基于微分Petri网的业务流程模块适配方法

Xian-wen FANG,Xiao-yan TAO,Xiang-wei LIU

Acta Electronica Sinica（2017）

Cited 12|Views1

Abstract

为适应业务流程多功能及动态变化的需求,用模块替换的方法对业务流程建模是解决问题的快速有效途径之一.以开放Petri网与微分Petri网为基础,提出了微分控制Petri网和微分数据Petri网的概念,分别从语义学角度利用微分Petri网的演化表达式对模型的控制流网与数据流网进行活性检测,利用微分Petri网对替换模块及其离散部分与连续部分进行结构稳定性分析,以达到业务流程模块适配分析.理论分析结果表明,所建立的微分表达式能够反映模型活性与稳定性,模块适配效果较好.最后基于平台数据进行仿真分析,实验结果表明本文所提的方法有一定的可行性.

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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