ABSTRACT
This paper aims to build CEOntoIAS, a cloud-based active multi-agent system based on the cloud environment WIAS, develop the cloud-based energy data mining agent system OntoDMA, as based on Big Data analysis technology, and proactively provide appropriate, real-time, and fast domain information prediction. On one hand, the related technologies for constructing web service platforms are shared; on the other hand, how to integrate and support the cloud interaction paradigm handled by the data mining agent system widely and seamlessly through these technologies is explored. In order to outline the feasibility of this system architecture, a case study is conducted on the energy saving information system, and the relevant R&D results are presented in detail. Then, the preliminary system R&D interface and experimental verification are illustrated. Finally, the cache performance of the Solutions Pool is increased by 19.82% and the query workload of the Prediction Rules is reduced by 66.51%, which relieves the workload on the back-end servo system.
