WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394

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Author: search.filters.author.Faheem, MuhammadScopus Q: search.filters.scopusQuartile.N/A

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  • Conference Object
    Citation - WoS: 30
    Citation - Scopus: 38
    Software Defined Communication Framework for Smart Grid to Meet Energy Demands in Smart Cities
    (IEEE, 2019-04) Faheem, Muhammad; Umar, Muhammad; Butt, Rizwan Aslam; Raza, Basit; Ngadi, Md. Asri; Gungor, Vehbi Cagri
    In smart cities, the electricity is an essential component since it preserves a certain level of residents' life quality and provisions the entire spectrum of their economic activities. Thus, a smart way is essential to develop cities without disregarding energy issues. In this scope, the smart grid paradigm offers power supply in an efficient, sustainable and economical manner with minimal impact on the environment and can meet the future energy demands. However, real-time monitoring and control of the smart grid (SG) for continuous and quality-aware power supply in smart cities (SCs) is challenging and requires an advanced quality of service (QoS)-aware communication framework. In this context, this research aims to present a novel data-gathering scheme by using the Internet of software-defined mobile sinks (SDMSs) and wireless sensor networks (WSNs) in the smart grid. The extensive simulation results conducted through the EstiNet9.0 indicate that the designed scheme outperforms existing approaches and achieves its defined goals for events-drive applications in the SG.
  • Conference Object
    Citation - Scopus: 3
    A Hybrid Adaptive Neuro-Fuzzy Inference System (Anfis) Approach for Professional Bloggers Classification
    (IEEE, 2019-11) Asim, Yousra; Raza, Basit; Malik, Ahmad Kamran; Shahid, Ahmad R.; Faheem, Muhammad; Kumar, Yogan Jaya
    Despite their small numbers, some users of the online social networks demonstrate the ability to influence others. Bloggers are one of such kind of users that through their ideas and opinions on different topics, influence other users. Their identification may be beneficial for several purposes, such as online marketing for products. Much effort has been expanded towards finding the impact of such bloggers within the blogging community. We have expanded on their work by identifying influential bloggers using labeled data. We have improved upon the accuracy of the classification of professional and non-professional bloggers. We have made use of Adaptive Neuro-Fuzzy Inference System (ANFIS), and the Fuzzy Inference System (FIS) models. Their performance has been gauged and compared with the existing techniques and approaches, such as an Artificial Neural Network (ANN), Alternating Decision Tree (ADTree) algorithm, and Classification Based on Associations (CBA) algorithm. Adaptive techniques (ANFIS and ANN) are found better than the aforementioned rule-based classifiers. The FIS model outperformed the CBA algorithm, but showed similar performance to the ADTree algorithm. Our proposed ANFIS model showed improved results in terms of performance measures with 93% accuracy for blogger classification.