Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Future Generation Computer Systems
Data mining: concepts and techniques
Data mining: concepts and techniques
Soft Computing and Intelligent Systems: Theory and Applications
Soft Computing and Intelligent Systems: Theory and Applications
Formation of an ant cemetery: swarm intelligence or statistical accident?
Future Generation Computer Systems - Cellular automata CA 2000 and ACRI 2000
Analysis on a Mobile Agent-Based Algorithm for Network Routing and Management
IEEE Transactions on Parallel and Distributed Systems
An agent-based approach to identification of prediction models
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
A novel approach for multi-agent-based Intelligent Manufacturing System
Information Sciences: an International Journal
| Hi-index | 0.07 |
This paper presents an agent-based approach to the identification of prediction models for continuous values from multi-dimensional data, both numerical and categorical. A simple description of the approach is: a number of agents are sent to the investigated data space; at the micro-level, each agent tries to build a local linear model with multi-linear regressions by competing with others; then at the macro-level all surviving agents build a global model by introducing membership functions. Three tests were carried out and the performance of the approach was compared with that of a neural network. The results of the three tests show that the agent-based approach can achieve good performance for some data sets. The approach complements rather than competes with other Soft Computing methods.