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RISS 인기검색어
- 검색키워드
- 저자 : Muhammad Arslan Raza (검색결과 2 건)
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Using Support Vector Machine to Predict Political Affiliations on Twitter: Machine Learning approach
Muhammad Javed,Kiran Hanif,Arslan Ali Raza,Syeda Maryum Batool,Syed Muhammad Ali Haider International Journal of Computer ScienceNetwork S 2024 International journal of computer science and netw Vol.24 No.5
The current study aimed to evaluate the effectiveness of using Support Vector Machine (SVM) for political affiliation classification. The system was designed to analyze the political tweets collected from Twitter and classify them as positive, negative, and neutral. The performance analysis of the SVM classifier was based on the calculation of metrics such as accuracy, precision, recall, and f1-score. The results showed that the classifier had high accuracy and f1-score, indicating its effectiveness in classifying the political tweets. The implementation of SVM in this study is based on the principle of Structural Risk Minimization (SRM), which endeavors to identify the maximum margin hyperplane between two classes of data. The results indicate that SVM can be a reliable classification approach for the analysis of political affiliations, possessing the capability to accurately categorize both linear and non-linear information using linear, polynomial or radial basis kernels. This paper provides a comprehensive overview of using SVM for political affiliation analysis and highlights the importance of using accurate classification methods in the field of political analysis.
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Fe/Co doped ZIF derived nitrogen doped nanoporous carbon as electrode material for supercapacitors
Ifra Fiaz Gul,Hirra Anwar,Muhammad Arslan Raza,Rabia Ahmad,Naseem Iqbal,Ghulam Ali 한국공업화학회 2022 Journal of Industrial and Engineering Chemistry Vol.116 No.-
Nanoporous carbon (NPC) for electrochemical energy storage devices has gained much interest due to itshigh specific area and tunable porosity. Herein, Fe and Co co-doped NPC is synthesized by a simple coprecipitationmethod followed by carbonization of Fe and Co doped ZIF8 at 900 ℃ (Fe-Co/NPC-900). The structural, morphological, elemental, chemical bonding, surface area, and thermal degradation ofthe synthesized material have been evaluated using X-ray diffraction, scanning electron microscopy,energy dispersive spectroscopy, X-ray photoelectron spectroscopy, Brunauer–Emmett–Teller method,and thermogravimetric analysis, respectively. The high surface area of 933 m2/g and nanoporous structureof Fe-Co/NPC-900 electrode results in a high specific capacitance of 900 F/g at a current density of5 A/g. The cycle performance of Fe-Co/NPC-900 was remarkable with 88% of the capacitance retentionafter 5000 cycles at a high current density of 30 A/g. The high electrochemical performance of Fe-Co/NPC-900 is attributed to the hybrid doping of Fe and Co in nitrogen doped carbon network which offersa synergic effect in reaction.
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