Rakibul Hassan
Rajshahi University of Engineering & Technology
18 Papers
5 Citations
Rakibul Hassan is an academic researcher from Rajshahi University of Engineering & Technology. The author has contributed to research in topics: Computer science & Renewable energy. The author has an hindex of 3, co-authored 9 publications.
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Papers
Techno-economic and environmental assessment of a hybrid renewable energy system using multi-objective genetic algorithm: A case study for remote Island in Bangladesh
Barun K. Das,Rakibul Hassan,Mohammad Shahed Hasan Khan Tushar,Forhad Zaman,Mahmudul Hasan,Pronob Das +5 more
TL;DR: The analyzed results indicate that the intelligent techniques are the superior to the hybrid optimisation of multiple energy resources software tool in terms of costs and environmental point of view.
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Techno-economic optimisation of stand-alone hybrid renewable energy systems for concurrently meeting electric and heating demand
TL;DR: In this article, the authors investigated the optimisation of hybrid renewable energy system using the excess energy generated by its own sources to satisfy the electric and thermal loads for a remote community.
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Integrated off-grid hybrid renewable energy system optimization based on economic, environmental, and social factors for sustainable development
TL;DR: In this paper , a hybrid renewable energy system comprising solar photovoltaic (PV), wind turbine (WT), micro-hydro turbine (MHT), biogas generator (BG) and vanadium redox flow (VRF) battery is proposed to meet the community load demand varying in the range of 951-1526 kWh/day in a remote rural part of Bangladesh.
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Investigation of a modified double slope solar still integrated with nanoparticle-mixed phase change materials: Energy, exergy, exergo-economic, environmental, and sustainability analyses
TL;DR: In this article , the combined effect of unique modifications of internal sidewall reflector (ISR), hollow circular fin (HCF), phase change material (PCM), and nanoparticle mixed PCM (nano-PCM) on the thermodynamic performance of double slope solar stills was investigated.
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A Novel Method for Multivariant Pneumonia Classification Based on Hybrid CNN-PCA Based Feature Extraction Using Extreme Learning Machine With CXR Images
Md. Nahiduzzaman,Md. Omaer Faruq Goni,Md. Shamim Anower,Md. Robiul Islam,Mominul Ahsan,Julfikar Haider,Saravanakumar Gurusamy,Rakibul Hassan,Md. Rakibul Islam +8 more
TL;DR: In this article, an automatic pneumonia detection system has been proposed by applying the extreme learning machine (ELM) on the Kaggle CXR images (Pneumonia).