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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:

Large-Scale Computing Systems Workload Prediction Using Parallel Improved LSTM Neural Network
Xiaoyong Tang
IEEE Access (2019) Vol. 7, pp. 40525-40533
Open Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

Intelligent Data-Driven Decision-Making Method for Dynamic Multisequence: An E-Seq2Seq-Based SCUC Expert System
Nan Yang, Yang Cong, Lei Wu, et al.
IEEE Transactions on Industrial Informatics (2021) Vol. 18, Iss. 5, pp. 3126-3137
Closed Access | Times Cited: 115
Self directed learning based workload forecasting model for cloud resource management
Jitendra Kumar, Ashutosh Kumar Singh, Rajkumar Buyya
Information Sciences (2020) Vol. 543, pp. 345-366
Closed Access | Times Cited: 88
A hybrid CNN-LSTM model for predicting server load in cloud computing
Eva Patel, Dharmender Singh Kushwaha
The Journal of Supercomputing (2022) Vol. 78, Iss. 8, pp. 1-30
Closed Access | Times Cited: 48
Performance Analysis of Machine Learning Centered Workload Prediction Models for Cloud
Deepika Saxena, Jitendra Kumar, Ashutosh Kumar Singh, et al.
IEEE Transactions on Parallel and Distributed Systems (2023) Vol. 34, Iss. 4, pp. 1313-1330
Open Access | Times Cited: 39
Recent advances in deep learning models: a systematic literature review
Ruchika Malhotra, Priya Singh
Multimedia Tools and Applications (2023) Vol. 82, Iss. 29, pp. 44977-45060
Closed Access | Times Cited: 25
Multi-objective energy management of multiple microgrids under random electric vehicle charging
Bifei Tan, Haoyong Chen
Energy (2020) Vol. 208, pp. 118360-118360
Closed Access | Times Cited: 69
Forecasting Cloud Application Workloads WithCloudInsightfor Predictive Resource Management
In Kee Kim, Wei Wang, Yanjun Qi, et al.
IEEE Transactions on Cloud Computing (2020) Vol. 10, Iss. 3, pp. 1848-1863
Closed Access | Times Cited: 51
Developing an Unsupervised Real-Time Anomaly Detection Scheme for Time Series With Multi-Seasonality
Wentai Wu, Ligang He, Weiwei Lin, et al.
IEEE Transactions on Knowledge and Data Engineering (2020) Vol. 34, Iss. 9, pp. 4147-4160
Open Access | Times Cited: 45
Technical Study of Deep Learning in Cloud Computing for Accurate Workload Prediction
Zaakki Ahamed, Maher Khemakhem, Fathy Eassa, et al.
Electronics (2023) Vol. 12, Iss. 3, pp. 650-650
Open Access | Times Cited: 14
A Novel Deep Recurrent Belief Network Model for Trend Prediction of Transformer DGA Data
Bo Qi, Yiming Wang, Peng Zhang, et al.
IEEE Access (2019) Vol. 7, pp. 80069-80078
Open Access | Times Cited: 35
An adaptive update model based on improved Long Short Term Memory for online prediction of vibration signal
Huixin Tian, Daixu Ren, Kun Li, et al.
Journal of Intelligent Manufacturing (2020) Vol. 32, Iss. 1, pp. 37-49
Closed Access | Times Cited: 33
Anomaly detection in cloud environment using artificial intelligence techniques
L Girish, Sridhar K. N. Rao
Computing (2021) Vol. 105, Iss. 3, pp. 675-688
Closed Access | Times Cited: 32
Adaptive Workload Forecasting in Cloud Data Centers
Eduard Zharikov, Sergii Telenyk, Petro I. Bidyuk
Journal of Grid Computing (2019) Vol. 18, Iss. 1, pp. 149-168
Closed Access | Times Cited: 24
Workload Time Series Cumulative Prediction Mechanism for Cloud Resources Using Neural Machine Translation Technique
Mustafa M. Al-Sayed
Journal of Grid Computing (2022) Vol. 20, Iss. 2
Open Access | Times Cited: 12
Is Machine Learning Necessary for Cloud Resource Usage Forecasting?
Georgia Christofidi, Konstantinos Papaioannou, Thaleia Dimitra Doudali
(2023), pp. 544-554
Closed Access | Times Cited: 6
A Self-Optimized Generic Workload Prediction Framework for Cloud Computing
Vinodh Kumaran Jayakumar, Jae Wook Lee, In Kee Kim, et al.
2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS) (2020), pp. 779-788
Closed Access | Times Cited: 15
CANFIS: A Chaos Adaptive Neural Fuzzy Inference System for Workload Prediction in the Cloud
Zohra Amekraz, Youssef Hadi
IEEE Access (2022) Vol. 10, pp. 49808-49828
Open Access | Times Cited: 9
PSO-GA-Based Resource Allocation Strategy for Cloud-Based Software Services With Workload-Time Windows
Zheyi Chen, Lijian Yang, Yinhao Huang, et al.
IEEE Access (2020) Vol. 8, pp. 151500-151510
Open Access | Times Cited: 14
Combination of Deep Learning Models for Student’s Performance Prediction with a Development of Entropy Weighted Rough Set Feature Mining
Sateesh Nayani, Srinivasa Rao P, R. D.
Cybernetics & Systems (2023), pp. 1-43
Closed Access | Times Cited: 4
Application-Oriented Cloud Workload Prediction: A Survey and New Perspectives
Binbin Feng, Zhijun Ding
Tsinghua Science & Technology (2024) Vol. 30, Iss. 1, pp. 34-54
Closed Access | Times Cited: 1
An Efficient Workflow Scheduling Using Genetically Modified Golden Jackal Optimization With Recurrent Autoencoder in Cloud Computing
Shivam Tripathi, Sarsij Tripathi
International Journal of Network Management (2024) Vol. 35, Iss. 1
Closed Access | Times Cited: 1
Toward Pattern-based Model Selection for Cloud Resource Forecasting
Georgia Christofidi, Konstantinos Papaioannou, Thaleia Dimitra Doudali
(2023)
Closed Access | Times Cited: 3
Forecasting the Spot Market Electricity Price with a Long Short-Term Memory Model Architecture in a Disruptive Economic and Geopolitical Context
Adela Bârã, Simona‐Vasilica Oprea, Alexandru-Costin Băroiu
International Journal of Computational Intelligence Systems (2023) Vol. 16, Iss. 1
Open Access | Times Cited: 3
CloudBruno: A Low-Overhead Online Workload Prediction Framework for Cloud Computing
Vinodh Kumaran Jayakumar, Shivani Arbat, In Kee Kim, et al.
(2022), pp. 188-198
Closed Access | Times Cited: 5
Pedestrian detection using Doppler radar and LSTM neural network
Mussyazwann Azizi Mustafa Azizi, Mohammad Nazrin Mohd Noh, Idnin Pasya, et al.
IAES International Journal of Artificial Intelligence (2020) Vol. 9, Iss. 3, pp. 394-394
Open Access | Times Cited: 6
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