Название: Inside AI: Over 150 billion purchases per year use this author's AI
Автор: Аkli Аdjаоutе
Издательство: Manning Publications
Год: 2024
Страниц: 216
Язык: английский
Формат: pdf (true)
Размер: 30.4 MB

Separate the AI facts from the AI fiction, and discover how you can best put these tools to work in your organization. In Inside AI AI professor and entrepreneur Dr. Akli Adjaoute puts AI in perspective, with informed insights from 30 years spent in the field. His book lays out a pragmatic blueprint that every leader can utilize to drive innovation with Artificial Intelligence. Inside AI provides a clear-headed overview of modern Artificial Intelligence, including the recent advances of Generative AI and Large Language Models. Its accessible and jargon-free explanations of leading AI techniques showcase how AI delivers tangible advantages to businesses. Both inspiring and practical, this book provides a proven framework for developing successful AI applications. Embark on an extensive exploration of the field of Artificial Intelligence within the 11 chapters of this insightful book. The journey begins with an introduction to fundamental principles, encompassing algorithms and programming languages, laying a solid foundation for understanding AI. Moving beyond, chapters 2 to 4 explore various AI techniques, covering expert systems, business rules, fuzzy logic, genetic algorithms, case-based reasoning, classical neural networks, Deep Learning, Bayesian networks, unsupervised learning, and smart agents.

Название: Metaheuristic Algorithms: Theory and Practice
Автор: Gаi-Gе Wаng, Хiаоqi Zhао, Кеqin Li
Издательство: CRC Press
Год: 2024
Страниц: 470
Язык: английский
Формат: pdf (true)
Размер: 21.5 MB

This book introduces the theory and applications of metaheuristic algorithms. It also provides methods for solving practical problems in such fields as software engineering, image recognition, video networks, and in the oceans. In the theoretical section, the book introduces the information feedback model, learning-based intelligent optimization, dynamic multi-objective optimization, and multi-model optimization. In the applications section, the book presents applications of optimization algorithms to neural architecture search, fuzz testing, oceans, and image processing. The neural architecture search chapter introduces the latest NAS method. The fuzz testing chapter uses multi-objective optimization and ant colony optimization to solve the seed selection and energy allocation problems in fuzz testing. In the ocean chapter, Deep Learning methods such as CNN, transformer, and attention-based methods are used to describe ENSO prediction and image processing for marine fish identification, and to provide an overview of traditional classification methods and Deep Learning methods.

Название: Special Topics in Artificial Intelligence and Augmented Reality: The Case of Spatial Intelligence Enhancement
Автор: Сhristоs Рараkоstаs, Сhristоs Тrоussаs, Сlео Sgоurороulоu
Издательство: Springer
Год: 2024
Страниц: 183
Язык: английский
Формат: pdf (true), epub
Размер: 18.9 MB

This monograph explores the synergy of Artificial Intelligence (AI), Augmented Reality (AR) and cognitive processes to enhance spatial abilities — an integral aspect of cognitive development. The ability to comprehend and manipulate spatial information is not only fundamental to our understanding of the physical world but also plays a pivotal role in numerous academic and professional fields. Recognizing the profound impact of spatial ability on scientific disciplines and educational achievement, this monograph takes on the challenge of enhancing spatial skills among users. In an ever-evolving world driven by technological advancements, the intersection of spatial intelligence, augmented reality, and fuzzy logic user modeling has emerged as a captivating frontier of research and innovation. These three interconnected realms are not only at the forefront of technological development but also have the potential to reshape and enhance a multitude of domains, including education, Artificial Intelligence, and industry. However, while these concepts have made waves in academic circles and technology hubs, their integration into education remains relatively uncharted territory.

Название: Computational Intelligence and Mathematics for Tackling Complex Problems 5
Автор: М. Еugеniа Соrnеjо, Lаszlо Т. Косzу, Jеsus Меdinа
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2024
Страниц: 151
Язык: английский
Формат: pdf (true), epub
Размер: 14.3 MB

This book is focused on connecting two interesting research areas, mathematics and Computational Intelligence, by means of appealing contributions devoted to give solutions to different challenges of the current technological age. It continues the collection of articles dealing with the important and efficient combination of these both areas, with a stress of fuzzy systems and fuzzy logic. It also includes relevant papers on the development and application of mathematics, Artificial Intelligence (AI), and automatic reasoning tools to Digital Forensics. The chapter “Efficiency of Fuzzy Rough Set Decision Algorithms” studies decision algorithms given in Rough Set Theory. Decision algorithms are used in this theory to know if a set of decision rules is suitable to describe a decision table. One of the most important notions associated with decision algorithms is the notion of efficiency. In this work, the authors present a generalized notion of efficiency, considering the fuzzy framework. The chapter “Use of Fuzzy Time Series to Generate Linguistic Descriptions of Noise Pollution” introduces a proposal to represent sets of time series by means of fuzzy time series composed of linguistic labels. This representation increases the interpretability of the fuzzy time series by using linguistic labels, which can be defined by an expert in the domain. The authors use the Monte Carlo method in order to match each fuzzy set in the initial fuzzy time series with the considered linguistic labels.

Название: Soft Computing Principles and Integration for Real-Time Service-Oriented Computing
Автор: Рunit Guрtа, Dinеsh Кumаr Sаini, Каshif Ziа
Издательство: CRC Press
Год: 2024
Страниц: 263
Язык: английский
Формат: pdf (true)
Размер: 18.3 MB

In recent years, soft computing techniques have emerged as a successful tool to understand and analyze the collective behavior of service- oriented computing software. Algorithms and mechanisms of self- organization of complex natural systems have been used to solve problems, particularly in complex systems, which are adaptive, ever- evolving, and distributed in nature across the globe. What fits more perfectly into this scenario other than the rapidly developing era of Fog, IoT, and Edge computing environment? Service- oriented computing can be enhanced with soft computing techniques embedded inside the Cloud, Fog, and IoT systems. Soft Computing Principles and Integration for Real-Time Service-Oriented Computing explores soft computing techniques that have wide application in interdisciplinary areas. These soft computing techniques provide an optimal solution to the optimization problem using single or multiple objectives.The book focuses on basic design principles and analysis of soft computing techniques. It discusses how soft computing techniques can be used to improve quality-of-service in serviceoriented architectures. The book also covers applications and integration of soft computing techniques with a service-oriented computing paradigm. Highlights of the book include: Soft computing also collaborates with various intelligent techniques used. (1) neural networks (NNs); (2) fuzzy logic; (3) genetic algorithm; (4) decision tree; (5) case base reasoning; (6) Probabilistic Reasoning (PR); and (7) Evolutionary Computation (EC) and other techniques of soft computing.

Название: Picture Fuzzy Logic and Its Applications in Decision Making Problems
Автор: Сhirаnjibе Jаnа, Маdhumаngаl Раl, Vаlеntinа Еmiliа Ваlаs
Издательство: Academic Press/Elsevier
Год: 2024
Страниц: 296
Язык: английский
Формат: pdf (true), epub
Размер: 15.6 MB

Picture Fuzzy Logic and Its Applications in Decision Making Problems provides methodological frameworks and the latest empirical research findings in the field of picture fuzzy operators and their applications in scientific research and real-world engineering problems. In this book, picture fuzzy sets are investigated, and different types of operators are defined to solve a number of important decision-making and optimization problems. The hybrid operator on picture fuzzy set based on the combination of picture fuzzy weighted averaging operators and picture fuzzy weighted geometric operators is developed and named Hybrid Picture Fuzzy Weighted Averaging Geometric (H-PFWAG) operator. In addition, another operator is developed for interval-valued picture fuzzy environment, which is named Hybrid Interval-Valued Picture Fuzzy Weighted Averaging Geometric (H-IVPFWAG) operator. These two operators are then demonstrated as solutions to Multiple-Attribute Decision-Making (MADM) problems. The picture fuzzy soft weighted aggregation operators (averaging and geometric) are defined, and these are applied to develop a multi-criteria group decision making system.

Название: Soft Computing Techniques in Connected Healthcare Systems
Автор: Мооlсhаnd Shаrmа, Sumаn Dеswаl, Umеsh Guрtа
Издательство: CRC Press
Год: 2024
Страниц: 313
Язык: английский
Формат: pdf (true)
Размер: 24.9 MB

This book provides an examination of applications of soft computing techniques related to healthcare systems and can be used as a reference guide for assessing the roles of various techniques. Soft Computing Techniques in Connected Healthcare Systems presents soft computing techniques and applications used in healthcare systems, along with the latest advancements. The authors examine how connected healthcare is the essence of combining a practical operative procedure of interconnectedness of electronic health records, mHealth, clinical informatics, electronic data exchange, practice management solutions, and pharmacy management. The book focuses on different soft computing techniques, such as artificial neural networks (ANNs), fuzzy logic, genetic algorithms (GAs), Machine Learning (ML), and Natural Language Processing (NLP), which will enhance services in connected health systems, such as remote diagnosis and monitoring, medication monitoring devices, identifying and treating the underlying causes of disorders and diseases, improved access to specialists, and lower healthcare costs. The chapters also examine descriptive, predictive, and social network techniques and discuss analytical tools and the important role they play in enhancing the services to connected healthcare systems. Finally, the authors address real-time challenges with real-world case studies to enhance the comprehension of topics. This book is intended for under graduate and graduate students, researchers, and practicing professionals in the field of connected healthcare. It provides an overview for beginners while also addressing professionals in the industry on the importance of soft computing approaches in connected healthcare systems.

Название: Fuzzy Logic-Based Software Systems
Автор: Коnstаntinа Сhrуsаfiаdi
Издательство: Springer
Год: 2023
Страниц: 187
Язык: английский
Формат: pdf (true), epub
Размер: 10.3 MB

This book aims to provide information about significant advances of Fuzzy Logic in software systems to researchers, scientists, educators, students, software engineers and developers. In particular, this book explains how Fuzzy Logic, can be used in software systems to automatically predict, model, decide, diagnose, recommend etc.. In more details, Fuzzy Logic is an artificial intelligent technique that is ideal for successfully addressing, , the uncertainty, imprecision and vagueness that exist in many diverse scientific and technological areas. It was introduced by Lotfi A. Zadeh of the University of California at Berkeley, as a methodology for computing with words. This ability of Fuzzy Logic allows the representation of imprecise and vague data in a more realistic way. Therefore, Fuzzy Logic-based systems can simulate the human reasoning and decision-making processes, addressing the human subjectivity. Fuzzy Logic-based software systems are referred to any software that concerns an automated program or process that is used in everyday life, like heating or air-conditioning system, or in the scientific world, like a medical diagnostic system, which uses Fuzzy Logic in order to perform reasoning. Artificial Intelligence (AI) is the process of making machines to think and to do tasks like humans. It includes advanced technologies that make machines more intelligent and capable of performing tasks more efficiently and reliable. There is a variety of AI techniques including Machine Learning, artificial neural networks, Deep Learning, knowledge representation and reasoning techniques. An AI technique is Fuzzy Logic, which allows reasoning in cases where there is uncertainty, vagueness, imprecision and/or subjectivity.

Название: Fuzzy Logic Applications in Computer Science and Mathematics
Автор: Rahul Kar, Dac-Nhuong Le, Gunjan Mukherjee, Biswadip Basu Mallik
Издательство: Wiley-Scrivener
Год: 2023
Страниц: 300
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Covered in this book are topics such as the fundamental concepts of mathematics, fuzzy logic concepts, probability and possibility theories, and evolutionary computing to some extent. The combined fields of neural network and fuzzy domain (known as the neuro-fuzzy system) are explained and elaborated through many highly regarded research papers. Each chapter has been produced in a very lucid manner, with a grading from simple to complex in an effort to accommodate different audiences. The application-oriented approach is the unique feature of this book. Apart from the theoretical discussion, the problems and the allied case studies concerned with the topics discussed in this book will be of great interest to a broad audience. The problems and the case studies furnished in this book are worthwhile to researchers and academicians, as well. This book comprises state-of-the-art information on a wide range of various subjects, all directly or indirectly connected to the overarching topic. The prime objective of developing this book was to provide meticulous details about the basic and advanced concepts of fuzzy logic and its all-around applications to different fields of mathematics and engineering. The book caters to a certain level of professional knowledge, academicians, students, and researchers.

Название: Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics
Автор: Oscar Castillo, Patricia Melin
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2023
Страниц: 489
Язык: английский
Формат: pdf (true)
Размер: 18.9 MB

In this book, recent theoretical developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, are presented. In addition, the above-mentioned methods are presented in application areas such as, intelligent control and robotics, pattern recognition, medical diagnosis, decision-making, time series prediction and optimization of complex problems. The book contains a collection of papers focused on hybrid intelligent systems based on soft computing techniques. There are a group of papers with the main theme of type-1 and type-2 fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications. There also a group of papers that offer theoretical concepts and applications of meta-heuristics in different areas. Another group of papers outlines diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical problems. There are also some papers that present theory and practice of neural networks in different application areas. In addition, there are papers that offer theory and practice of optimization and evolutionary algorithms in different application areas. Finally, there are a group of papers describing applications of fuzzy logic, neural networks and meta-heuristics in pattern recognition and classification problems.