Research on Synchronization Mechanism of Artificial Intelli-gence Model Based on Belief Measure and Its Application in Pumped Storage Power Station

For the security monitoring of pumped storage power station, a model synchroniza-tion mechanism for cloud edge cooperation framework is proposed. The method uses the belief function to describe the threshold and uses the ping-pong operation strategy to update the model alternately, which solves the problem of artificial intelligence model synchronization and update of edge equipment. The cloud is based on Baidu BML platform, the edge uses customized servers, and the average model update cycle is about three months.

Avoiding unnecessary information loss: correct and efficient model synchronization based on triple graph grammars

Model synchronization, i.e., the task of restoring consistency between two interrelated models after a model change, is a challenging task. Triple graph grammars (TGGs) specify model consistency by means of rules that describe how to create consistent pairs of models. These rules can be used to automatically derive further rules, which describe how to propagate changes from one model to the other or how to change one model in such a way that propagation is guaranteed to be possible. Restricting model synchronization to these derived rules, however, may lead to unnecessary deletion and recreation of model elements during change propagation. This is inefficient and may cause unnecessary information loss, i.e., when deleted elements contain information that is not represented in the second model, this information cannot be recovered easily. Short-cut rules have recently been developed to avoid unnecessary information loss by reusing existing model elements. In this paper, we show how to automatically derive (short-cut) repair rules from short-cut rules to propagate changes such that information loss is avoided and model synchronization is accelerated. The key ingredients of our rule-based model synchronization process are these repair rules and an incremental pattern matcher informing about suitable applications of them. We prove the termination and the correctness of this synchronization process and discuss its completeness. As a proof of concept, we have implemented this synchronization process in eMoflon, a state-of-the-art model transformation tool with inherent support of bidirectionality. Our evaluation shows that repair processes based on (short-cut) repair rules have considerably decreased information loss and improved performance compared to former model synchronization processes based on TGGs.

Towards Model Synchronization for Consistency Management of Mechatronic Systems

The development of a mechatronic system involves different designers having various viewpoints on the overall system to handle its complexity. Consequently, multiple models are created from a variety of domains such as mechanical, electronic, and software engineering. These models use different formalisms, modeling languages, and tools to address specific concerns. The major challenge of this approach is to identify and solve any potential inconsistency between models in order to minimize costs and development time before the verification and validation phases. This paper proposes a new collaborative methodology to maintain consistency between different engineering disciplines at an early stage of the development cycle of mechatronic systems based on Model-Based Engineering (MBE). We apply a model synchronization approach to actively check for model consistency in a continuous way during the multidisciplinary design process. As a novel contribution of this paper, we demonstrate how model transformation techniques can be employed; firstly, to abstract various engineering models in a common formalism based on graph theory and, secondly, to update models with appropriate changes evaluated by a project manager. We also show how to detect the differences automatically, and we discuss where designer decisions are essential.