Zobrazeno 1 - 10 of 15 pro vyhledávání: '"Md Fazla Elahe"'
1
Akademický článek
An Explainable AI Approach for the Rapid Diagnosis of COVID-19 Using Ensemble Learning Algorithms
Autor: Houwu Gong, Miye Wang, Hanxue Zhang, Md Fazla Elahe, Min Jin
Publikováno v: Frontiers in Public Health, Vol 10 (2022)
BackgroundArtificial intelligence-based disease prediction models have a greater potential to screen COVID-19 patients than conventional methods. However, their application has been restricted because of their underlying black-box nature.ObjectiveTo
Externí odkaz: https://doaj.org/article/63c1f1130d4b437692dedbad041cd1a9
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2
Akademický článek
An Adaptive and Parallel Forecasting Strategy for Short-Term Power Load Based on Second Learning of Error Trend
Autor: Md Fazla Elahe, Min Jin, Pan Zeng
Publikováno v: IEEE Access, Vol 8, Pp 201889-201899 (2020)
Modeling an accurate forecasting model for short-term load is still challenging due to the diverse causes of load changing and lack of information on many of these causes. In this paper, error trend is used to reveal the trend effect caused by unknow
Externí odkaz: https://doaj.org/article/fa3e96b3d3c34bb295bd3f1886f407b7
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3
A Novel Hybrid Approach for Classifying Osteosarcoma Using Deep Feature Extraction and Multilayer Perceptron
Autor: Moni, Md. Tarek Aziz, S. M. Hasan Mahmud, Md. Fazla Elahe, Hosney Jahan, Md Habibur Rahman, Dip Nandi, Lassaad K. Smirani, Kawsar Ahmed, Francis M. Bui, Mohammad Ali
Publikováno v: Diagnostics; Volume 13; Issue 12; Pages: 2106
Osteosarcoma is the most common type of bone cancer that tends to occur in teenagers and young adults. Due to crowded context, inter-class similarity, inter-class variation, and noise in H&E-stained (hematoxylin and eosin stain) histology tissue, pat
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=multidiscipl::44e24fd3682a68c964d869904359cac3
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5
Factors Impacting Short-Term Load Forecasting of Charging Station to Electric Vehicle
Autor: Azim, Md Fazla Elahe, Md Alamgir Kabir, S. M. Hasan Mahmud, Riasat
Publikováno v: Electronics; Volume 12; Issue 1; Pages: 55
The rapid growth of electric vehicles (EVs) is likely to endanger the current power system. Forecasting the demand for charging stations is one of the critical issues while mitigating challenges caused by the increased penetration of EVs. Uncovering
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=multidiscipl::d4088ded11ac3d72cc39a5cfd341aa81
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8
A Cancer Diagnosis Method Combining miRNA-lncRNA Interaction Pairs and Class Weight Competition
Autor: Wei Zhang, Jun Huang, Hao Nan Chen, Md. Fazla Elahe, Min Jin
Publikováno v: IEEE Access, Vol 8, Pp 67059-67074 (2020)
From the perspective of data science, we propose a cancer diagnosis method combining miRNA-lncRNA interaction pairs and class weight competition. First, miRNA-lncRNA interaction data is introduced into joint expression profiles, and the complex mecha
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ec343eca7b6c327bfbc8d65ce32ef321
https://doi.org/10.1109/access.2020.2985405
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9
Short-Term Power Load Forecasting Based on Cross Multi-Model and Second Decision Mechanism
Autor: Pan Zeng, Md. Fazla Elahe, Min Jin
Publikováno v: IEEE Access, Vol 8, Pp 184061-184072 (2020)
Short-term load forecasting (STLF) plays a vital role in the reliable, secure, and efficient operation of power systems. Since electric load variation results from diverse factors, accurate and stable load forecasting remains a challenging task. To i
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5bc63ed38137b22bc07fa783d7567b44
https://doi.org/10.1109/access.2020.3028649
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