Multivariate time series prediction of high dimensional data based on deep reinforcement learning [PDF]
E3S Web of Conferences, 2021 In order to improve the prediction accuracy of high-dimensional data time series, a high-dimensional data multivariate time series prediction method based on deep reinforcement learning is proposed. The deep reinforcement learning method is used to solve
Ji Xin +5 more
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Advances in Multimedia, 2022 The Internet is like a huge neural network that is thought to be built, linking all the information in the human brain, and the communication between people is a part of the communication in the whole society.
Yun Dong +4 more
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Hierarchical mining algorithm for high dimensional spatiotemporal big data based on association rules [PDF]
E3S Web of Conferences, 2021 The traditional data mining algorithm focuses too much on a single dimension of data time or space, ignoring the association between time and space, which leads to a large amount of computation and low processing efficiency of the mining algorithm and ...
Zhou Chunlei +5 more
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Accounting CO2 Emissions of the Cement Industry: Based on an Electricity–Carbon Coupling Analysis
Energies, 2023 Since the cement industry acts as a significant contributor to carbon emissions in China, China’s national emission trading system has announced that it should be included in the system soon. However, current cement carbon accounting methods require high-
Chunlei Zhou +5 more
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An Efficient Data Replication Strategy in Large-Scale Data Grid Environments Based on Availability and Popularity [PDF]
AUT Journal of Modeling and Simulation, 2018 The data grid technology, which uses the scale of the Internet to solve storage limitation for the huge amount of data, has become one of the hot research topics.
N. Mansouri, M.M. Javidi
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Data and Task Scheduling in Distributed Computing Environments
Journal of Telecommunications and Information Technology, 2014 Data-aware scheduling in today’s large-scale heterogeneous environments has become a major research and engineering issue. Data Grids (DGs), Data Clouds (DCs) and Data Centers are designed for supporting the processing and analysis of massive data ...
Magdalena Szmajduch
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An Improved Federated Learning-Assisted Data Aggregation Scheme for Smart Grids
Applied Sciences, 2023 In the context of rapid advancements in artificial intelligence (AI) technology, new technologies, such as federated learning and edge computing, have been widely applied in the power Internet of Things (PIoT).
Bo Pang +7 more
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The Impact of the Implementation Cost of Replication in Data Grid Job Scheduling
Mathematical and Computational Applications, 2018 Data Grids deal with geographically-distributed large-scale data-intensive applications. Schemes scheduled for data grids attempt to not only improve data access time, but also aim to improve the ratio of data availability to a node, where the data ...
Babar Nazir +3 more
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A Power Text Classification Model Based on Dual-layer Attention Mechanism
Zhongguo dianliThere are a large amount of Chinese text data in the electric power field, traditional text mining methods are faced with problems such as difficulty in word segmentation, limitations in text feature representation, and poor performance in handling ...
Tongxin WU +4 more
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Reliability and Availability Improvement in Economic Data Grid Environment Based On Clustering Approach [PDF]
Journal of Advances in Computer Engineering and Technology, 2015 - One of the important problems in grid environments is data replication in grid sites. Reliability and availability of data replication in some cases is considered low.
Ali Abbasi +2 more
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