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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Domain Fusion CNN-LSTM for Short-Term Power Consumption Forecasting
Xiaorui Shao, Pu Chen, Yuxin Zhang, et al.
IEEE Access (2020) Vol. 8, pp. 188352-188362
Open Access | Times Cited: 54

Showing 26-50 of 54 citing articles:

Deep learning-based power consumption and generation forecasting for demand side management
S Abhiram Thejus, P. Sivraj
2021 Second International Conference on Electronics and Sustainable Communication Systems (ICESC) (2021), pp. 1350-1357
Closed Access | Times Cited: 13
Deep Learning with Dipper Throated Optimization Algorithm for Energy Consumption Forecasting in Smart Households
Abdelaziz A. Abdelhamid, El-Sayed M. El-kenawy, Fadwa Alrowais, et al.
Energies (2022) Vol. 15, Iss. 23, pp. 9125-9125
Open Access | Times Cited: 9
Application of CNN-LSTM Algorithm for PM2.5 Concentration Forecasting in the Beijing-Tianjin-Hebei Metropolitan Area
Yuxuan Su, Junyu Li, Lilong Liu, et al.
Atmosphere (2023) Vol. 14, Iss. 9, pp. 1392-1392
Open Access | Times Cited: 5
A Novel Hybrid Model for the Prediction and Classification of Rolling Bearing Condition
Aina Wang, Yingshun Li, Yao Zhao, et al.
Applied Sciences (2022) Vol. 12, Iss. 8, pp. 3854-3854
Open Access | Times Cited: 8
Multi-Task Learning and Temporal-Fusion-Transformer-Based Forecasting of Building Power Consumption
Wenxian Ji, Zeyu Cao, Xiaorun Li
Electronics (2023) Vol. 12, Iss. 22, pp. 4656-4656
Open Access | Times Cited: 4
Long-Term Forecasting Using MAMTF: A Matrix Attention Model Based on the Time and Frequency Domains
Kaixin Guo, Xin Yu
Applied Sciences (2024) Vol. 14, Iss. 7, pp. 2893-2893
Open Access | Times Cited: 1
PConvLSTM: an effective parallel ConvLSTM-based model for short-term electricity load forecasting
Nilakanta Kshetrimayum, Khumukcham Robindro Singh, Nazrul Hoque
International Journal of Data Science and Analytics (2024)
Open Access | Times Cited: 1
Self-Supervised Long-Short Term Memory Network for Solving Complex Job Shop Scheduling Problem
Xiaorui Shao, Chang H. Kim
KSII Transactions on Internet and Information Systems (2021) Vol. 15, Iss. 8
Open Access | Times Cited: 10
Deep learning-based load forecasting considering data reshaping using MATLAB\Simulink
Zhalla Hamad, Ismael Abdulrahman
International journal of energy and environmental engineering (2022) Vol. 13, Iss. 2, pp. 853-869
Closed Access | Times Cited: 6
A hybrid model of CNN-BiLSTM and XGBoost for HVAC systems energy consumption prediction
Heng Luo, Xiangshun Li
2022 4th International Conference on Industrial Artificial Intelligence (IAI) (2023)
Closed Access | Times Cited: 3
Developing a Long Short-Term Memory-Based Model for Forecasting the Daily Energy Consumption of Heating, Ventilation, and Air Conditioning Systems in Buildings
Luis Mendoza, Huriviades Calderón, José Manuel Gómez Pulido, et al.
Applied Sciences (2021) Vol. 11, Iss. 15, pp. 6722-6722
Open Access | Times Cited: 6
Probabilistic Forecasting of Residential Energy Consumption Based on SWT-QRTCN-ADSC-NLSTM Model
Ning Jin, Linlin Song, Gabriel Jing Huang, et al.
Information (2023) Vol. 14, Iss. 4, pp. 231-231
Open Access | Times Cited: 2
Use of Convolutional Neural Networks and Long Short-Term Memory for Accurate Residential Energy Prediction
Hafiz Al-Alami, Hani Jamleh
2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT) (2023), pp. 294-299
Closed Access | Times Cited: 2
An Adaptive Job Shop Scheduler Using Multilevel Convolutional Neural Network and Iterative Local Search
Xiaorui Shao, Chang Soo Kim
IEEE Access (2022) Vol. 10, pp. 88079-88092
Open Access | Times Cited: 4
Short-Term Load Forecasting Based on Wavelet Transform and Chaotic Bat Optimization Algorithm-Long Short-Term Memory Neural Network
Bin Ding, Fan Wang, Zhenhua Chen, et al.
Journal of Nanoelectronics and Optoelectronics (2022) Vol. 17, Iss. 12, pp. 1611-1615
Closed Access | Times Cited: 4
Hybrid Deep Network Based Multi-Source Sensing Data Fusion for FDIA Detection in Smart Grid
Yi Wu, Sheng Yang, Naiwang Guo, et al.
(2022), pp. 310-315
Closed Access | Times Cited: 4
Balancing of Motor Armature Based on LSTM-ZPF Signal Processing
Ruiwen Dong, Mengxuan Li, Ao Sun, et al.
Sensors (2022) Vol. 22, Iss. 23, pp. 9043-9043
Open Access | Times Cited: 3
Short-Term Load Forecasting with an Ensemble Model Using Densely Residual Block and Bi-LSTM Based on the Attention Mechanism
Wenhao Chen, Guangjie Han, Hongbo Zhu, et al.
Sustainability (2022) Vol. 14, Iss. 24, pp. 16433-16433
Open Access | Times Cited: 3
A Novel Multi-Objective Hybrid Evolutionary-Based Approach for Tuning Machine Learning Models in Short-Term Power Consumption Forecasting
Aleksei Vakhnin, Ivan Ryzhikov, Harri Niska, et al.
AI (2024) Vol. 5, Iss. 4, pp. 2461-2496
Open Access
Anomaly Detection in IoT Sensor Energy Consumption Using LSTM Neural Networks and Isolation Forest
Quoc Bao Vo, Philippe Ea, Selma Benzouaoua, et al.
(2024), pp. 1-8
Closed Access
A Comparative Analysis of Deep Neural Network-Based Models for Short-Term Load Forecasting
Nilakanta Kshetrimayum, Khumukcham Robindro Singh, Nazrul Hoque
Lecture notes in networks and systems (2023), pp. 195-214
Closed Access | Times Cited: 1
Smart Prediction Models for Energy Efficiency in Smart Residential Buildings: A Deep Learning Approach
A. Vasantharaj, M. Irshad Ahamed, K. V. Prema, et al.
(2023), pp. 343-348
Closed Access | Times Cited: 1
Highly Accurate Short-Term Gas Consumption and Elapsed Time Forecasting Using Multi-Channel Deep Neural Network
Yeonjee Choi, Xiaorui Shao, Hyun Suk Hwang
IEEE Access (2021) Vol. 9, pp. 157447-157457
Open Access | Times Cited: 3
Minimalistic LSTM Models for Next Day Hourly Residential HVAC Energy Usage Forecasting
Rahman Heidarykiany, Cristinel Ababei
(2022)
Closed Access | Times Cited: 2
A State-of-the-Art Review of Time Series Forecasting Using Deep Learning Approaches
Radhika Chandrasekaran, Senthil Kumar Paramasivan
International Journal on Recent and Innovation Trends in Computing and Communication (2022) Vol. 10, Iss. 12, pp. 92-105
Open Access | Times Cited: 2

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