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Artificial intelligence and machine learning techniques for civil engineering
Offers state-of-the-art contributions in the area of AI and its applications in the field of civil engineering presenting methods and implementation of AI and machine learning in multiple facets of civil engineering
Artificial intelligence and machine learning in health care and medical sciences : Best practices and pitfalls
Provides a detailed review of the latest methods and applications of artificial intelligence (AI) and machine learning (ML) in medicine. With chapters focusing on enabling the reader to develop a thorough understanding of the key concepts in these subject areas along with a range of methods and resulting models that can be utilized to solve healthcare problems, the use of causal and predictive models are comprehensively discussed. Care is taken to systematically describe the concepts to facilitate the reader in developing a thorough conceptual understanding of how different methods and resulting models function and how these relate to their applicability to various issues in health care and medical sciences. Guidance is also given on how to avoid pitfalls that can be encountered on a day-to-day basis and stratify potential clinical risks.
Artificial intelligence and knowledge engineering applications : A bioinspired approach ; 1st international work-Conference on the interplay between natural and artificial computation, IWINAC 2005, Las Palmas, Canary Islands, Spain, June 15-18, 2005, Proceedings, Part II
The computational paradigm considered here is a conceptual, theoretical andformal framework situated above machines and living creatures (two instantia-tions), sufficiently solid, and still non-exclusive, that allows us:1. to help neuroscientists to formulate intentions, questions, experiments, meth-ods and explanation mechanisms assuming that neural circuits are the psy-chological support of calculus;2. to help scientists and engineers from the fields of artificial intelligence (AI)and knowledge engineering (KE) to model, formalize and program the com-putable part of human knowledge;3. to establish an interaction framework between natural system computation(NSC) and artificial system computation (ASC) in both directions, fromASC to NSC (in computational neuroscience), and from NSC to ASC (inbioinspired computation).
Artificial Intelligence and Cybersecurity : Advances and Innovations
Provides advanced system implementation for Smart Cities using artificial intelligence. It addresses the complete functional framework workflow and explores basic and high-level concepts. The book is based on the latest technologies covering major challenges, issues and advances, and discusses intelligent data management and automated systems.
Artificial intelligence : Theories, models and applications ; 5th Hellenic Conference on AI, SETN 2008, Syros, Greece, October 2-4, 2008. Proceedings
This book constitutes the refereed proceedings of the 5th Hellenic Conference on Artificial Intelligence, SETN 2008, held at Syros, Greece in October 2008.
Artificial intelligence : Methodology, systems, and applications ; 13th International Conference, AIMSA 2008, Varna, Bulgaria, September 4-6, 2008. Proceedings
This book constitutes the refereed proceedings of the 13th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2008, held in Varna, Bulgaria in September 2008.
Artificial intelligence : Methodology, systems, and applications ; 12th International Conference, AIMSA 2006, Varna, Bulgaria, September 12-15, 2006, Proceedings
This book constitutes the refereed proceedings of the 12th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2006. The 28 revised full papers presented together with the abstracts of 2 invited lectures were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections on agents, constraints and optimization, user concerns, decision support, models and ontologies, machine learning, ontology manipulation, natural language processing, and applications.
Artificial Intelligence : Applications and innovations
It's about the science of artificial intelligence (AI). AI is the study of the design of intelligent computational agents. This book provides a valuable resource for researchers, scientists, professionals, academicians and students dealing with the new challenges and advances in the areas of AI and innovations. This book also covers a wide range of applications of machine learning such as fire detection, structural health and pollution monitoring and control. Provides insight into prospective research and application areas related to industry and technology / Discusses industry- based inputs on success stories of technology adoption / Discusses technology applications from a research perspective in the field of AI / Provides a hands- on approach and case studies for readers of the book to practice and assimilate learning
Artificial intelligence : A modern approach ; global ed.
Explores the full breadth and depth of the field of artificial intelligence (AI). The 4th edition brings readers up to date on the latest technologies, presents concepts in a more unified manner, and offers new or expanded coverage of machine learning, deep learning, transfer learning, multi agent systems, robotics, natural language processing, causality, probabilistic programming, privacy, fairness, and safe AI
Artificial evolution ; 7th International Conference, Evolution artificielle, EA 2005, revised selected papers
This book constitutes the thoroughly refereed post-proceedings of the 7th International Conference on Artificial Evolution, EA 2005, held in Lille, France, in October 2005. They cover all aspects of artificial evolution: genetic programming, machinelearning, combinatorial optimization, co-evolution, self-assembling, artificial lifeand bioinformatics.In addition, the program included an invited talk by David Corne on “Evolu-tionary Computation in Bioinformatics: How to Save Lives and Make ScientificBreakthrough.
Artifical intelligence for human computing ; ICMI 2006 and IJCAI 2007 International Workshops, Banff, Canada, November 3, 2006 Hyderabad, India, January 6, 2007 Revised Selceted Papers
This book contains the thoroughly refereed post-proceedings of two events discussing AI for Human Computing.It presented a vision of the future of computing technology in which AI, in particular machine learning and agent technology, plays an essential role.
Applied mathematics and machine learning
The simultaneous availability of large datasets and high-performance computing capability in recent years has enabled the rapid development of powerful machine learning algorithms. On the one hand, state-of-the-art machine learning techniques have transformed many areas of science and engineering; on the other hand, theoretical discoveries in mathematical algorithms, differential equations, and statistical inferences, to name a few, have provided the foundation for the exploration of new multidisciplinary models for solving practical problems. This Special Issue endeavors to continue the journey that started in our previous Special Issue (Applied Mathematics and Computational Physics) by providing a platform for researchers from both academia and industry, as well as government, to present their new computational methods that have engineering and physics applications.
Applied Informatics; Third International Conference, ICAI 2020, Ota, Nigeria, October 29–31, 2020, Proceedings
This book constitutes the thoroughly refereed papers of the Second International Conference on Applied Informatics, ICAI 2020, held in Ota, Nigeria, in October 2020. The 35 full papers were carefully reviewed and selected from 101 submissions. The papers are organized in topical sections on artificial intelligence; business process management; cloud computing; data analysis; decision systems; health care information systems; human-computer interaction; image processing; learning management systems; software design engineering.
Applied Deep Learning with TensorFlow 2 : Learn to Implement Advanced Deep Learning Techniques with Python
Focuses on the fundamental concepts and at the same time on practical aspects of implementing neural networks and deep learning for your research projects. This book is designed so that you can focus on the parts you are interested in. You will explore topics as regularization, optimizers, optimization, metric analysis, and hyper-parameter tuning. In addition, you will learn the fundamentals ideas behind autoencoders and generative adversarial networks. All the code presented in the book will be available in the form of Jupyter notebooks which would allow you to try out all examples and extend them in interesting ways. A companion online book is available with the complete code for all examples discussed in the book and additional material more related to TensorFlow and Keras. All the code will be available in Jupyter notebook format and can be opened directly in Google Colab (no need to install anything locally) or downloaded on your own machine and tested locally. You will: Understand the fundamental concepts of how neural networks work / Learn the fundamental ideas behind autoencoders and generative adversarial networks / Be able to try all the examples with complete code examples that you can expand for your own projects / Have available a complete online companion book with examples and tutorials.
Applied and computational mathematics for digital environments
Contains the 11 papers that were accepted and published in the Special Issue “Applied and Computational Mathematics for Digital Environments” of the MDPI Mathematics journal. The topics of interest include, among others, scientific research, applied tasks, and problems in the following areas: The construction of mathematical and information models of intelligent computer systems for monitoring and controlling the parameters of digital environments; The development of intelligent optimization algorithms that search for optimal parameter values of mathematical and information models in digital environments; Software and mathematical technologies in the implementation of intelligent monitoring and computer control of the parameters of digital environments; The development and application of mathematical and information models, machine learning methods, and artificial intelligence for the analysis and processing of big data in digital environments.
Applications of Fuzzy Sets Theory ; 7th International Workshop on Fuzzy Logic and Applications, WILF 2007, Camogli, Italy, July 7-10, 2007, Proceedings
The book is organized in topical sections on fuzzy set theory, fuzzy information access and retrieval, fuzzy machine learning, fuzzy architectures and systems; and special sessions on intuitionistic fuzzy sets and soft computing in image processing.
Applications of computational intelligence in data-driven trading
The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term “Artificial Intelligence,” especially as it relates to the financial industry.
Applications and Innovations in Intelligent Systems XIII ; Proceedings of AI-2005, the Twenty-fifth SGAI International Conference on Innovative Techniques and Applications of Artifical Intelligence
The papers in this volume present new and innovative developments in the field, divided into sections on Applied AI in Information Processing, Techniques for Applied AI, Industrial Applications and Medical Applications.This is the thirteenth volume in the Applications and Innovations series. The series serves as a key reference as to how AI technology has enabled organisations to solve complex problems and gain significant business benefit.
Application and theory of multimedia signal processing using machine learning or advanced methods
Consists of a collection of peer-reviewed published papers on various advanced technology researches related to signal processing applications and theories for multimedia systems using machine learning or advanced methods. Multimedia signals include image, video, audio, character recognition, and communication channel optimization for networks. The specific contents included in this book are data hiding, encryption, object detection, image classification, and character recognition.
Anomaly Detection : Techniques and Applications
When information in the data warehouse is processed, it follows a definite pattern. An unexpected deviation in the data pattern from the usual behavior is called an anomaly. The anomaly in the data is also referred to as noise, outlier, spammer, deviations, novelties and exceptions. Identification of the rare items, events, observations, patterns which raise suspension by differing significantly from the majority of data is called anomaly detection. With progress in the technologies and the widespread use of data for the purpose for business the increase in the spams faced by the individuals and the companies are increasing day by day. This noisy data has boomed as a major problem in various areas such as Internet of Things, web service, Machine Learning, Artificial Intelligence, Deep learning, Image Processing, Cloud Computing, Audio processing, Video Processing, VoIP, Data Science, Wireless Sensor etc. Identifying the anomaly data and filtering them before processing is a major challenge for the data analyst. This anomaly is unavoidable in all areas of research. This book covers the techniques and algorithms for detecting the deviated data.
