Advances in computational intelligence of polymer composite materials: machine learning assisted modeling, analysis and design
The superior multi-functional properties of polymer composites have made them an ideal
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
choice for aerospace, automobile, marine, civil, and many other technologically demanding …
Machine learning based marine water quality prediction for coastal hydro-environment management
During the past three decades, harmful algal blooms (HAB) events have been frequently
observed in marine waters around many coastal cities in the world including Hong Kong …
observed in marine waters around many coastal cities in the world including Hong Kong …
Deep data assimilation: integrating deep learning with data assimilation
In this paper, we propose Deep Data Assimilation (DDA), an integration of Data Assimilation
(DA) with Machine Learning (ML). DA is the Bayesian approximation of the true state of …
(DA) with Machine Learning (ML). DA is the Bayesian approximation of the true state of …
Power consumption model based on feature selection and deep learning in cloud computing scenarios
Y Liang, Z Hu, K Li - IET Communications, 2020 - Wiley Online Library
High power consumption of cloud data centres is a crucial challenge in modern cloud
computing. To comply with the conceptions of green computing, power consumption …
computing. To comply with the conceptions of green computing, power consumption …
Deep machine learning-based power usage effectiveness prediction for sustainable cloud infrastructures
The expansion of online services, the advent of big data, and the development of Internet of
Things (IoT) technology have led to an exponential growth in the number of data centers …
Things (IoT) technology have led to an exponential growth in the number of data centers …
Model error correction in data assimilation by integrating neural networks
In this paper, we suggest a new methodology which combines Neural Networks (NN) into
Data Assimilation (DA). Focusing on the structural model uncertainty, we propose a …
Data Assimilation (DA). Focusing on the structural model uncertainty, we propose a …
Modelling and prediction of resource utilization of hadoop clusters: A machine learning approach
Hadoop is a distributed computing framework that has a large number of configurable
parameters. These parameters have impact on system resources and execution time …
parameters. These parameters have impact on system resources and execution time …
EWM: An entropy‐based framework for estimating energy consumption of edge servers
G Li, J Li - Engineering Reports, 2024 - Wiley Online Library
In mobile edge computing (MEC), accurately predicting and monitoring the energy
consumption of edge servers is a key challenge in achieving green computing. The …
consumption of edge servers is a key challenge in achieving green computing. The …
Instrumentation location diversity paradigm for future astronomy observations
AA Periola, OE Falowo - Wireless Personal Communications, 2018 - Springer
Capital constrained organizations desiring to conduct astronomy observations face
significant challenges due to the high cost of acquiring telescopes and computing facilities …
significant challenges due to the high cost of acquiring telescopes and computing facilities …
EPF: a general framework for supporting continuous top-k queries over streaming data
H Jiang, R Zhu, B Wang - Cognitive Computation, 2020 - Springer
Continuous top-k query over sliding window is a fundamental problem in the domain of
streaming data management, which monitors the query window and retrieves k objects with …
streaming data management, which monitors the query window and retrieves k objects with …