C4.5: programs for machine learning
C4.5: programs for machine learning
Foundations of Neuro-Fuzzy Systems
Foundations of Neuro-Fuzzy Systems
BT Technology Journal
Towards real-time business intelligence
BT Technology Journal
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BT's Work Manager platform uses a dynamic scheduler to plan the daily jobs of field engineers. In order to produce reliable schedules, Work Manager requires accurate estimates about the time an engineer spends on travelling from one job location to the next (inter-job time) and how much time is required to complete a job.We have developed a generic platform called Intelligent Travel Time Estimation and Management System (ITEMS) that we have used to derive a specialised version for modelling the behaviour of BT's mobile workforce. This travel time estimation system (TTE) receives job data every night and learns a new estimation model on a daily basis. When a new estimation model significantly differs from the currently used model, the new estimation model is automatically uploaded into Work Manager.The estimation algorithm has been used in a loosely coupled trial for about two years. Currently, we are undertaking trials of TTE — a tightly coupled Web-based system that fully automates the learning and management of estimation models, providing a graphical user interface that displays rich detail about the travel patterns of BT's mobile workforce. During the trial period we have observed that using TTE can quickly improve the accuracy of travel time estimates by up to 10%.