Novel nonlinear fractional order Parkinson's disease model for brain electrical activity rhythms: Intelligent adaptive Bayesian networks
In this study, a novel investigation in developing intelligent adaptive Bayesian networks
(IABN) is carried out to solve the fractional order Parkinson's disease model (FOPDM) …
(IABN) is carried out to solve the fractional order Parkinson's disease model (FOPDM) …
Design of intelligent neuro-supervised networks for brain electrical activity rhythms of Parkinson's disease model
The objective of this paper is to present a novel design of intelligent neuro-supervised
networks (INSNs) in order to study the dynamics of a mathematical model for Parkinson's …
networks (INSNs) in order to study the dynamics of a mathematical model for Parkinson's …
Electricity Theft Detection Based on Temporal Convolutional Networks with Self-Attention
The issue of Non-Technical Losses (NTL) is a major concern for power systems, as it results
in significant revenue loss for electric utility companies and has a negative impact on the …
in significant revenue loss for electric utility companies and has a negative impact on the …
Dam safety evaluation method after extreme load condition based on health monitoring and deep learning
J Song, Y Liu, J Yang - Sensors, 2023 - mdpi.com
The safety operation of dams after extreme load is an important frontier research topic in the
field of dam engineering. The dam health monitoring provides a reliable data basis for a …
field of dam engineering. The dam health monitoring provides a reliable data basis for a …
Mitigating Class Imbalance Issues in Electricity Theft Detection via a Sample-Weighted Loss
Recent advances in neural networks have significantly improved electricity theft detection,
achieving higher detection accuracy compared to earlier methods (eg, support vector …
achieving higher detection accuracy compared to earlier methods (eg, support vector …
[HTML][HTML] A WOA-CNN-BiLSTM-based multi-feature classification prediction model for smart grid financial markets
G Ni, X Zhang, X Ni, X Cheng, X Meng - Frontiers in Energy Research, 2023 - frontiersin.org
Introduction: Smart grid financial market forecasting is an important topic in deep learning.
The traditional LSTM network is widely used in time series forecasting because of its ability …
The traditional LSTM network is widely used in time series forecasting because of its ability …
Artificial intelligence-based power market price prediction in smart renewable energy systems: Combining prophet and transformer models
C Huang, T Zhao, D Huang, B Cen, Q Zhou, W Chen - Heliyon, 2024 - cell.com
With the increasing integration of smart renewable energy systems and power electronic
converters, electricity market price prediction is particularly important. It is not only crucial for …
converters, electricity market price prediction is particularly important. It is not only crucial for …
Electricity Theft Detection for Smart Homes: Harnessing the Power of Machine Learning With Real and Synthetic Attacks
Electricity theft is a pervasive issue with economic implications that necessitate innovative
approaches for its detection, given the critical challenge of limited labeled data. However …
approaches for its detection, given the critical challenge of limited labeled data. However …
Machine intelligence aware electricity theft detection for smart metering applications
Electricity theft detection (ETD) is a serious issue and needs proper attention to investigate
and detect the fraudulent consumers. Fraudulent consumers steal electricity and …
and detect the fraudulent consumers. Fraudulent consumers steal electricity and …
Electricity theft detection in IoT-based smart grids using a parameter-tuned bidirectional LSTM with pre-trained feature learning mechanism
M Krishnamoorthy, JR Albert - Electrical Engineering, 2024 - Springer
The most significant issue today is electricity theft (ET) which causes much loss to electricity
boards. The development of smart grids (SGs) is crucial for ET detection (ETD) because …
boards. The development of smart grids (SGs) is crucial for ET detection (ETD) because …