Managing the air cargo offload problems using rough set theory

Azuraliza Abu Bakar, Zalinda Othman, Ruhaizan Ismail, Rosmawati Muhamad Abdullah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper focuses on the development of knowledge model for a prediction of air cargo offload. A knowledge model is a model containing a set of knowledge via rules that has been obtained from mining certain amount of data. These rules might help the management in major decision making such as setting up new strategy. In this study, an intelligent technique for data mining called a rough set theory was used for the knowledge modelling. Rough set technique has been used based on its capability of handling uncertain data often occurs in the real world problem. As a result, a rough classifier was produced and has been used for offload prediction in four travelling sectors. A total of 267 data were obtained from a Malaysian air cargo company. There were eight attributes used as input and one attribute as an output. Data has been through a pre-processing stage to facilitate the requirement of the modelling process. A total of ten experiments using ten sets of different data have been conducted. The best model was selected from the total models generated from the experiment. The model has given a promising result with 100% accuracy. The rules obtained have contributing to offload problem knowledge but need further investigation for more comprehensive knowledge decision model.

Original languageEnglish
Title of host publicationProceedings of the 2009 International Conference on Electrical Engineering and Informatics, ICEEI 2009
Pages1-6
Number of pages6
Volume1
DOIs
Publication statusPublished - 2009
Event2009 International Conference on Electrical Engineering and Informatics, ICEEI 2009 - Selangor
Duration: 5 Aug 20097 Aug 2009

Other

Other2009 International Conference on Electrical Engineering and Informatics, ICEEI 2009
CitySelangor
Period5/8/097/8/09

Fingerprint

Rough set theory
Air
Data mining
Classifiers
Decision making
Experiments
Processing
Industry

Keywords

  • Air cargo offloads
  • Data mining
  • Reduct
  • Rough set

ASJC Scopus subject areas

  • Information Systems
  • Software
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

Cite this

Abu Bakar, A., Othman, Z., Ismail, R., & Abdullah, R. M. (2009). Managing the air cargo offload problems using rough set theory. In Proceedings of the 2009 International Conference on Electrical Engineering and Informatics, ICEEI 2009 (Vol. 1, pp. 1-6). [5254828] https://doi.org/10.1109/ICEEI.2009.5254828

Managing the air cargo offload problems using rough set theory. / Abu Bakar, Azuraliza; Othman, Zalinda; Ismail, Ruhaizan; Abdullah, Rosmawati Muhamad.

Proceedings of the 2009 International Conference on Electrical Engineering and Informatics, ICEEI 2009. Vol. 1 2009. p. 1-6 5254828.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abu Bakar, A, Othman, Z, Ismail, R & Abdullah, RM 2009, Managing the air cargo offload problems using rough set theory. in Proceedings of the 2009 International Conference on Electrical Engineering and Informatics, ICEEI 2009. vol. 1, 5254828, pp. 1-6, 2009 International Conference on Electrical Engineering and Informatics, ICEEI 2009, Selangor, 5/8/09. https://doi.org/10.1109/ICEEI.2009.5254828
Abu Bakar A, Othman Z, Ismail R, Abdullah RM. Managing the air cargo offload problems using rough set theory. In Proceedings of the 2009 International Conference on Electrical Engineering and Informatics, ICEEI 2009. Vol. 1. 2009. p. 1-6. 5254828 https://doi.org/10.1109/ICEEI.2009.5254828
Abu Bakar, Azuraliza ; Othman, Zalinda ; Ismail, Ruhaizan ; Abdullah, Rosmawati Muhamad. / Managing the air cargo offload problems using rough set theory. Proceedings of the 2009 International Conference on Electrical Engineering and Informatics, ICEEI 2009. Vol. 1 2009. pp. 1-6
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