H
Hadi Saboohi
Researcher at Information Technology University
Publications - 32
Citations - 778
Hadi Saboohi is an academic researcher from Information Technology University. The author has contributed to research in topics: Web service & Service (business). The author has an hindex of 13, co-authored 31 publications receiving 667 citations. Previous affiliations of Hadi Saboohi include Islamic Azad University & University of Malaya.
Papers
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On Density-Based Data Streams Clustering Algorithms: A Survey
TL;DR: This paper summarizes the main density-based clustering algorithms on data streams, discusses their uniqueness and limitations, but also explains how they address the challenges in clustering data streams and investigates the evaluation metrics used in validating cluster quality and measuring algorithms’ performance.
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Potential of radial basis function-based support vector regression for apple disease detection
Elham Omrani,Benyamin Khoshnevisan,Shahaboddin Shamshirband,Hadi Saboohi,Nor Badrul Anuar,Mohd Hairul Nizam Md Nasir +5 more
TL;DR: In this article, three apple diseases appearing on leaves, namely Alternaria, apple black spot, and apple leaf miner pest were selected for detection via image processing technique, and three soft-computing approaches for disease classification, of artificial neural networks (ANNs), and support vector machines (SVMs).
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A comparative study between fuzzy linear regression and support vector regression for global solar radiation prediction in Iran
TL;DR: The experimental results show that it is possible to achieve enhanced predictive accuracy and capability of generalization via the proposed approach and that SVR_rbf performed well in predicting GSR compared with FLR.
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MuDi-Stream
TL;DR: The proposed MuDi-Stream algorithm improves clustering quality in multi-density environments and is evaluated on various synthetic and real-world datasets using different quality metrics and further, scalability results are compared.
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An appraisal of wind speed distribution prediction by soft computing methodologies: A comparative study
Dalibor Petković,Shahaboddin Shamshirband,Shahaboddin Shamshirband,Nor Badrul Anuar,Hadi Saboohi,Ainuddin Wahid Abdul Wahab,Milan Protić,Erfan Zalnezhad,Seyed Mohammad Amin Mirhashemi +8 more
TL;DR: Enhanced predictive accuracy and capability of generalization can be achieved using the SVR approach compared to other soft computing methodologies.