Research of Fuzzy Neural Network Model Based on Quantum Clustering

Abstract

Fuzzy neural network can handle non-linear, complex data, but the structure of model determination is an important and difficult issues identified. More complete results can be made .in a short period of time by the optimization network model. To address this issue, this paper presents the fusion of a quantum clustering algorithm and fuzzy c-means clustering algorithm, the fuzzy neural network structure is carried out at different levels data processing. Through the model of mining in complex industrial process, the validity of the model is tested.

Quantum Optimization and Quantum Learning: A Survey

“…Fuzzy neural network is able to handle non-linear and complex data, but the structure of model determination is a difficult yet important issue to be identified. [164] presents the fusion of fuzzy C-Means clustering method and QC, and the structure of the network is carried out at different levels. Also, in [165], the quantum state machine equips random fuzzy membership input with the fuzzy C-Means soft clustering algorithm to deal with remotely sensed multi-band image segmentation.…”