Journal Menu► ▼ Journal Menu
Journal Browser► ▼ Journal Browser
Special Issue "Clustering Algorithms"
A special issue of Algorithms (ISSN 1999-4893).
Deadline for manuscript submissions: closed (15 August 2015).
OPTIMA Area, Tecnalia Research & Innovation, 48160 Zamudio, Bizkaia, Spain
Interests: machine learning; meta-heuristic optimization; predictive analytics; resource allocation; wireless network design; cognitive radio; risk contention; logistics; clustering
Special Issues and Collections in MDPI journals
Special Issue in Algorithms: Novel Meta-heuristic Approaches and Their Applications to Preemptive Operational Planning and Logistics in Disaster Management
Special Issue in Algorithms: Data Analytics and Optimization for Hybrid Communication Systems
Special Issue in Algorithms: Selected Papers from the 3rd International Conference on the Harmony Search Algorithm (ICHSA 2017)
The last decade has witnessed an upsurge of new clustering algorithms based on innovative technical approaches beyond those traditionally addressed in the data mining community. While the principles and fundamentals of distance and similarity prevail underneath these new schemes, their pattern search procedures are radically different from previous approaches: among them, evolutionary (and in general, bio-inspired) meta-heuristics have emerged as computationally efficient search engines that can be exploited, so as to find similarity patterns among massive datasets.
This Special Issue invites prospective researchers and practitioners in this field to submit their latest developments and/or surveys of the state of the art concerning the following topics:
- Evolutionary computing for clustering
- Meta-heuristically empowered pattern discovery
- Applications of clustering when hybridized with meta-heuristics
- Other combinations of meta-heuristics and machine learning (e.g., predictive analytics)
Proposals on other related topics will also be considered via a previous query.
Javier (Javi) Del Ser Lorente
- Meta-heuristically empowered clustering schemes
- Meta-heuristics (evolutionary computing, swarm intelligence, etc.) for machine learning