Artificial Intelligence and Cognitive Computing : Methods, Technologies, Systems, Applications and Policy Making

doi:10.3390/books978-3-0365-1160-3

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https://mdpi.com/books/pdfview/book/3715

Contributor(s)

Lytras, Miltiadis (editor)

Visvizi, Anna (editor)

Language

English

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Abstract

Artificial intelligence (AI) is a subject garnering increasing attention in both academia and the industry today. The understanding is that AI-enhanced methods and techniques create a variety of opportunities related to improving basic and advanced business functions, including production processes, logistics, financial management and others. As this collection demonstrates, AI-enhanced tools and methods tend to offer more precise results in the fields of engineering, financial accounting, tourism, air-pollution management and many more. The objective of this collection is to bring these topics together to offer the reader a useful primer on how AI-enhanced tools and applications can be of use in today’s world. In the context of the frequently fearful, skeptical and emotion-laden debates on AI and its value added, this volume promotes a positive perspective on AI and its impact on society. AI is a part of a broader ecosystem of sophisticated tools, techniques and technologies, and therefore, it is not immune to developments in that ecosystem. It is thus imperative that inter- and multidisciplinary research on AI and its ecosystem is encouraged. This collection contributes to that.

URI

https://directory.doabooks.org/handle/20.500.12854/76299

Keywords

data mining; decision-making system; rough set; mixed integer linear programming; assembly clearance; diesel engine quality; Internet of things; Wireless nodes; Hybrid clustering; Multi-hop routing; Network lifetime; Artificial intelligence; data envelopment analysis; decision making; artificial intelligence; performance; visual analytics; system; air quality; spatiotemporal; multivariate; dimension reduction; clustering; regular patterns; anomalies; speech recognition; Long Short Term Memory (LSTM); speech output correction; most-matching; empirical correlations; rheological properties; real-time; water-based drill-in fluid; artificial neural network; elastic parameters; Poisson’s ratio; sandstone; self-adaptive differential evolution; total organic carbon; barnett shale; devonian shale; fishbone multilateral wells; predictive models; well productivity; international research; knowledge map visualization; policy documents quantification; research hotspot; policy keyword; minimum miscibility pressure (MMP); CO2 flooding; new models; face recognition; security; spoofing; histogram of oriented gradients; smart cities; deep learning; LSTM; neural networks; location prediction; trajectories; smart tourism; static Young’s modulus; sandstone formations; machine learning; n/a