnerable to unauthorized access, manipulation, and disruption of critical services. This book can be used as a reference by graduate students, researchers, professors, and professionals in computer science, software design, and disaster management.

Information Modeling and Relational Databases

3rd Edition
July 1, 2024
Terry Halpin + 1 more
English
Hardback
9 7 8 - 0 - 4 4 3 - 2 3 7 9 0 - 4
eBook
9 7 8 - 0 - 4 4 3 - 2 3 7 9 1 - 1

Information Modeling and Relational Databases, Third Edition, provides thorough coverage of information modeling approaches, including object-role modeling (ORM), entity-relationship (ER) modeling, and the unified modeling language (UML). It shows how to map models developed with those approaches to a variety of relational and nonrelational database systems, including document databases, column-oriented databases, graph databases, and deductive databases. Process and state modeling, ontological modeling, and metamodeling are also covered. For this new edition, the coverage of ORM, ER, UML, SQL, OWL, and BPMN has been thoroughly updated to include their latest versions. A significant amount of new material has been added. Various data file formats such as CSV, XML, JSON, YAML, and some other markup languages are now covered, and a more thorough treatment is provided for nonrelational databases, especially NoSQL. One of the major features of the book is its large number of exercises, which have been thoroughly class-tested. This book is intended for anyone with a stake in the accuracy and efficacy of databases such as systems analysts, information modelers, database designers and administrators, and programmers.

An Introduction to Probability and Statistical Inference

3rd Edition
June 1, 2024
George G. Roussas
English
Paperback
9 7 8 - 0 - 4 4 3 - 1 8 7 2 0 - 9
eBook
9 7 8 - 0 - 4 4 3 - 1 8 7 2 1 - 6

An Introduction to Probability and Statistical Inference, Third Edition guides the reader through probability models and statistical methods to develop critical-thinking skills. Written by award-winning author George Roussas, this valuable text introduces a thinking process to help users obtain the best solution to a posed question or situation and provides a plethora of examples and exercises to illustrate applying statistical methods to different situations.

The Theory and Practice of Intelligent Algorithms

1st Edition
June 1, 2024
Han Huang + 1 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 2 1 7 5 8 - 6
eBook
9 7 8 - 0 - 4 4 3 - 2 1 7 5 9 - 3

The Theory and Practice of Intelligent Algorithms discusses the latest achievements of the computation time analysis theory and practical applications of intelligent algorithms. In five chapters, the book covers (1) New methods of intelligent algorithm computation time analysis; (2)Application of intelligent algorithms in computer vision; (3) Application of intelligent algorithms in logistics scheduling; (4) Application of intelligent algorithms in software testing; and (5) Application of intelligent algorithm in multi-objective optimization.The content of each chapter is supported by papers published in top journals. The book's authors introduce the work of each part, which mainly includes a brief introduction (mainly for readers to understand) and academic discussion (rigorous theoretical and experimental support), in a vivid and interesting way through excellent pictures and literary compositions. To help readers learn and make progress together, each part of this book provides relevant literature, code, experimental data, and so on.

API Design for C++

2nd Edition
June 1, 2024
Martin Reddy
English
Paperback
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eBook
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API Design for C++, Second Edition provides a comprehensive discussion of Application Programming Interface (API) development, from initial design through implementation, testing, documentation, release, versioning, maintenance, and deprecation. It is the only book that teaches the strategies of C++ API development, including interface design, versioning, scripting, and plug-in extensibility. Drawing from the author's experience on large scale, collaborative software projects, the text offers practical techniques of API design that produce robust code for the long-term. It presents patterns and practices that provide real value to individual developers as well as organizations.The Second Edition includes all new material fully updated for the latest versions of C++, including a new chapter on concurrency and multithreading, as well as a new chapter discussing how Objective C++ and C++ code can co-exist and how a C++ API can be accessed from Swift programs. In addition, it explores often overlooked issues, both technical and non-technical, contributing to successful design decisions that produce high quality, robust, and long-lived APIs. It focuses on various API styles and patterns that will allow you to produce elegant and durable libraries. A discussion on testing strategies concentrates on automated API testing techniques rather than attempting to include end-user application testing techniques such as GUI testing, system testing, or manual testing.

Advanced Calculus for Mathematical Modeling in Engineering and Physics

1st Edition
June 1, 2024
David Stapleton
English
Paperback
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eBook
9 7 8 - 0 - 4 4 3 - 2 2 2 8 8 - 7

Advanced Calculus for Mathematical Modeling in Engineering and Physics: With Discrete and Numerical Analogies introduces the principles and methods of advanced calculus for mathematical modeling through a balance of theory and application using a state space approach with elementary functional analysis. This framework facilitates a deeper understanding of the nature of mathematical models, and of the behavior of their solutions. The work provides a variety of advanced calculus models for mathematical, physical science, and engineering audiences, with discussions on how calculus-based models and their discrete analogies are generated. This valuable textbook offers scientific computations driven by Octave/MATLAB script.

Numerical Analysis meets Machine Learning

1st Edition
Volume 25
June 1, 2024
Siddhartha Mishra + 1 more
English
Hardback
9 7 8 - 0 - 4 4 3 - 2 3 9 8 4 - 7
eBook
9 7 8 - 0 - 4 4 3 - 2 3 9 8 5 - 4

Numerical Analysis Meets Machine Learning series, highlights new advances in the field, with this new volume presenting interesting chapters. Each chapter is written by an international board of authors.

Fractional Differential Equations

1st Edition
May 10, 2024
Praveen Agarwal + 2 more
English
Paperback
9 7 8 - 0 - 4 4 3 - 1 5 4 2 3 - 2
eBook
9 7 8 - 0 - 4 4 3 - 1 5 4 2 4 - 9

Fractional Differential Equations: Theoretical Aspects and Applications presents the latest mathematical and conceptual developments in the field of Fractional Calculus and explores the scope of applications in research science and computational modeling. The book delves into these methods and applied computational modelling techniques, including analysis of equations involving fractional derivatives, fractional derivatives and the wave equation, analysis of FDE on groups, direct and inverse problems, functional inequalities, and computational methods for FDEs in physics and engineering. Other modeling techniques and applications explored include general fractional derivatives involving the special functions in analysis and fractional derivatives with respect to other functions. Fractional Calculus, the field of mathematics dealing with operators of differentiation and integration of arbitrary real or even complex order, extends many of the modelling capabilities of conventional calculus and integer-order differential equations and finds its application in various scientific areas, such as physics, mechanics, engineering, economics, finance, biology, and chemistry, among others.

Bio-Inspired Strategies for Modeling and Detection in Diabetes Mellitus Treatment

1st Edition
April 18, 2024
Alma Y Alanis + 3 more
English
Paperback
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eBook
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Bio-Inspired Strategies for Modeling and Detection in Diabetes Mellitus Treatment focuses on bioinspired techniques such as modeling to generate control algorithms for the treatment of diabetes mellitus. The book addresses the identification of diabetes mellitus using a high-order recurrent neural network trained by an extended Kalman filter. The authors also describe the use of metaheuristic algorithms for the parametric identification of compartmental models of diabetes mellitus widely used in research works such as the Sorensen model and the Dallaman model. In addition, the book addresses the modeling of time series for the prediction of risk scenarios such as hyperglycaemia and hypoglycaemia using deep neural networks. The detection of diabetes mellitus in the early stages or when current diagnostic techniques cannot detect glucose intolerance or prediabetes is proposed, carried out by means of deep neural networks present in the literature. Readers will find leading-edge research in diabetes identification based on discrete high-order neural networks trained with an extended Kalman filter; parametric identification of compartmental models used to describe diabetes mellitus; modeling of data obtained by continuous glucose-monitoring sensors for the prediction of risk scenarios such as hyperglycaemia and hypoglycaemia; and screening for glucose intolerance using glucose-tolerance test data and deep neural networks. Application of the proposed approaches is illustrated via simulation and real-time implementations for modeling, prediction, and classification.