Sukarna Barua, Md. Monirul Islam, Xin Yao, Kazuyuki Murase
Imbalanced learning problems contain an unequal distribution of data samples among different classes and pose a challenge to any classifier as it becomes hard to learn the minority class samples. Synthetic oversampling methods address this problem by generating the synthetic minority class samples t...
Md. Nazmul Hasan, Rafia Nishat Toma, Abdullah-Al Nahid, M. M. Manjurul Islam et al.
Among an electricity provider’s non-technical losses, electricity theft has the most severe and dangerous effects. Fraudulent electricity consumption decreases the supply quality, increases generation load, causes legitimate consumers to pay excessive electricity bills, and affects the overall econo...
Khan Md. Hasib, Md. Sadiq Iqbal, Faisal Muhammad Shah, Jubayer Al Mahmud et al.
The problem of class imbalance is extensive for focusing on numerous applications in the real world. In such a situation, nearly all of the examples are labeled as one class called majority class, while far fewer examples are labeled as the other class usually, the more important class is called min...
Noor Mohammad, Avijit Barua, Muhammad Abdullah Arafat
Power utilities in different countries especially in the developing ones are incurring huge losses due to electricity theft. This paper proposes a prepaid energy metering system to control electricity theft. In this system a smart energy meter is installed in every consumer unit and a server is main...
Sukarna Barua, Md. Monirul Islam, Kazuyuki Murase
Sukarna Barua, Md. Monirul Islam, Kazuyuki Murase
Farshid Rayhan, Sajid Ahmed, Asif Mahbub, Rafsan Jani et al.
Class imbalance classification is a demanding research problem in the context of machine learning and its applications, as most of the real-life datasets are often imbalanced in nature. Existing learning algorithms maximise the classification accuracy by correctly classifying the majority class, but...
Md. Nazrul Islam Siddique, Md Shafiullah, Saad Mekhilef, H. R. Pota et al.
Accurate fault detection and localization play a pivotal role in the reliable and optimal operation of electric power distribution networks. However, the integration of intermittent distributed generation (DG) brings distinctive challenges to traditional fault diagnosis schemes, requiring more robus...
M. Mejbaul Haque, Kamal Hossain, Md. Mortuza Ali, Md. Rafiqul Islam Sheikh
This paper presents a single phase digital prepaid energy meter based on two microcontrollers and a single phase energy meter IC. This digital prepaid energy meter does not have any rotating parts. The energy consumption is calculated using the output pulses of the energy meter chip and the internal...
Mahbub Ul Islam Khan, M Ilius Pathan, Mohammad Mominur Rahman, Md. Maidul Islam et al.
Electric vehicles (EVs) are commonly recognized as environmentally friendly modes of transportation. They function by converting electrical energy into mechanical energy using different types of motors, which aligns with the sustainable principles embraced by smart cities. The motors of EVs store an...
Sajid Ahmed, Asif Mahbub, Farshid Rayhan, Rafsan Jani et al.
Class imbalance classification has become a dominant problem in supervised learning. The bias of majority class instances dominates in quantity over minority class instances in imbalanced datasets, which produce the suboptimal classification results for classifying the minority class instances. In t...
Mimusa Azim Mim, Nazia Majadi, Peal Mazumder
With the advancement of e-commerce and modern technological development, credit cards are widely used for both online and offline purchases, which has increased the number of daily fraudulent transactions. Many organizations and financial institutions worldwide lose billions of dollars annually beca...
Abrar Mahi-al-rashid, Fahmid Hossain, Adnan Anwar, Sami Azam
Supervisory Control and Data Acquisition (SCADA) systems are essential for reliable communication and control of smart grids. However, in the cyber-physical realm, it becomes highly vulnerable to cyber-attacks like False Data Injection (FDI) into the measurement signal which can circumvent the conve...
Khan Md. Hasib, Nurul Akter Towhid, Md Rafiqul Islam
Imbalanced data presents many difficulties, as the majority of learners will be prejudice against the majority class, and in severe cases, may fully disregard the minority class. Over the last few decades, class inequality has been extensively researched using traditional machine learning techniques...
Saiful Islam, Umme Sara, Abu Kawsar, Anichur Rahman et al.
A real world big dataset with disproportionate classification is called imbalance dataset which badly impacts the predictive result of machine learning classification algorithms. Most of the datasets faces the class imbalance problem in machine learning. Most of the algorithms in machine learning wo...