Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Computers in Industry - Special issue: Process/workflow mining
iBOM: A Platform for Intelligent Business Operation Management
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Application of dynamic diffusion theory in foreign direct investment of Taiwan IC industry in China
International Journal of Computational Science and Engineering
SPDW+: a seamless approach for capturing quality metrics in software development environments
Software Quality Control
Business process performance prediction on a tracked simulation model
Proceedings of the 3rd International Workshop on Principles of Engineering Service-Oriented Systems
Expert Systems with Applications: An International Journal
Hi-index | 0.00 |
The ability to forecast metrics and performance indicators for business operations is crucial to proactively avoid abnormal situations, and to do effective business planning. However, expertise is typically required to drive each step of the prediction process. This is impractical when there are thousands of metrics to monitor. Fortunately, for business operations management, extreme accuracy is not required. It is usually enough to know when a metric is likely to go beyond the normal range of values. This gives opportunity for automation. In this paper, we present an engine that completely automates the prediction of metrics to support a better management of business operations.