Ai Applied To Simulation


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AI Applied to Simulation


AI Applied to Simulation

Author: E. J. H. Kerckhoffs

language: en

Publisher:

Release Date: 1986


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Applying AI-Based IoT Systems to Simulation-Based Information Retrieval


Applying AI-Based IoT Systems to Simulation-Based Information Retrieval

Author: Madhulika, Bhatia

language: en

Publisher: IGI Global

Release Date: 2023-05-01


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Communication based on the internet of things (IoT) generates huge amounts of data from sensors over time, which opens a wide range of applications and areas for researchers. The application of analytics, machine learning, and deep learning techniques over such a large volume of data is a very challenging task. Therefore, it is essential to find patterns, retrieve novel insights, and predict future behavior using this large amount of sensory data. Artificial intelligence (AI) has an important role in facilitating analytics and learning in the IoT devices. Applying AI-Based IoT Systems to Simulation-Based Information Retrieval provides relevant frameworks and the latest empirical research findings in the area. It is ideal for professionals who wish to improve their understanding of the strategic role of trust at different levels of the information and knowledge society and trust at the levels of the global economy, networks and organizations, teams and work groups, information systems, and individuals as actors in the networked environments. Covering topics such as blockchain visualization, computer-aided drug discovery, and health monitoring, this premier reference source is an excellent resource for business leaders and executives, IT managers, security professionals, data scientists, students and faculty of higher education, librarians, hospital administrators, researchers, and academicians.

Artificial Intelligence, Simulation, and Modeling


Artificial Intelligence, Simulation, and Modeling

Author: Lawrence E. Widman

language: en

Publisher:

Release Date: 1989-09-06


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This interdisciplinary approach to computer modeling addresses both traditional simulationists seeking the greater representational flexibility and ease of use that AI techniques offer, and computer scientists seeking the greater power and realism that rigorous simulation techniques can provide. First section reveals the theoretical underpinnings of AI and simulation. Second section describes application of simulation techniques to current problems in AI research. Third section discusses application of AI methods to simulation.