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Keyword: Recurrent Neural Network (RNN)
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Open AccessArticle
8 Pages, 954 KB Download PDF

Smart Meter Data Analysis for Electricity Theft Detection using Neural Networks

Advances in Science, Technology and Engineering Systems Journal, Volume 4, Issue 4, Page # 161–168, 2019; DOI: 10.25046/aj040420
Abstract:

The major problem in electric utility is Electrical Theft, which is harmful to electric power suppliers and causes economic loss. Detecting and controlling electrical theft is a challenging task that involves several aspects like economic, social, regional, managerial, political, infrastructural, literacy rate, etc. Numerous methods were proposed formerly for detecting electricity theft. However, the previous…

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(This article belongs to the SP7 (Special Issue on Advancement in Engineering and Computer Science 2019) & Section Electronic Engineering (EEE))
Open AccessArticle
9 Pages, 767 KB Download PDF

Advanced Fall Analysis for Elderly Monitoring Using Feature Fusion and CNN-LSTM: A Multi-Camera Approach

Advances in Science, Technology and Engineering Systems Journal, Volume 9, Issue 6, Page # 12–20, 2024; DOI: 10.25046/aj090602
Abstract:

As society ages, the imbalance between family caregivers and elderly individuals increases, leading to inadequate support for seniors in many regions. This situation has ignited interest in automatic health monitoring systems, particularly in fall detection, due to the significant health risks that falls pose to older adults. This research presents a vision-based fall detection system…

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(This article belongs to the SP17 (Special Issue on Innovation in Computing, Engineering Science & Technology 2024-25) & Section Artificial Intelligence in Computer Science (CAI))
Open AccessArticle
11 Pages, 1,647 KB Download PDF

An Ensemble of Voting- based Deep Learning Models with Regularization Functions for Sleep Stage Classification

Advances in Science, Technology and Engineering Systems Journal, Volume 8, Issue 1, Page # 84–94, 2023; DOI: 10.25046/aj080110
Abstract:

Sleep stage performs a vital role in people’s daily lives in the detection of sleep-related diseases. Conventional automated sleep stage classifier models are not efficient due to the complexity linked to the design of mathematical models and extraction of hand-engineering features. Further, quick oscillations amongst sleep stages frequently lead to indistinct feature extraction, which might…

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(This article belongs to Section Biomedical Engineering (EBI))
Open AccessArticle
7 Pages, 2,135 KB Download PDF

Deep Learning based Models for Solar Energy Prediction

Advances in Science, Technology and Engineering Systems Journal, Volume 6, Issue 1, Page # 349–355, 2021; DOI: 10.25046/aj060140
Abstract:

Solar energy becomes widely used in the global power grid. Therefore, enhancing the accuracy of solar energy predictions is essential for the efficient planning, managing and operating of power systems. To minimize the negatives impacts of photovoltaics on electricity and energy systems, an approach to highly accurate and advanced forecasting is urgently needed. In this…

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(This article belongs to the SP10 (Special Issue on Multidisciplinary Sciences and Engineering 2020-21) & Section Electrical Engineering (ELE))
Open AccessArticle
9 Pages, 1,005 KB Download PDF

Differential Evolution based Hyperparameters Tuned Deep Learning Models for Disease Diagnosis and Classification

Advances in Science, Technology and Engineering Systems Journal, Volume 5, Issue 5, Page # 253–261, 2020; DOI: 10.25046/aj050531
Abstract:

With recent advancements in medical filed, the quantity of healthcare care data is increasing at a faster rate. Medical data classification is considered as a major research topic and numerous research works have been already existed in the literature. Presently, deep learning (DL) models offers an efficient method for developing a dedicated model to determine…

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(This article belongs to the SP9 (Special Issue on Multidisciplinary Innovation in Engineering Science & Technology 2020) & Section Bioinformatics (BIF))

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