Title: Development for granular computing-based multi-agent system for data fusion process

Authors: Bin Ma; Nannan Li; Kuan Huang; Changtao Wang; Zhonghua Han; Jie Han

Addresses: Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China ' Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China ' Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China ' Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China ' Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China ' Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang 110168, China

Abstract: In data fusion systems, the characteristics of the information from the sensors include diversity, complexity and uncertainty. In this paper, the data fusion of the granular computing-based multi-layer structure is studied. Neural network and fuzzy system are adopted for the inference mechanism to construct an equivalent fuzzy logic system. Neural network clustering is used to cluster the concept lattices with different formal contexts. And in each concept lattice, fuzzy clustering is used to cluster the formal contexts. The design of the data fusion middleware in the multi-agent system (MAS) enables the two-step data fusion. This design is used to solve the issues caused by the imprecise, incomplete, fuzzy or contradictory inference. Simulation results on the fire detection in the intelligent building environment show the effectiveness and the feasibility of this design.

Keywords: granular computing; multi-agent systems; MAS; agent-based systems; fuzzy logic; neural networks; middleware; data fusion; fuzzy clustering; simulation; fire detection; intelligent buildings.

DOI: 10.1504/IJCAT.2013.058354

International Journal of Computer Applications in Technology, 2013 Vol.48 No.4, pp.321 - 329

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 18 Dec 2013 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article