NILM applications: Literature review of learning approaches, recent developments and challenges
This paper presents a critical approach to the non-intrusive load monitoring (NILM) problem,
by thoroughly reviewing the experimental framework of both legacy and state-of-the-art …
by thoroughly reviewing the experimental framework of both legacy and state-of-the-art …
Review on deep neural networks applied to low-frequency nilm
P Huber, A Calatroni, A Rumsch, A Paice - Energies, 2021 - mdpi.com
This paper reviews non-intrusive load monitoring (NILM) approaches that employ deep
neural networks to disaggregate appliances from low frequency data, ie, data with sampling …
neural networks to disaggregate appliances from low frequency data, ie, data with sampling …
Non-intrusive load disaggregation based on composite deep long short-term memory network
M Xia, K Wang, W Song, C Chen, Y Li - Expert Systems with Applications, 2020 - Elsevier
Non-invasive load monitoring (NILM) is a vital step to realize the smart grid. Although the
existing various NILM algorithms have made significant progress in energy consumption …
existing various NILM algorithms have made significant progress in energy consumption …
Sequence to point learning based on bidirectional dilated residual network for non-intrusive load monitoring
Abstract Non-Intrusive Load Monitoring (NILM) or Energy Disaggregation, seeks to save
energy by decomposing corresponding appliances power reading from an aggregate power …
energy by decomposing corresponding appliances power reading from an aggregate power …
Water areas segmentation from remote sensing images using a separable residual segnet network
Changes on lakes and rivers are of great significance for the study of global climate change.
Accurate segmentation of lakes and rivers is critical to the study of their changes. However …
Accurate segmentation of lakes and rivers is critical to the study of their changes. However …
Step-wise multi-grained augmented gradient boosting decision trees for credit scoring
W Liu, H Fan, M Xia - Engineering Applications of Artificial Intelligence, 2021 - Elsevier
Credit scoring is an important financial tool for banks to determine whether to issue the loan
to potential borrowers. Ensemble algorithms, which mainly can be divided into bagging …
to potential borrowers. Ensemble algorithms, which mainly can be divided into bagging …
Sequence-to-point learning based on temporal convolutional networks for nonintrusive load monitoring
W Yang, C Pang, J Huang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Nonintrusive load monitoring (NILM) is performed by monitoring the total electricity
consumption data from the customer's meter and decomposing it with a load decomposition …
consumption data from the customer's meter and decomposing it with a load decomposition …
Multi-grained and multi-layered gradient boosting decision tree for credit scoring
W Liu, H Fan, M Xia - Applied Intelligence, 2022 - Springer
Credit scoring is an important process for banks and financial institutions to manage credit
risk. Tree-based ensemble algorithms have made promising progress in credit scoring …
risk. Tree-based ensemble algorithms have made promising progress in credit scoring …
Lightweight non-intrusive load monitoring employing pruned sequence-to-point learning
J Barber, H Cuayáhuitl, M Zhong, W Luan - Proceedings of the 5th …, 2020 - dl.acm.org
Non-intrusive load monitoring (NILM) is the process in which a household's total power
consumption is used to determine the power consumption of household appliances …
consumption is used to determine the power consumption of household appliances …
A marine object detection algorithm based on SSD and feature enhancement
K Hu, F Lu, M Lu, Z Deng, Y Liu - Complexity, 2020 - Wiley Online Library
Autonomous detection and fishing by underwater robots will be the main way to obtain
aquatic products in the future; sea urchins are the main research object of aquatic product …
aquatic products in the future; sea urchins are the main research object of aquatic product …