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Data science and big data analytics: a systematic review of methodologies used in the supply chain and logistics research
Data science and big data analytics (DS &BDA) methodologies and tools are used
extensively in supply chains and logistics (SC &L). However, the existing insights are …
extensively in supply chains and logistics (SC &L). However, the existing insights are …
Outcome-oriented predictive process monitoring: Review and benchmark
Predictive business process monitoring refers to the act of making predictions about the
future state of ongoing cases of a business process, based on their incomplete execution …
future state of ongoing cases of a business process, based on their incomplete execution …
Predictive business process monitoring with LSTM neural networks
Predictive business process monitoring methods exploit logs of completed cases of a
process in order to make predictions about running cases thereof. Existing methods in this …
process in order to make predictions about running cases thereof. Existing methods in this …
[HTML][HTML] Utilizing machine learning on freight transportation and logistics applications: A review
This review article explores and locates the current state-of-the-art related to application
areas from freight transportation, supply chain and logistics that focuses on arrival time …
areas from freight transportation, supply chain and logistics that focuses on arrival time …
Predictive monitoring of business processes: a survey
Nowadays, process mining is becoming a growing area of interest in business process
management (BPM). Process mining consists in the extraction of information from the event …
management (BPM). Process mining consists in the extraction of information from the event …
Machine learning in business process monitoring: a comparison of deep learning and classical approaches used for outcome prediction
Predictive process monitoring aims at forecasting the behavior, performance, and outcomes
of business processes at runtime. It helps identify problems before they occur and re …
of business processes at runtime. It helps identify problems before they occur and re …
Predictive process monitoring methods: Which one suits me best?
Predictive process monitoring has recently gained traction in academia and is maturing also
in companies. However, with the growing body of research, it might be daunting for data …
in companies. However, with the growing body of research, it might be daunting for data …
Survey and cross-benchmark comparison of remaining time prediction methods in business process monitoring
Predictive business process monitoring methods exploit historical process execution logs to
generate predictions about running instances (called cases) of a business process, such as …
generate predictions about running instances (called cases) of a business process, such as …
Impact of big data on supply chain management
This study focuses on big data, which offer new opportunities, added value and operational
excellence for existing supply chain practices. A survey was conducted among employees of …
excellence for existing supply chain practices. A survey was conducted among employees of …
Clustering-based predictive process monitoring
The enactment of business processes is generally supported by information systems that
record data about each process execution (aka case). This data can be analyzed via a …
record data about each process execution (aka case). This data can be analyzed via a …