Stock market prediction using machine learning techniques: a decade survey on methodologies, recent developments, and future directions
With the advent of technological marvels like global digitization, the prediction of the stock
market has entered a technologically advanced era, revamping the old model of trading …
market has entered a technologically advanced era, revamping the old model of trading …
Solar radiation prediction using recurrent neural network and artificial neural network: A case study with comparisons
With the rapid advancement of the high-performance computing technology and the
increasing availability of the mass-storage memory device, the application of the data-driven …
increasing availability of the mass-storage memory device, the application of the data-driven …
A multi-objective predictive energy management strategy for residential grid-connected PV-battery hybrid systems based on machine learning technique
K Shivam, JC Tzou, SC Wu - Energy Conversion and Management, 2021 - Elsevier
This paper proposes a multi-objective predictive energy management strategy based on
machine learning technique for residential grid-connected hybrid energy systems. The …
machine learning technique for residential grid-connected hybrid energy systems. The …
Data-driven techniques for fault detection in anaerobic digestion process
Anaerobic digestion (AD) is an appropriate process for bio-energy (biogas) production from
waste and wastewater receiving a high level of attention at both academic and industrial …
waste and wastewater receiving a high level of attention at both academic and industrial …
[HTML][HTML] A predictive maintenance model using long short-term memory neural networks and Bayesian inference
D Pagano - Decision Analytics Journal, 2023 - Elsevier
The fourth industrial revolution is a profound transformation utilizing emerging technologies
like smart automation, large-scale machine-to-machine communication, and the internet of …
like smart automation, large-scale machine-to-machine communication, and the internet of …
Robust data-driven soft sensors for online monitoring of volatile fatty acids in anaerobic digestion processes
The concentration of volatile fatty acids (VFAs) is one of the most important measurements
for evaluating the performance of anaerobic digestion (AD) processes. In real-time …
for evaluating the performance of anaerobic digestion (AD) processes. In real-time …
[HTML][HTML] A reliable intelligent diagnostic assistant for nuclear power plants using explainable artificial intelligence of GRU-AE, LightGBM and SHAP
JH Park, HS Jo, SH Lee, SW Oh, MG Na - Nuclear Engineering and …, 2022 - Elsevier
When abnormal operating conditions occur in nuclear power plants, operators must identify
the occurrence cause and implement the necessary mitigation measures. Accordingly, the …
the occurrence cause and implement the necessary mitigation measures. Accordingly, the …
Infrastructure fault detection and prediction in edge cloud environments
M Soualhia, C Fu, F Khomh - Proceedings of the 4th ACM/IEEE …, 2019 - dl.acm.org
As an emerging 5G system component, edge cloud becomes one of the key enablers to
provide services such us mission critical, IoT and content delivery applications. However …
provide services such us mission critical, IoT and content delivery applications. However …
Deep learning based fusion model for multivariate LTE traffic forecasting and optimized radio parameter estimation
With the evaluation of cellular network internet data traffic, forecasting and understanding
traffic patterns become the critical objectives for managing the network-designed Quality of …
traffic patterns become the critical objectives for managing the network-designed Quality of …
Deep learning-based predictions of older adults' adherence to cognitive training to support training efficacy
As the population ages, the number of older adults experiencing mild cognitive impairment
(MCI), Alzheimer's disease, and other forms of dementia will increase dramatically over the …
(MCI), Alzheimer's disease, and other forms of dementia will increase dramatically over the …