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 book's 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.
Table of Contents
Chapter 1 Unsupervised Ensemble Learning
Chapter 2 Using Deep Learning to Configure Parallel Distributed Discrete-Event Simulators
Chapter 3 Machine Learning Applied to Autonomous Vehicles
Chapter 4 Evolutionary Optimization of Support Vector Machines Using Genetic Algorithms
Chapter 5 Texture Descriptors for the Generic Pattern Classification Problem
Chapter 6 Simulation Optimization Using a Hybrid Scheme with Particle Swarm Optimization for a Manufacturing Supply Chain
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
Chapter 8 Predictive Analytics using Genetic Programming
Chapter 9 Managing Overcrowding in Healthcare using Fuzzy Logic
Chapter 10 The Utilization of Case-Based Reasoning: A Case Study of the Healthcare Sector Using Simulation Modeling
Chapter 11 Agent-Based Modeling Simulation and Its Application to Ecommerce
Chapter 12 Artificial Intelligence for the Modeling and Prediction of the Bioactivities of Complex Natural Products
Chapter 13 Predictive Analytics for Thermal Coal Prices Using Neural Networks and Regression Trees
Chapter 14 Explorations of the ‘Transhuman’ Dimension of Artificial Intelligence
- Title: Artificial Intelligence: Advances in Research and Applications
- Length: 291 pages
- Edition: 1
- Language: English
- Publisher: Nova Science Pub Inc
- Publication Date: 2018-02-01
- ISBN-10: 1536126772
- ISBN-13: 9781536126778