[PDF] Advances In Artificial Intelligence Iberamia 2018 eBook

Author : Guillermo R. Simari
Publisher : Springer
Page : 520 pages
File Size : 46,41 MB
Release : 2018-11-08
Category : Computers
ISBN : 3030039285

GET BOOK

This book constitutes the refereed proceedings of the 16th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2018, held in Trujillo, Peru,in November 2018. The 41 papers presented were carefully reviewed and selected from 92 submissions. The papers are organized in the following topical sections: Knowledge Engineering, Knowledge Representation and Reasoning under Uncertainty., Multiagent Systems., Game Theory and Economic Paradigms, Game Playing and Interactive Entertainment, Ambient Intelligence, Machine Learning Methods, Cognitive Modeling,General AI, Knowledge Engineering, Computational Sustainability and AI, Heuristic Search and Optimization and much more.

Author : Ana Cristina Bicharra Garcia
Publisher : Springer Nature
Page : 422 pages
File Size : 24,35 MB
Release : 2023-01-03
Category : Computers
ISBN : 3031224191

GET BOOK

This book constitutes the refereed proceedings of the 17th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2022, held in Cartagena de Indias, Colombia, in November 2022. The 33 full and 4 short papers presented were carefully reviewed and selected from 67 submissions. The papers are organized in the following topical sections: applications of AI; ethics and smart city; green and sustainable AI; machine learning; natural language processing; robotics and computer vision; simulation and forecasting.

Author : Francisco Herrera
Publisher : Springer
Page : 264 pages
File Size : 30,18 MB
Release : 2019-06-21
Category : Technology & Engineering
ISBN : 3030238873

GET BOOK

This book features the outcomes of the 16th International Conference on Distributed Computing and Artificial Intelligence 2019 (DCAI 2019), which is a forum to present applications of innovative techniques for studying and solving complex problems in artificial intelligence and computing. The exchange of ideas between scientists and technicians from both the academic and industrial sectors is essential to facilitate the development of systems that can meet the ever-increasing demands of today’s society. This book brings together lessons learned, current work and promising future trends associated with distributed computing, artificial intelligence and their application to provide efficient solutions to real-world problems. The book includes 29 high-quality and diverse contributions in established and emerging areas of research presented at the symposium organized by the Osaka Institute of Technology, Hiroshima University, University of Granada and University of Salamanca, which was held in Ávila, Spain, from 26th–28th June 2019

Author : Xiao-Zhi Gao
Publisher : Springer Nature
Page : 922 pages
File Size : 11,55 MB
Release : 2021-05-10
Category : Technology & Engineering
ISBN : 9813346043

GET BOOK

This book presents best selected papers presented at the First Global Conference on Artificial Intelligence and Applications (GCAIA 2020), organized by the University of Engineering & Management, Jaipur, India, during 8–10 September 2020. The proceeding will be targeting the current research works in the domain of intelligent systems and artificial intelligence.

Author : Shalli Rani
Publisher : John Wiley & Sons
Page : 308 pages
File Size : 47,32 MB
Release : 2022-02-16
Category : Computers
ISBN : 1119763479

GET BOOK

MACHINE LEARNING PARADIGM FOR INTERNET OF THINGS APPLICATIONS As companies globally realize the revolutionary potential of the IoT, they have started finding a number of obstacles they need to address to leverage it efficiently. Many businesses and industries use machine learning to exploit the IoT’s potential and this book brings clarity to the issue. Machine learning (ML) is the key tool for fast processing and decision-making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. Machine learning has become a common subject to all people like engineers, doctors, pharmacy companies, and business people. The book addresses the problem and new algorithms, their accuracy, and their fitness ratio for existing real-time problems. Machine Learning Paradigm for Internet of Thing Applications provides the state-of-the-art applications of machine learning in an IoT environment. The most common use cases for machine learning and IoT data are predictive maintenance, followed by analyzing CCTV surveillance, smart home applications, smart-healthcare, in-store ‘contextualized marketing’, and intelligent transportation systems. Readers will gain an insight into the integration of machine learning with IoT in these various application domains.

Author : Christina Ahmet
Publisher : Shockwave Publishing via PublishDrive
Page : 69 pages
File Size : 11,56 MB
Release : 2018-11-20
Category : Computers
ISBN :

GET BOOK

Currently, Artificial Intelligence (AI) lives amongst the human population. They reside in smartphones. They help people find content on the internet. They learn the behavior of their owners and put out relevant, interesting content to enhance their owner's experience while they are browsing on the internet. In this book you will learn all about Artificial Intelligence and how it will affect your life in the near future. Learn exactly what Artificial Intelligence is Machine Learning AI and The Internet Of Things Opportunities for Artificial Intelligence Intelligent IoT and much much more!

Author : Valentina E. Balas
Publisher : Springer Nature
Page : 618 pages
File Size : 43,99 MB
Release : 2019-11-19
Category : Technology & Engineering
ISBN : 3030326446

GET BOOK

This book covers all the emerging trends in artificial intelligence (AI) and the Internet of Things (IoT). The Internet of Things is a term that has been introduced in recent years to define devices that are able to connect and transfer data to other devices via the Internet. While IoT and sensors have the ability to harness large volumes of data, AI can learn patterns in the data and quickly extract insights in order to automate tasks for a variety of business benefits. Machine learning, an AI technology, brings the ability to automatically identify patterns and detect anomalies in the data that smart sensors and devices generate, and it can have significant advantages over traditional business intelligence tools for analyzing IoT data, including being able to make operational predictions up to 20 times earlier and with greater accuracy than threshold-based monitoring systems. Further, other AI technologies, such as speech recognition and computer vision can help extract insights from data that used to require human review. The powerful combination of AI and IoT technology is helping to avoid unplanned downtime, increase operating efficiency, enable new products and services, and enhance risk management.