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An Efficiency of Third Party Genetic Algorithms Software Libraries in Mobile Distributed Computing for Financial Time Series Forecasting
Mateeva, Gergana ; Parvanov, Dimitar ; Dimitrov, Ioan ; et al.
2022 International Conference Automatics and Informatics (ICAI) Automatics and Informatics (ICAI), 2022 International Conference. :351-354 Oct, 2022
Distributed photovoltaic cluster output monitoring method based on time series data acquisition.
Ye, Hua ; Lu, Xuegang ; Zhang, Wei ; et al.
Energy Informatics; 2/19/2025, Vol. 8 Issue 1, p1-27, 27p
A distributed computing system for multivariate time series analyses of multichannel neurophysiological data
Muller, A. ; Osterhage, H. ; Sowa, R. ; et al.
JOURNAL OF NEUROSCIENCE METHODS. 152(1-2):190-201
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Distributed Computing in a Time Series Analysis System
Yamamoto, Yoshikazu ; Nakano, Junji ; Yamamoto, Yoshikazu ; et al.
ARTIFICIAL NEURAL NETWORKS FOR EDGE AND FOG COMPUTING-BASED ENERGY PREDICTION.
Sai Sree, M. Syamala ; Yeshswini, M. P. ; Jahnavi, M. P. ; et al.
Journal of Cardiovascular Disease Research (Journal of Cardiovascular Disease Research); 2023, Vol. 14 Issue 10, p749-760, 12p
Towards an Introspective Dynamic Model of Globally Distributed Computing Infrastructures
Kilic, Ozgur O. ; Park, David K. ; Ren, Yihui ; et al.
CHEP 2024, EPJ Web of Conferences (EPJ WoC)
Distributed computing in a time series analysis system
Yamamoto, Yoshikazu ; Nakano, Junji
Deterministic (Δ + 1)-Coloring in Sublinear (in Δ) Time in Static, Dynamic, and Faulty Networks.
BARENBOIM, LEONID
Journal of the ACM. Nov2016, Vol. 63 Issue 5, p1-22. 22p.
Monitoring distributed computing beyond the traditional time-series histogram.
Doglioni, C. ; Kim, D. ; Stewart, G.A. ; et al.
EPJ Web of Conferences; 11/16/2020, Vol. 245, p1-5, 5p
Scalable and accurate online multivariate anomaly detection.
Salles, Rebecca ; Lange, Benoit ; Akbarinia, Reza ; et al.
Information Systems. Jun2025, Vol. 131, pN.PAG-N.PAG. 1p.
Pattern sequence-based algorithm for multivariate big data time series forecasting: Application to electricity consumption.
Pérez-Chacón, R. ; Asencio-Cortés, G. ; Troncoso, A. ; et al.
Future Generation Computer Systems. May2024, Vol. 154, p397-412. 16p.
MAP-Vis: A Distributed Spatio-Temporal Big Data Visualization Framework Based on a Multi-Dimensional Aggregation Pyramid Model.
Xuefeng Guan ; Chong Xie ; Linxu Han ; et al.
Applied Sciences (2076-3417); 1/15/2020, Vol. 10 Issue 2, p598, 19p
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Dynamic Scheduling of Trigger Command for Sub-Microsecond Alignment Accuracy in Distributed Measurement System.
Lamonaca, Francesco ; Grimaldi, Domenico ; Morello, Rosario
IEEE Transactions on Instrumentation & Measurement. Jul2014, Vol. 63 Issue 7, p1795-1803. 9p.
A periodicity-based parallel time series prediction algorithm in cloud computing environments.
Chen, Jianguo ; Li, Kenli ; Rong, Huigui ; et al.
Information Sciences. Sep2019, Vol. 496, p506-537. 32p.
SPOT: Testing Stream Processing Programs with Symbolic Execution and Stream Synthesizing.
Ye, Qian ; Lu, Minyan
Applied Sciences (2076-3417); 9/1/2021, Vol. 11 Issue 17, p8057, 26p
Simulating the Planck Mission on a Distributed Computing Architecture: The DEISA and EGEE Experiences
Astronomical data analysis software and systems
Gheller, C. ; Leach, S. ; Taffoni, G. ; et al.
ASTRONOMICAL SOCIETY OF THE PACIFIC CONFERENCE SERIES. 376:61-64
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Static Models and Simulation Engine for Time-Analysis and Verification of Mission-Critical Distributed Systems
Real time computing
Cantone, G.
NATO ASI SERIES F COMPUTER AND SYSTEMS SCIENCES. 127:325-346
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