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Shahaboddin Shamshirband
Researcher at Ton Duc Thang University
Publications - 408
Citations - 18037
Shahaboddin Shamshirband is an academic researcher from Ton Duc Thang University. The author has contributed to research in topics: Adaptive neuro fuzzy inference system & Wind speed. The author has an hindex of 58, co-authored 404 publications receiving 13207 citations. Previous affiliations of Shahaboddin Shamshirband include Information Technology University & Islamic Azad University of Mashhad.
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Performance Evaluation of Supervised Machine Learning Techniques for Efficient Detection of Emotions from Online Content
Muhammad Zubair Asghar,Fazli Subhan,Muhammad A. Imran,Fazal Masud Kundi,Shahaboddin Shamshirband,Amir Mosavi,Peter Csiba,Annamária R. Várkonyi-Kóczy +7 more
TL;DR: The experimental results show the performance of different machine learning classifiers in terms of different evaluation metrics like precision, recall, and a classifier with the best performance is recommended for the emotion classification.
Journal ArticleDOI
Soft-Computing Methodologies for Precipitation Estimation: A Case Study
Shahaboddin Shamshirband,Milan Gocic,Dalibor Petković,Hadi Saboohi,Tutut Herawan,Miss Laiha Mat Kiah,Shatirah Akib +6 more
TL;DR: Enhanced predictive accuracy and capability of generalization can be achieved with the ANFIS approach compared to SVR estimation, and the simulation results verify the effectiveness of the proposed optimization strategies.
Journal ArticleDOI
Generalized adaptive neuro-fuzzy based method for wind speed distribution prediction
TL;DR: In this paper, an adaptive neuro-fuzzy inference system (ANFIS) was used to predict the annual probability density distribution of wind speed, which is a specific type of the ANN family.
Journal ArticleDOI
Software SMEs' unofficial readiness for CMMI®-based software process improvement
Javed Iqbal,Rodina Ahmad,Mohd Hairul Nizam Md Nasir,Mahmood Niazi,Shahaboddin Shamshirband,Muhammad Asim Noor +5 more
TL;DR: The results of the study show that a large segment of software development SMEs informally follows the specific practices of CMMI level 2 process areas and thus has true potential for rapid and effective CMMI-based SPI.
Journal ArticleDOI
Sensitivity analysis of the discharge coefficient of a modified triangular side weir by adaptive neuro-fuzzy methodology
TL;DR: In this article, the Adaptive Neuro-Fuzzy Inference System (ANFIS) was applied for the selection of the most prominent triangular side weir discharge coefficient parameters based on ten input parameters.