Methods and Techniques of Electricity Thieving in Pakistan

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Journal of Power and Energy Engineering

ISSN Print: 2327-588X
ISSN Online: 2327-5901
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"Methods and Techniques of Electricity Thieving in Pakistan"
written by Zahoor Hussain, Shahzad Memon, Razahussain Shah, Zulﬁqar Ali Bhutto, Mahmoud Aljawarneh,
published by Journal of Power and Energy Engineering, Vol.4 No.9, 2016

has been cited by the following article(s):

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[13]	A PLSTM, AlexNet and ESNN Based Ensemble Learning Model for Detecting Electricity Theft in Smart Grids
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[14]	A data-driven approach to reduce electricity theft in developing countries
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[15]	Big data analytics for identifying electricity theft using machine learning approaches in microgrids for smart communities
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[16]	Urban governance and electricity losses: An exploration of spatial unevenness in Karachi, Pakistan
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[17]	Smart Energy Meter System Design & Simulation Presenting Electricity Theft Methods, Detection and Protection
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[18]	Implementation of Smart Grid Technologies in Pakistan under CPEC Project: Technical and Policy Implications
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[19]	Employing Machine Learning and Deep Learning Models for Electricity Theft Detection in Smart Grids
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[20]	An Android Based Smart System to Control and Monitor Home Appliances Using Arduino Microcontroller
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[26]	An Approach to Energy Economy In Household Environment Using Smart System (SSFEE)
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[27]	On Demand Electrical Power Load Management Service for Smart Meters Using Gsm Technology
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[28]	Energy production system optimization: Evidence from Pakistan
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[30]	Technical Losses Ratio: Analysis of Electric Power Transmission and Distribution Network
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[33]	TYPE AND NATURE OF ELECTRICITY THEFT: A CASE STUDY OF GHANA
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[4]	Future Prospective of Smart Meters, Net Metering and Electricity Market for Power Distribution companies in Pakistan 2023 4th International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), 2023 DOI:10.1109/iCoMET57998.2023.10099361

[5]	AlexNet, AdaBoost and Artificial Bee Colony Based Hybrid Model for Electricity Theft Detection in Smart Grids IEEE Access, 2022 DOI:10.1109/ACCESS.2022.3150016

[6]	Risk assessment and mitigation for electric power sectors: A developing country's perspective International Journal of Critical Infrastructure Protection, 2022 DOI:10.1016/j.ijcip.2021.100507

[7]	Towards Efficient Energy Utilization Using Big Data Analytics in Smart Cities for Electricity Theft Detection Big Data Research, 2022 DOI:10.1016/j.bdr.2021.100285

[8]	Towards Efficient Energy Utilization Using Big Data Analytics in Smart Cities for Electricity Theft Detection Big Data Research, 2022 DOI:10.1016/j.bdr.2021.100285

[9]	Risk assessment and mitigation for electric power sectors: A developing country's perspective International Journal of Critical Infrastructure Protection, 2022 DOI:10.1016/j.ijcip.2021.100507

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[11]	AlexNet, AdaBoost and Artificial Bee Colony Based Hybrid Model for Electricity Theft Detection in Smart Grids IEEE Access, 2022 DOI:10.1109/ACCESS.2022.3150016

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[14]	Towards Efficient Energy Utilization Using Big Data Analytics in Smart Cities for Electricity Theft Detection Big Data Research, 2022 DOI:10.1016/j.bdr.2021.100285

[15]	Application of Machine Learning Algorithm in Managing Deviant Consumer Behaviors and Enhancing Public Service. Journal of Global Information Management, 2021 DOI:10.4018/JGIM.292064

[16]	Application of Machine Learning Algorithm in Managing Deviant Consumer Behaviors and Enhancing Public Service. Journal of Global Information Management, 2021 DOI:10.4018/JGIM.292064

[17]	Urban governance and electricity losses: An exploration of spatial unevenness in Karachi, Pakistan Energy Research & Social Science, 2021 DOI:10.1016/j.erss.2021.102166

[18]	Implementation of Smart Grid Technologies in Pakistan under CPEC Project: Technical and Policy Implications IEEE Access, 2021 DOI:10.1109/ACCESS.2021.3074338

[19]	Smart Energy Meter System Design & Simulation Presenting Electricity Theft Methods, Detection and Protection 2021 IEEE 1st International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering MI-STA, 2021 DOI:10.1109/MI-STA52233.2021.9464447

[20]	Big data analytics for identifying electricity theft using machine learning approaches in microgrids for smart communities Concurrency and Computation: Practice and Experience, 2021 DOI:10.1002/cpe.6316

[21]	Modelling Residential-Scale Consumer Demographics using Monthly Electricity Consumption Data 2021 IEEE Electrical Power and Energy Conference (EPEC), 2021 DOI:10.1109/EPEC52095.2021.9621651

[22]	A data-driven approach to reduce electricity theft in developing countries Utilities Policy, 2021 DOI:10.1016/j.jup.2021.101304

[23]	A PLSTM, AlexNet and ESNN Based Ensemble Learning Model for Detecting Electricity Theft in Smart Grids IEEE Access, 2021 DOI:10.1109/ACCESS.2021.3134754

[24]	A data-driven approach to reduce electricity theft in developing countries Utilities Policy, 2021 DOI:10.1016/j.jup.2021.101304

[25]	A voted based random forests algorithm for smart grid distribution network faults prediction Enterprise Information Systems, 2020 DOI:10.1080/17517575.2019.1600724

[26]	Performance Analysis of Different Types of Machine Learning Classifiers for Non-Technical Loss Detection IEEE Access, 2020 DOI:10.1109/ACCESS.2019.2962510

[27]	Impact of Feature Selection on Non-technical Loss Detection 2020 6th Conference on Data Science and Machine Learning Applications (CDMA), 2020 DOI:10.1109/CDMA47397.2020.00009

[28]	LSTM and Bat-Based RUSBoost Approach for Electricity Theft Detection Applied Sciences, 2020 DOI:10.3390/app10124378

[29]	A voted based random forests algorithm for smart grid distribution network faults prediction Enterprise Information Systems, 2019 DOI:10.1080/17517575.2019.1600724

[30]	Energy production system optimization: Evidence from Pakistan Renewable and Sustainable Energy Reviews, 2018 DOI:10.1016/j.rser.2017.09.089

[31]	An Estimation of the Impact of Uninterpretable Power Supply Systems on Electricity Distribution Utility of Pakistan Journal of Basic & Applied Sciences, 2018 DOI:10.6000/1927-5129.2018.14.13

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