Business processes resource management using rewriting logic and deep-learning-based predictive monitoring

IF 0.7 4区 数学 Q3 COMPUTER SCIENCE, THEORY & METHODS
Francisco Durán , Nicolás Pozas , Camilo Rocha
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引用次数: 0

Abstract

A significant task in business process optimization is concerned with streamlining the allocation and sharing of resources. This paper presents an approach for analyzing business process provisioning under a resource prediction strategy based on deep learning. A timed and probabilistic rewrite theory specification formalizes the semantics of business processes. It is integrated with an external oracle in the form of a long short-term memory neural network that can be queried to predict how traces of the process may advance within a time frame. Comparison of execution time and resource occupancy under different parameters is included for several case studies, as well as details on the construction of the deep learning model and its integration with Maude.

业务流程资源管理使用重写逻辑和基于深度学习的预测监控
业务流程优化中的一项重要任务是简化资源的分配和共享。提出了一种基于深度学习的资源预测策略下的业务流程配置分析方法。定时和概率重写理论规范形式化了业务流程的语义。它以长短期记忆神经网络的形式与外部神谕相结合,可以通过查询来预测过程的痕迹在一个时间框架内可能会如何发展。比较了几个案例在不同参数下的执行时间和资源占用情况,并详细介绍了深度学习模型的构建及其与Maude的集成。
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来源期刊
Journal of Logical and Algebraic Methods in Programming
Journal of Logical and Algebraic Methods in Programming COMPUTER SCIENCE, THEORY & METHODS-LOGIC
CiteScore
2.60
自引率
22.20%
发文量
48
期刊介绍: The Journal of Logical and Algebraic Methods in Programming is an international journal whose aim is to publish high quality, original research papers, survey and review articles, tutorial expositions, and historical studies in the areas of logical and algebraic methods and techniques for guaranteeing correctness and performability of programs and in general of computing systems. All aspects will be covered, especially theory and foundations, implementation issues, and applications involving novel ideas.
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