A nearest neighbour extension to project duration forecasting with artificial intelligence

DOI10.1016/j.ejor.2016.11.018zbMath1403.68247OpenAlexW2554894595MaRDI QIDQ1751933

Mathieu Wauters, Mario Vanhoucke

Publication date: 25 May 2018

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2016.11.018

zbMATH Keywords

predictionartificial intelligenceproject managementearned value management (EVM)

Mathematics Subject Classification ID

Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Uses Software

• R
• e1071
• gbm
• C4.5
• RanGen
• FNN

Cites Work

• Unnamed Item
• Greedy function approximation: A gradient boosting machine.
• Bagging predictors
• Bankruptcy prediction in banks and firms via statistical and intelligent techniques -- a review
• Forecasting with cue information: a comparison of multiple regression with alternative forecasting approaches
• Measuring time. Improving project performance using earned value management
• Optimal timing of project control points
• Principal component analysis.
• Support-vector networks
• An evaluation of the adequacy of project network generators with systematically sampled networks
• Rangen: A random network generator for activity-on-the-node networks
• Developing activity duration specification limits for effective project control
• Critical-Path Planning and Scheduling: Mathematical Basis
• A simulation and evaluation of earned value metrics to forecast the project duration
• Nearest neighbor pattern classification
• Problems in the Analysis of Survey Data, and a Proposal

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