This book contains papers presented at the sixth International Conference on Application of Artificial Intelligence in Engineering held in Oxford, UK in was held in Southampton, UK July 1991. The first conference in this series the second in Cambridge, Massachusetts, USA in 1987, the third in 1986, 1989 in Palo Alto, California, USA in 1988, the fourth in Cambridge, UK in and the fifth in Boston, Massachusetts, USA in 1990. The conference series has now established itself as the unique forum for the presentation of the latest research, development and application of artificial intelligence (AI) in all fields of engineering. Consequently, books of conference proceedings provide a historical record of the application of AI in engineering design, analysis, simulation, planning, scheduling, monitoring, control, diagnosis, reliability and quality, as well as in robotics and manufacturing systems, from the early beginnings to mature applications of today. Whilst previously the field was dominated by knowledge-based systems, in this latest volume, for the first time, a significant proportion of papers cover the paradigms of neural networks and genetic algorithms. Learning and self organising behaviour of systems based on these paradigms are particularly important in engineering applications. From a large number of submitted proposals over sixty papers have been selected by members of the Advisory Committee who acted as referees. Pa pers have been grouped under the following headings.

Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis Gives direction to future development trends of AI technologies in chemical and process engineering

These proceedings cover state of the art applications of artificial intelligence to a wide range of engineering problems. It covers basic research in artificial intelligence as well as application areas of design, manufacturing, vehicles, robotics surveillance and others.

This text presents state-of-the-art applications of AI for engineering problems and contains the edited proceedings of the tenth International Conference on Applications of Artificial Intelligence in Engineering, held in Udine, Italy during July 1995.

Artificial intelligence is increasingly finding its way into industrial and manufacturing contexts. The prevalence of AI in industry from stock market trading to manufacturing makes it easy to forget how complex artificial intelligence has become. Engineering provides various current and prospective applications of these new and complex artificial intelligence technologies. Applications of Artificial Intelligence in Electrical Engineering is a critical research book that examines the advancing developments in artificial intelligence with a focus on theory and research and their implications. Highlighting a wide range of topics such as evolutionary computing, image processing, and swarm intelligence, this book is essential for engineers, manufacturers, technology developers, IT specialists, managers, academicians, researchers, computer scientists, and students.

Applications of Artificial Intelligence Techniques in the Petroleum Industry gives engineers a critical resource to help them understand the machine learning that will solve specific engineering challenges. The reference begins with fundamentals, covering preprocessing of data, types of intelligent models, and training and optimization algorithms. The book moves on to methodically address artificial intelligence technology and applications by the upstream sector, covering exploration, drilling, reservoir and production engineering. Final sections cover current gaps and future challenges. Teaches how to apply machine learning algorithms that work best in exploration, drilling, reservoir or production engineering Helps readers increase their existing knowledge on intelligent data modeling, machine learning and artificial intelligence, with foundational chapters covering the preprocessing of data and training on algorithms Provides tactics on how to cover complex projects such as shale gas, tight oils, and other types of unconventional reservoirs with more advanced model input