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Books in Mathematics

The Mathematics collection presents a range of foundational and advanced research content across applied and discrete mathematics, including fields such as Computational Mathematics; Differential Equations; Linear Algebra; Modelling & Simulation; Numerical Analysis; Probability & Statistics.

11-20 of 2679 results in All results

Handbook of Statistical Analysis

  • 3rd Edition
  • September 16, 2024
  • Robert Nisbet + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 5 8 4 5 - 2
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 5 8 4 6 - 9
Handbook of Statistical Analysis: AI and ML Applications, third edition, is a comprehensive introduction to all stages of data analysis, data preparation, model building, and model evaluation. This valuable resource is useful to students and professionals across a variety of fields and settings: business analysts, scientists, engineers, and researchers in academia and industry. General descriptions of algorithms together with case studies help readers understand technical and business problems, weigh the strengths and weaknesses of modern data analysis algorithms, and employ the right analytical methods for practical application. This resource is an ideal guide for users who want to address massive and complex datasets with many standard analytical approaches and be able to evaluate analyses and solutions objectively. It includes clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques; offers accessible tutorials; and discusses their application to real-world problems.

Computer and Information Security Handbook

  • 4th Edition
  • September 1, 2024
  • John Vacca
  • English
  • Hardback
    9 7 8 - 0 - 4 4 3 - 1 3 2 2 3 - 0
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 3 2 2 4 - 7
Computer and Information Security Handbook, Fourth Edition offers deep coverage of an extremely wide range of issues in computer and cybersecurity theory, along with applications and best practices, offering the latest insights into established and emerging technologies and advancements. With new parts devoted to such current topics as Cyber Security for the Smart City and Smart Homes, Cyber Security of Connected and Automated Vehicles, and Future Cyber Security Trends and Directions, the book now has 115 chapters written by leading experts in their fields, as well as 8 updated appendices and an expanded glossary.Chapters new to this edition include such timely topics as Threat Landscape and Good Practices for Internet Infrastructure, Cyber Attacks Against the Grid Infrastructure, Threat Landscape and Good Practices for the Smart Grid Infrastructure, Energy Infrastructure Cyber Security, Smart Cities Cyber Security Concerns, Community Preparedness Action Groups for Smart City Cyber Security, Smart City Disaster Preparedness and Resilience, Cyber Security in Smart Homes, Threat Landscape and Good Practices for Smart Homes and Converged Media, Future Trends for Cyber Security for Smart Cities and Smart Homes, Cyber Attacks and Defenses on Intelligent Connected Vehicles, Cyber Security Issues in VANETs, Use of AI in Cyber Security, New Cyber Security Vulnerabilities and Trends Facing Aerospace and Defense Systems, and much more.

Statistical Analysis for Civil Engineers

  • 1st Edition
  • September 1, 2024
  • Hussam K. Risan + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 7 3 6 2 - 9
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 7 3 6 3 - 6
Statistical Analysis for Civil Engineers: Mathematical Theory and Applied Experiment Design is a well-researched and topically organized reference book that guides its readers, both in academia and industry, to recognize how to describe unpredictable events in a quantitative way and to learn how these events can be incorporated into practical engineering analysis that facilitates data-driven problem solving and optimization-based decision-making.Written by experts in the field with a proven track record as educators and practicing consultancy specialists, this book has been developed in such a manner that it advances understanding of the mathematical theory underlying analytical methodology gradually. It also supports practical application through relevant worked examples in a variety of civil engineering branches, notably structural, materials, transportation, and geotechnical engineering. Through all stages of data analysis, numerical modeling and simulation, and implementation, the volume emphasizes the need to change the current perception with respect to the use of modern statistical techniques in the scientific as well as practical spheres of civil engineering.

Probability Models

  • 1st Edition
  • Volume 51
  • September 1, 2024
  • Arni S.R. Srinivasa Rao + 2 more
  • English
  • Hardback
    9 7 8 - 0 - 4 4 3 - 2 9 3 2 8 - 3
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 9 3 2 9 - 0
Probability Models, Volume 51 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on Stein’s methods, Probabilities and thermodynamics third law, Random Matrix Theory, General tools for understanding fluctuations of random variables, An approximation scheme to compute the Fisher-Rao distance between multivariate normal distributions, Probability Models Applied to Reliability and Availability Engineering, Backward stochastic differential equation– Stochastic optimization theory and viscous solution of HJB equation, and much more.Additional chapters cover Probability Models in Machine Learning, The recursive stochastic algorithm, randomized urn models and response-adaptive randomization in clinical trials, Random matrix theory: local laws and applications, KOO methods and their high-dimensional consistencies in some multivariate models, Fourteen Lectures on Inference for Stochastic Processes, and A multivariate cumulative damage model and some applications.

Visualizing More Quaternions

  • 1st Edition
  • August 1, 2024
  • Andrew J. Hanson
  • English
  • Hardback
    9 7 8 - 0 - 3 2 3 - 9 9 2 0 2 - 2
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 9 3 9 0 - 6
Visualizing More Quaternions is a sequel to Dr. Andrew J. Hanson’s first book, Visualizing Quaternions, which appeared in 2006. This new volume develops and extends concepts that have attracted the author’s attention in the intervening 18 years, providing new insights into existing scholarship, and detailing results from Dr. Hanson’s own published and unpublished investigations relating to quaternion applications. Among the topics covered are the introduction of new approaches to depicting quaternions and their properties, applications of quaternion methods to cloud matching, including both orthographic and perspective projection problems, and orientation feature analysis for proteomics and bioinformatics. The quaternion adjugate variables are introduced to embody the nontrivial quaternion topology on the three-sphere and incorporate it into machine learning tasks. Other subjects include quaternion applications to a wide variety of problems in physics, including quantum computing, complexified quaternions in special relativity, and a detailed study of the Kleinian “ADE”discrete groups of the ordinary two-sphere. Quaternion geometry is also incorporated into the isometric embedding of the Eguchi–Hanson gravitational instanton corresponding to the k = 1 Kleinian cyclic group. Visualizing More Quaternions endeavors to explore novel ways of thinking about challenging problems that are relevant to a broad audience involved in a wide variety of scientific disciplines.

Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications

  • 1st Edition
  • August 1, 2024
  • Siddhartha Bhattacharyya + 3 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 5 5 3 3 - 8
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 5 5 3 2 - 1
Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications focuses on recent, up-to-date technologies, combining other intelligent tools with swarm intelligence techniques to yield robust and failsafe solutions to real world problems. This book aims to provide audiences with a platform to learn and gain insights into the latest developments in hybrid swarm intelligence. It will be useful to researchers, engineers, developers, practitioners, and graduate students working in the major and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing.With the advent of data-intensive applications, the elimination of redundancy in disseminated information has become a serious challenge for researchers who are on the lookout for evolving metaheuristic algorithms which can explore and exploit the information feature space to derive the optimal settings for specific applications. Swarm intelligence algorithms have developed as one of the most widely used metaheuristic techniques for addressing this challenge in an effective way. Inspired by the behavior of a swarm of bees, these swarm intelligence techniques emulate the corresponding natural instincts to derive optimal solutions for data-intensive applications.

Decision Making Models

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

Information Modeling and Relational Databases

  • 3rd Edition
  • July 22, 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.

Numerical Analysis meets Machine Learning

  • 1st Edition
  • Volume 25
  • July 19, 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.

Advanced Calculus for Mathematical Modeling in Engineering and Physics

  • 1st Edition
  • June 28, 2024
  • David Stapleton
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 2 2 8 9 - 4
  • 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.