Predictive Process Model Monitoring using Recurrent Neural Networks

11/05/2020
by   Johannes De Smedt, et al.
0

The field of predictive process monitoring focuses on modelling future characteristics of running business process instances, typically by either predicting the outcome of particular objectives (e.g. completion (time), cost), or next-in-sequence prediction (e.g. what is the next activity to execute). This paper introduces Processes-As-Movies (PAM), a technique that provides a middle ground between these predictive monitoring. It does so by capturing declarative process constraints between activities in various windows of a process execution trace, which represent a declarative process model at subsequent stages of execution. This high-dimensional representation of a process model allows the application of predictive modelling on how such constraints appear and vanish throughout a process' execution. Various recurrent neural network topologies tailored to high-dimensional input are used to model the process model evolution with windows as time steps, including encoder-decoder long short-term memory networks, and convolutional long short-term memory networks. Results show that these topologies are very effective in terms of accuracy and precision to predict a process model's future state, which allows process owners to simultaneously verify what linear temporal logic rules hold in a predicted process window (objective-based), and verify what future execution traces are allowed by all the constraints together (trace-based).

READ FULL TEXT

page 21

page 22

page 23

research
02/24/2022

Can deep neural networks learn process model structure? An assessment framework and analysis

Predictive process monitoring concerns itself with the prediction of ong...
research
12/07/2016

Predictive Business Process Monitoring with LSTM Neural Networks

Predictive business process monitoring methods exploit logs of completed...
research
09/16/2018

Classifying Process Instances Using Recurrent Neural Networks

Process Mining consists of techniques where logs created by operative sy...
research
03/25/2020

Predictive Business Process Monitoring via Generative Adversarial Nets: The Case of Next Event Prediction

Predictive process monitoring aims to predict future characteristics of ...
research
09/17/2018

Learning short-term past as predictor of human behavior in commercial buildings

This paper addresses the question of identifying the time-window in shor...
research
12/31/2016

p-DLA: A Predictive System Model for Onshore Oil and Gas Pipeline Dataset Classification and Monitoring - Part 1

With the rise in militant activity and rogue behaviour in oil and gas re...
research
07/01/2019

Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks

Latent dynamics discovery is challenging in extracting complex dynamics ...

Please sign up or login with your details

Forgot password? Click here to reset