کتابخانه

Title: Artificial Intelligence: Advances in Research and Applications | Author(s): Luis Rabelo, Sayli Bhide, Edgar Gutierrez | Publisher: Nova Science | Year: 2018  | Language: English | Pages : 364 | Size: 13 MB | Extension: pdf

After decades of basic research and more promises than impressive applications, artificial intelligence (AI) is starting to deliver benefits. A convergence of advances is motivating this new surge of AI development and applications. Computer capability as it has evolved from high throughput and high performance computing systems is increasing. AI models and operations research adaptations are becoming more mature, and the world is breeding big data not only from the web and social media but also from the Internet of Things.
Organizations around the world have been realizing that there are substantial performance gains and increases in productivity for the use of AI and predictive analytics techniques. Their use is bringing a new era of breakthrough innovation and opportunities. This book, compiles research insights and applications in diverse areas such as manufacturing, supply chain management, pricing, autonomous vehicles, healthcare, ecommerce, and aeronautics. Using classical and advanced tools in AI such as deep learning, particle swarm optimization, support vector machines and genetic programming among others.
This is a very distinctive book which discusses important applications using a variety of paradigms from AI and outlines some of the research to be performed. The work supersedes similar books that do not cover as diversified a set of sophisticated applications. The authors present a comprehensive and articulated view of recent developments, identifies the applications gap by quoting from the experience of experts, and details suggested research areas.
Artificial Intelligence: Advances in Research and Applications guides the reader through an intuitive understanding of the methodologies and tools for building and modeling intelligent systems. The books coverage is broad, starting with clustering techniques with unsupervised ensemble learning, where the optimal combination strategy of individual partitions is robust in comparison to the selection of an algorithmic clustering pool. This is followed by a case in a parallel-distributed simulator using deep learning for its configuration. Chapter Three presents a case for autonomous vehicles. Chapter Four discusses the novel use of genetic algorithms with support vector machines. Chapters Five through Thirteen focus on the applications. The book discusses how the use of AI can allow for productivity development and other benefits not just for businesses, but also for economies. Finally, you can find an interesting investigation of the “transhuman” dimension of AI. (Nova)

Table of Contents:
Preface

Chapter 1. Unsupervised Ensemble Learning
(Ramazan Ünlü, Industrial Engineering and Management Systems, University of Central Florida, Orlando, Florida, US)

Chapter 2. Using Deep Learning to Configure Parallel Distributed Discrete-Event Simulators
(Edwin Cortes, Luis Rabelo, and Gene Lee, Institute of Simulation and Training, Orlando, Florida, US, and others)

Chapter 3. Machine Learning Applied to Autonomous Vehicles
(Olmer Garcia and Cesar Diaz, School of Engineering, Universidad Jorge Tadeo Lozano, Bogotá, Colombi, and others)

Chapter 4. Evolutionary Optimization of Support Vector Machines Using Genetic Algorithms
(Fred K. Gruber, Principal Scientist, GNS Healthcare, Cambridge, Massachusetts, US)

Chapter 5. Texture Descriptors for the Generic Pattern Classification Problem
(Olmer Garcia and Cesar Diaz, School of Engineering, Universidad Jorge Tadeo Lozano, Bogotá, Colombia)

Chapter 6. Simulation Optimization Using a Hybrid Scheme with Particle Swarm Optimization for a Manufacturing Supply Chain
(Alfonso T. Sarmiento and Edgar Gutierrez-Franco, Program of Industrial Engineering, University of La Sabana, Chía, Colombia, and others)

Chapter 7. The Estimation of Cutting Forces in the Turning of Inconel 718 Assisted with a High Pressure Coolant using Bio-Inspired Artificial Neural Networks
(Djordje Cica and Davorin Kramar, Univeristy of Banja Luka, Faculty of Mehanical Engineering, Stepe Stepanovica, Banja Luka, Bosnia and Herzegovina, and others)

Chapter 8. Predictive Analytics Using Genetic Programming
(Luis Rabelo, Edgar Gutierrez, Sayli Bhide, and Mario Marin, Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, Florida, US, and others)

Chapter 9. Managing Overcrowding in Healthcare Using Fuzzy Logic
(Abdulrahman Albar, Ahmad Elshennawy, Mohammed Basingab, and Haitham Bahaitham, Industrial Engineering, Jazan University, Jazan, Saudi Arabia, and others)

Chapter 10. The Utilization of Case-Based Reasoning: A Case Study of the Healthcare Sector Using Simulation Modeling
(Khaled Alshareef, Ahmad Rahal, and Mohammed Basingab, Industrial and Systems Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia, and others)

Chapter 11. Agent-Based Modeling Simulation and Its Application to Ecommerce
(Oloruntomi Joledo, Edgar Gutiérrez-Franco, and Hatim Bukhari, Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, Florida, US, and others)

Chapter 12. Artificial Intelligence for the Modeling and Prediction of the Bioactivities of Complex Natural Products
(Jose M. Prieto, UCL School of Pharmacy, London, United Kingdom)

Chapter 13. Predictive Analytics for Thermal Coal Prices Using Neural Networks and Regression Trees
(Mayra Bornacelli, Edgar Gutierrez-Franco, and John Pastrana, Carbones del Cerrejón (BHP Billiton, Anglo American, Xtrata), Bogota, Colombia, and others)

Chapter 14. Explorations of the "Transhuman" Dimension of Artificial Intelligence
(Bert Olivier, Department of Philosophy, University of the Free State, Bloemfontein, South Africa)

Index