Special Issue "Computational Intelligence, Soft Computing and Communication Networks for Applied Science"
Deadline for manuscript submissions: 20 April 2020.
Prof. Dr. Jason K. Levy
Disaster Preparedness and Emergency Management, University of Hawaii, Kapolei, HI 96707, USA
Website | E-Mail
Interests: disaster risk governance; sustainable hazard mitigation; stochastic and statistical hydrology; sociohydrology; fluvial and marine disasters; global climate change, computational intelligence for water management; hydrologic resilience; process-based modeling of coupled human–water systems; inundation; economics of water resources management; drought
Based on their ability to capture the uncertainty, complexity, and stochastic nature of the underlying physical and sociopolitical processes, recent advances in artificial and computational intelligence have transformed the modeling and management of healthcare, environmental systems, and many fields in the applied sciences. Computational intelligence and soft computing approaches not only process large amounts of information historical data and/or data acquired via interaction with the environment but also continually learn through the consequences of action–result combinations. All aspects of communication systems and networks and computational intelligence will be considered in this Special Issue. Artificial intelligence and soft computing paradigms often leverage nature-inspired computational methodologies, including artificial neural networks (ANNs), fuzzy sets, and evolutionary algorithms (EA), including genetic algorithms (EA/GAs) and their hybridizations, such as neuro-fuzzy computing and neo-fuzzy systems. These systems have produced valuable, timely, robust, high-quality, and human-competitive results that have contributed to artificial intelligence research breakthroughs ranging from deep learning to genetic programming. Powerful computational intelligence and soft computing paradigms have recently been uncovered in numerous branches of soft systems science, including neural networks, swarm intelligence, expert systems, evolutionary computing, fuzzy systems, and artificial immune systems.
Prof. Dr. Jason K. Levy
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Soft, mobile cloud-based computing for social networks
- Data mining and big data analytics for applied science and engineering
- Fuzzy system theory in health and environmental applications
- Socioenvironmental data analytical approaches using computational methods
- Deep learning and machine learning algorithms for industrial applications
- Intelligent techniques for smart surveillance and security in public health systems
- Crowd computing-assisted access control and digital rights management
- Evolutionary algorithms for data analysis and recommendations
- Crowd intelligence and computing paradigms
- Computer vision and image processing and pattern recognition technologies healthcare
- Parallel and distributed computing for smart healthcare services
- Autonomous systems and industrial processes optimization
- Extreme and intelligent manufacturing
- Wireless and optical communications and networking
- Parallel and distributed computing
- Cloud computing and networks
- Networked control systems and information security
- Speech/image/video processing and communications
- Green computing and Internet of Things