Fast Ant Colony Optimization for Clustering
نویسندگان
چکیده
منابع مشابه
Constrained Ant Colony Optimization for Data Clustering
Processes that simulate natural phenomena have successfully been applied to a number of problems for which no simple mathematical solution is known or is practicable. Such meta-heuristic algorithms include genetic algorithms, particle swarm optimization and ant colony systems and have received increasing attention in recent years. This paper extends ant colony systems and discusses a novel data...
متن کاملAn Ant-Colony Optimization Clustering Model for Cellular Automata Routing in Wireless Sensor Networks
High efficient routing is an important issue for the design of wireless sensor network (WSN) protocols to meet the severe hardware and resource constraints. This paper presents an inclusive evolutionary reinforcement method. The proposed approach is a combination of Cellular Automata (CA) and Ant Colony Optimization (ACO) techniques in order to create collision-free trajectories for every agent...
متن کاملAnt Colony Optimization based clustering methodology
In this work we consider spatial clustering problem with no a priori information. The number of clusters is unknown, and clusters may have arbitrary shapes and density differences. The proposed clustering methodology addresses several challenges of the clustering problem including solution evaluation, neighborhood construction, and data set reduction. In this context, we first introduce two obj...
متن کاملAn Efficient Ant Colony Optimization Clustering Algorithm
This paper presents a new algorithm for clustering which is called an “efficient ant colony optimization clustering algorithm” (EACOC) based on a classic algorithm “LF algorithm”. We have proved the algorithm efficiency when dealt with a big variety of different data as well as providing high quality and converging speed simultaneously. This is considered as the outcome of many changes we have ...
متن کاملClustering social networks using ant colony optimization
Several e-marketing applications rely on the ability to understand the structure of social networks. Social networks can be represented as graphs with customers as nodes and their interactions as edges. Most real world social networks are known to contain extremely dense subgraphs (also called as communities) which often provide critical insights about the emergent properties of the social netw...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Indonesian Journal of Electrical Engineering and Computer Science
سال: 2018
ISSN: 2502-4760,2502-4752
DOI: 10.11591/ijeecs.v12.i1.pp78-86