Journal of Ambient Intelligence and Humanized Computing - Call for Papers: Adaptive Computational Intelligence Methods for Handling Big Data of Decision Support Systems in Sustainable Business Models

CLOSED FOR SUBMISSIONS

Decision analysis has been proved to be an excellent operational research direction. After nearly 60 years of development, many multiple criteria decision-making methods that can flexibly handle multi-dimensional and discrete decision-making problems with quantitative or qualitative information have been proposed. By developing complex and dynamic nature of the emerging Internet of Things (IoT) ecosystems and growing requirement for supporting Service Level

Agreements (SLAs), the intelligent systems and applications must actively deliver performance guarantees in Quality of Service (QoS). On the other side, a sustainable business model pattern describes an ecological, social, and/or economic problem on the IoT applications that arises when an organization aims to create value, and it describes the core of a solution based on decision making problems. With the rapid development of the IoT, Decision Support System (DSS) is applied as an attractive solution for the decision-making process of big data and managing the information of IoT ecosystems. DSS for sustainable business models in IoT environments investigates the massive quantity of complex big data to help industry, academicians, medical systems, doctors, and other smart applications. Also, DSS methods have been generalized to adaptive machine learning methods and many applications have been achieved in different areas. On the other hand, the adaptive machine learning is one of the most important breakthroughs in the field of DSS on big data over the last decade. The adaptive machine learning methods on DSS make use of more efficient and powerful prediction and detection methods to improve the process of complex making decisions and prediction for sustainable business models in IoT ecosystems. Despite the importance of decision making on IoT ecosystems, this special issue aims to encourage researchers and practitioners to address challenges associated with adaptive machine learning methods for DSS for sustainable business model in IoT environments. Also, review articles as the state-of-the-art of this topic can be invited for showing recent major advances and discoveries, significant gaps in this special issue.

Topics of Interest
The topics of interest for this SI include, but are not limited to:

Methodologies, and Techniques

• Theoretical topics of fuzzy logic and computing

• Evolutionary Algorithms

• Machine Learning methods

• Neural Networks

• Deep learning

• Fuzzy Graphs

• Knowledge-based algorithms

• Combinatorial fuzzy-evolutionary methods

Applications

• Consumer engagement and communication for DSS in IoT

• DSS for Disease prediction methods in IoT

• Sustainable products and cloud services in IoT

• DSS for supply chain management in IoT applications

• Big data for DSS-based knowledge discovery in IoT

• Intelligent decision-making systems for Computer-aided diagnostic system.

• DSS for sustainable business models in IoT applications.

• Medical Instrumentation and Healthcare Technologies in IoT

• Intelligent approaches on Wireless Body Area Network (WBAN) in big data

• Formal analysis of DSS-based industrial systems in sustainable business models IoT

• Energy prediction on sensor-based DSS systems in sustainable business models

• Security and privacy aspects of DSS in IoT systems.

• Blockchain technology on big data in DSS

• Big data management based on DSS in IoT systems

• Cloud-edge service management in DSS-based IoT systems

• Life cycle sustainability assessment in IoT environment

• Resource discovery and selection based on decision-making methods in IoT systems

The format for the full article submission is available at: https://www.springer.com/journal/12652/submission-guidelines (this opens in a new tab)

GUEST EDITORS

Dr. Muhammad ARIF (Lead Guest Editor)
Associate Professor
The Superior University, Lahore, Pakistan
E-mail: md.arif@superior.edu.pk

Dr. Alessio FERONE
Associate Professor
University of Naples Parthenope, Naples, Italy
E-mail: alessio.ferone@uniparthenope.it

Prof. Dr. Oana GEMAN
Associate Professor
Stefan cel Mare University, Suceava, Romania
E-mail: oana.geman@usm.ro

Prof. Dr. Arfan JAFFAR
Professor
The Superior University, Lahore, Pakistan
E-mail: arfan.jaffar@superior.edu.pk

Prof. Dr. Guojun WANG
Professor
Guangzhou University, Guangzhou, China
E-mail: csgjwang@gzhu.edu.cn