Ensembles of Collaborative Neural Networks

人工神经网络已成功地用于数据挖掘和控制。神经网络集成（NNE）是一组具有自组织、可塑性和自适应行为的网络。本研究的目的是开发一个有效的和理论上合理的算法NNE学习。该项目的成果将包括深入了解复杂NNE的自组织和自动问题分解以及构建和训练NNE的有效算法。实际成果将包括为早期职业研究人员提供研究培训，以及为数据挖掘、机器人和多智能体系统提供新的建模工具。该项目有助于智能信息使用的国家优先领域。

Artificial neural networks have been used successfully for data mining and control. A neural network ensemble(NNE) is a collection of networks that exhibits properties of self-organization, plasticity, and adaptive behaviour. The aim of this research is to develop an efficient and theoretically sound algorithm for NNE learning. The outcomes of the project will include insights into self-organization of complex NNE and automatic problem decomposition and an efficient algorithm for constructing and training NNE. Practical outcomes will include research training for early career researchers and new modelling tools for data mining, robotics and multi-agent systems. The project contributes to the national priority area of smart information use.