S
Simon Fong
Researcher at University of Macau
Publications - 527
Citations - 8593
Simon Fong is an academic researcher from University of Macau. The author has contributed to research in topics: Data stream mining & Metaheuristic. The author has an hindex of 37, co-authored 523 publications receiving 6161 citations. Previous affiliations of Simon Fong include Nanyang Technological University & La Trobe University.
Papers
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Proceedings ArticleDOI
DBSCAN: Past, present and future
TL;DR: Different variations of DBSCAN algorithms that were proposed so far are surveyed and critically evaluated and their limitations are also listed.
Journal ArticleDOI
Artificial intelligence in cancer diagnosis and prognosis: Opportunities and challenges
TL;DR: How AI assists cancer diagnosis and prognosis is explored, specifically with regard to its unprecedented accuracy, which is even higher than that of general statistical applications in oncology.
Book ChapterDOI
An Application of Oversampling, Undersampling, Bagging and Boosting in Handling Imbalanced Datasets
Bee Wah Yap,Khatijahhusna Abd Rani,Hezlin Aryani Abd Rahman,Simon Fong,Zuraida Khairudin,Nik Nairan Abdullah +5 more
TL;DR: Oversampling and undersampling are found to work well in improving the classification for the imbalanced dataset using decision tree, while boosting and bagging did not improve the Decision Tree performance.
Journal ArticleDOI
Developing residential wireless sensor networks for ECG healthcare monitoring
TL;DR: The paper concludes that such mass-market health monitoring systems will only be prevalent when implemented together with home environmental monitoring and control systems.
Book ChapterDOI
Accelerated Particle Swarm Optimization and Support Vector Machine for Business Optimization and Applications
TL;DR: In this article, a combination of a recently developed Accelerated PSO and a nonlinear support vector machine (SVM) is used for solving business optimization problems, and the proposed SVM is applied to production optimization, and then used for income prediction and project scheduling.