RTFN: A robust temporal feature network for time series classification
Time series data usually contains local and global patterns. Most of the existing feature
networks focus on local features rather than the relationships among them. The latter is also …
networks focus on local features rather than the relationships among them. The latter is also …
[HTML][HTML] Predicting energy consumption in residential buildings using advanced machine learning algorithms
F Dinmohammadi, Y Han, M Shafiee - Energies, 2023 - mdpi.com
The share of residential building energy consumption in global energy consumption has
rapidly increased after the COVID-19 crisis. The accurate prediction of energy consumption …
rapidly increased after the COVID-19 crisis. The accurate prediction of energy consumption …
[HTML][HTML] Wind turbine data analysis and LSTM-based prediction in SCADA system
I Delgado, M Fahim - Energies, 2020 - mdpi.com
The number of wind farms is increasing every year because many countries are turning their
attention to renewable energy sources. Wind turbines are considered one of the best …
attention to renewable energy sources. Wind turbines are considered one of the best …
Evaluating time series encoding techniques for predictive maintenance
Predictive Maintenance has become an important component in modern industrial
scenarios, as a way to minimize down-times and fault rate for different equipment. In this …
scenarios, as a way to minimize down-times and fault rate for different equipment. In this …
Regularizing autoencoders with wavelet transform for sequence anomaly detection
Nowadays, systems or entities are usually monitored by devices, generating large amounts
of time series. Detecting anomalies in them help prevent potential losses, thus arousing …
of time series. Detecting anomalies in them help prevent potential losses, thus arousing …
[HTML][HTML] Developing a deep neural network with fuzzy wavelets and integrating an inline PSO to predict energy consumption patterns in urban buildings
Energy has been one of the most important topics of political and social discussion in recent
decades. A significant proportion of the country's revenues is derived from energy resources …
decades. A significant proportion of the country's revenues is derived from energy resources …
[HTML][HTML] Electricity theft detection based on hybrid random forest and weighted support vector data description
Q Cai, P Li, R Wang - International Journal of Electrical Power & Energy …, 2023 - Elsevier
Improving the detection rate of electricity theft users in smart grids is crucial to the safe
operation of the power system and the economic efficiency of the grid. The traditional …
operation of the power system and the economic efficiency of the grid. The traditional …
Energy-efficiency oriented occupancy space optimization in buildings: A data-driven approach based on multi-sensor fusion considering behavior-environment …
Y Zhou, Y Wang, C Li, L Ding, Z Yang - Energy, 2024 - Elsevier
Buildings contribute significantly to global energy consumption. Optimizing internal building
space layout is an essential approach for reducing energy consumption. However …
space layout is an essential approach for reducing energy consumption. However …
Smart energy management: Energy consumption metering, monitoring and prediction for mining industry
With the evolution of technology, and the well-known concept of industry 4.0 and digitization,
the energy is and always be an important factor in every field, and must follow up with the …
the energy is and always be an important factor in every field, and must follow up with the …
Efficient time series clustering by minimizing dynamic time warping utilization
Dynamic Time Warping (DTW) is a widely used distance measurement in time series
clustering. DTW distance is invariant to time series phase perturbations but has a quadratic …
clustering. DTW distance is invariant to time series phase perturbations but has a quadratic …