Books
Innovations in Machine and Deep Learning: Case Studies and Applications
Studies in Big Data 134
In recent years, significant progress has been made in achieving artificial intelligence (AI) with an impact on students, managers, scientists, health personnel, technical roles, investors, teachers, and leaders. This book presents numerous successful applications of AI in various contexts.
The innovative implications covered fall under the general field of machine learning (ML), including deep learning, decision-making, forecasting, pattern recognition, information retrieval, and interpretable AI. Decision-makers and entrepreneurs will find numerous successful applications in health care, sustainability, risk management, human activity recognition, logistics, and Industry 4.0.
This book is an essential resource for anyone interested in challenges, opportunities, and the latest developments and real-world applications of ML. Whether you are a student, researcher, practitioner, or simply curious about AI, this book provides valuable insights and inspiration for your work and learning.
Rivera, G., Rosete, A., Dorronsoro, B., & Rangel-Valdez, N. (Eds.) (2023). "Innovations in Machine and Deep Learning: Case Studies and Applications". Studies in Big Data 134, Springer Cham. https://doi.org/10.1007/978-3-031-40688-1
Data Analytics and Computational Intelligence: Novel Models, Algorithms and Applications
Studies in Big Data 132
In the age of transformative artificial intelligence (AI), which has the potential to revolutionize our lives, this book provides a comprehensive exploration of successful research and applications in AI and data analytics.
Covering innovative approaches, advanced algorithms, and data analysis methodologies, this book addresses complex problems across topics such as machine learning, pattern recognition, data mining, optimization, and predictive modeling.
With clear explanations, practical examples, and cutting-edge research, this book seeks to expand the understanding of a wide readership, including students, researchers, practitioners, and technology enthusiasts eager to explore these exciting fields.
Featuring real-world applications in education, health care, climate modeling, cybersecurity, smart transportation, conversational systems, and material analysis, among others, this book highlights how these technologies can drive innovation and generate competitive advantages.
Rivera, G., Cruz-Reyes, L., Dorronsoro, B., & Rosete, A. (Eds.) (2023). "Data Analytics and Computational Intelligence: Novel Models, Algorithms and Applications". Studies in Big Data 132, Springer Cham. https://doi.org/10.1007/978-3-031-38325-0
Computational Intelligence for Business Analytics
Studies in Computational Intelligence 953
Corporate success has been changed by the importance of new developments in Business Analytics (BA) and, furthermore, by the support of computational intelligence-based techniques. This book opens a new avenue in these subjects and identifies key developments and opportunities. The book will be of interest to students, researchers, and professionals to identify innovative ways delivered by Business Analytics based on computational intelligence solutions. They help elicit information, handle knowledge, and support decision-making for more informed and reliable decisions even under high-uncertainty environments.
Computational Intelligence for Business Analytics has collected the latest technological innovations in the field of BA to improve business models related to Group Decision-Making, Forecasting, Risk Management, Knowledge Discovery, Data Breach Detection Social Well-Being, among other key topics related to this field.
Pedrycz, W., Martínez, L., Espin-Andrade, R. A., Rivera, G., & Marx-Gómez, J. (Eds.) (2021). "Computational Intelligence for Business Analytics". Studies in Computational Intelligence 953, Springer Cham. https://doi.org/10.1007/978-3-030-73819-8
Soft Computing for Business Intelligence
Studies in Computational Intelligence 537
The book Soft Computing for Business Intelligence is the remarkable output of a program based on the idea of joint trans-disciplinary research as supported by the Eureka Iberoamerica Network and the University of Oldenburg.
It contains twenty-seven papers allocated to three sections: Soft Computing, Business Intelligence and Knowledge Discovery, and Knowledge Management and Decision Making. Although the contents touch different domains, they are similar in so far as they follow the BI principle of “Observation and Analysis” while keeping a practical-oriented theoretical eye on sound methodologies, like Fuzzy Logic, Compensatory Fuzzy Logic (CFL), Rough Sets, and other soft computing elements.
The book tears down the traditional focus on business and extends Business Intelligence techniques in an impressive way to a broad range of fields like medicine, environment, wind farming, social collaboration and interaction, car sharing, and sustainability.
Espin-Andrade, R. A., Bello Pérez, R, Cobo, A., Marx-Gómez, J, & Racet-Valdés, A. (Eds.) (2014). "Soft Computing for Business Intelligence". Studies in Computational Intelligence 537, Springer Verlag. https://doi.org/10.1007/978-3-642-53737-0
Studies on Knowledge Discovery, Knowledge Management and Decision Making
Advances in Intelligent Systems Research 51
Eureka-2013 is the fourth international workshop on Knowledge Discovery, Knowledge Management and Decision Support. Eureka-2013 aims to build on the success of the 2011 meeting in Santander, Spain, in bringing together the Knowledge Discovery (KD), Knowledge Management (KM), and Decision Analysis (DA) communities, and will also stimulate a new focus on the application of KD, KM and DA research to support solutions of real problems in government, business, and industry.
Leyva López, J. C., Espin Andrade, R.A., Bello Pérez, R. & Álvarez Carrillo, P.A. (Eds.) (2013). Proceedings of the Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support. Atlantis Press. https://www.atlantis-press.com/proceedings/eureka-13
