Decision Support Systems for Industrial and Scientific Applications

This book explores the latest progress in intelligent systems designed to assist decision-making, revealing how advanced computers contribute to informed judgments. The authors show how these intelligent systems utilize cutting-edge technologies such as artificial intelligence, machine learning, and deep learning to comprehend and interpret data. The book illustrates successful applications of these systems to improve decision support in various industries, including business, finance, and healthcare. Essentially, the book focuses on the evolving role of technology in improving decision-making. The book offers a diverse collection of articles written by experts in the field, presenting a wide range of perspectives and approaches to intelligent systems for decision support. Readers can benefit from insights into various applications, methodologies, and success stories, providing a comprehensive understanding of the topic.

List of contents

Introduction.- Anomaly Detection in Smart Manufacturing Using an Intelligent Decision Support System with Applications in Supply Chain Management.- Lung and colon cancer detection system in histopathological images based on deep transfer Learning.- Design of an application to support the diagnosis of skin cancer using deep learning.- Enhancing Vascular Structure from Computed Tomography Angiography Images using Score-based Generative Models.- Remote medical assistance y wearable devices in health applications.- Product Demand Forecasting in the Industry 4.0 through machine learning and Intelligent Decision Support Systems.- Application of the Sugeno-Takagi-Kang considering fuzzy logic for demand forecasting in the supply chain: a Fuzzy temporary series forecast model (FTS) proposal.- Optimizing a Smart City's Urban Park Lighting using Monkey Algorithm.- Intelligent System for Multimedia Data Analysis in Industry 4.0 using a Smart color management approach.- Technologies for Vehicle Classification in Intelligent Traffic Systems: Advances, Challenges, and Perspectives.- Conclusion.

About the author

Dr. Nishu Gupta is a Senior Member, IEEE and presently working as a Research Scientist as the VTT Technical Research Centre of Finland Ltd, located in Oulu, Finland. Before this position, he was a Postdoctoral Fellow in the Smart Wireless Systems Group, Department of Electronic Systems, Faculty of Information Technology and Electrical Engineering, at Norwegian University of Science and Technology (NTNU) in Gjøvik, Norway. He has worked as Research Associate in the Smart Living Lab, a joint project of The Swiss Federal Institute of Technology Lausanne (EPFL), School of Engineering and Architecture of Fribourg (HEIA-FR), and University of Fribourg (UniFR) in the Digitalization and Information Systems Research Group, Department of Informatics, University of Fribourg, Switzerland. Prior to this position, he was a Postdoctoral Fellow in the Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University in Rabigh, Saudi Arabia. He is also a visiting researcher at the University of Oviedo, Gijón, Spain under the research group on Systems for Multimedia and the Internet of Things (SMIOT). He served as a Member, Zero Trust Architecture working group of MeitY-C-DAC-STQC project under ‘e-Governance Standards and Guidelines’, Ministry of Electronics and Information Technology (MeitY), Government of India. He is the winner of the International Travel grant awarded by the journal Electronics, MDPI for the year 2022. Nishu received his Ph.D. degree in 2016 from the Department of Electronics and Communication Engineering, MNNIT Allahabad, Prayagraj, India which is an Institute of National Importance as declared by the Government of India. He is specialized in the field of Computer Communication and Networking. His major work is in the area of IoT based enhanced safety applications in vehicular communication. He received his Master’s degree (M.Tech.) from Delhi Technological University, Delhi, India (formerly Delhi College of Engineering) and Bachelor’s degree (B.Tech.) from BBDNITM Lucknow, affiliated to U.P. Technical University, Lucknow, India. His research interests include Vehicular Communication, Driving Behaviour Analysis, Autonomous Vehicles, Intelligent Transportation, Smart Cities, Security in Sensor Networks and Internet of Things and Internet of Vehicles.
José David Díaz Román obtained his title as an electronic engineer from the Polytechnic Institute of the National Armed Forces in Maracay, Venezuela, in 1997. He furthered his academic pursuits and earned a Doctorate in Engineering from the Simón Bolívar University in Caracas, Venezuela. From 1998 to 2016, José was an integral part of the Electromedicine-Biomedical Engineering Program at the Francisco de Miranda National Experimental University in Coro, Venezuela. Since 2016, he has served as a full-time professor in the Biomedical Engineering Program. Additionally, he is actively involved in the academic cores of the Master's programs in Electrical Engineering and the Doctorate in Advanced Engineering Sciences at the Department of Electrical and Computer Engineering of the Autonomous University of Ciudad Juárez, Chihuahua, Mexico. José Díaz Román holds a membership in the National System of Researchers in Mexico and has a recognized publication record. He has contributed to prestigious journals and books, presenting papers and book chapters. His research interests encompass digital signal and image processing, the modeling of artificial intelligence systems (Machine Learning and Deep Learning) for classification, segmentation, and prediction tasks, as well as electronic and biomedical instrumentation, and wireless sensor networks.

Summary

This book explores the latest progress in intelligent systems designed to assist decision-making, revealing how advanced computers contribute to informed judgments. The authors show how these intelligent systems utilize cutting-edge technologies such as artificial intelligence, machine learning, and deep learning to comprehend and interpret data. The book illustrates successful applications of these systems to improve decision support in various industries, including business, finance, and healthcare. Essentially, the book focuses on the evolving role of technology in improving decision-making. The book offers a diverse collection of articles written by experts in the field, presenting a wide range of perspectives and approaches to intelligent systems for decision support. Readers can benefit from insights into various applications, methodologies, and success stories, providing a comprehensive understanding of the topic.

Product details

• Assisted by: David Diaz Roman (Editor), Jose David Diaz Roman (Editor), Nishu Gupta (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Hardback
• Release: 10.09.2025
• EAN: 9783031896996
• ISBN: 978-3-0-3189699-6
• No. of pages: 240
• Illustrations: X, 240 p.
• Series: Signals and Communication Technology
• Subjects: Natural sciences, medicine, IT, technology > Technology > Electronics, electrical engineering, communications engineering; Unternehmensforschung, Künstliche Intelligenz, Artificial Intelligence, Management: Entscheidungstheorie, Operations Research and Decision Theory, data analysis, decision support, Communications Engineering, Networks, Intelligent Systems, decision support systems, Decision-Making Technologies, Artificial Intelligence, Machine Learning, Deep Learning