Scenario-based automated data preprocessing to predict severity of construction accidents
Occupational accidents are common in the construction industry, therefore developing
prediction models to detect high severe accidents would be useful. However, existing …
prediction models to detect high severe accidents would be useful. However, existing …
A systematic literature review of clustering techniques for patients with traumatic brain injury
While the number of people suffering from traumatic brain injury (TBI) has increased
considerably in recent years, the multiple deficits of these patients makes designing the …
considerably in recent years, the multiple deficits of these patients makes designing the …
Empirical mode decomposition based multi-objective deep belief network for short-term power load forecasting
C Fan, C Ding, J Zheng, L Xiao, Z Ai - Neurocomputing, 2020 - Elsevier
With the rapid development of power grid data, the data generated by the operation of the
power system is increasingly complex, and the amount of data increases exponentially. In …
power system is increasingly complex, and the amount of data increases exponentially. In …
A structurally re-parameterized convolution neural network-based method for gearbox fault diagnosis in edge computing scenarios
Gearboxes operate in harsh environments. Cloud-based techniques have been previously
adopted for fault diagnosis in Gearboxes. Cloud-based fault diagnosis methods are prone to …
adopted for fault diagnosis in Gearboxes. Cloud-based fault diagnosis methods are prone to …
[HTML][HTML] Systematic review of graphical visual methods in honeypot attack data analysis
G Ikuomenisan, Y Morgan - Journal of Information Security, 2022 - scirp.org
Mitigating increasing cyberattack incidents may require strategies such as reinforcing
organizations' networks with Honeypots and effectively analyzing attack traffic for detection …
organizations' networks with Honeypots and effectively analyzing attack traffic for detection …
A methodology for community detection in Twitter
W Silva, Á Santana, F Lobato, M Pinheiro - Proceedings of the …, 2017 - dl.acm.org
The microblogging service Twitter is one of the world's most popular online social networks
and assembles a huge amount of data produced by interactions between users. A careful …
and assembles a huge amount of data produced by interactions between users. A careful …
[HTML][HTML] Survey: time-series data preprocessing: a survey and an empirical analysis
Data are naturally collected in their raw state and must undergo a series of preprocessing
steps to obtain data in their input state for Artificial Intelligence (AI) and other applications …
steps to obtain data in their input state for Artificial Intelligence (AI) and other applications …
Impacts of dirty data: and experimental evaluation
Data quality issues have attracted widespread attention due to the negative impacts of dirty
data on data mining and machine learning results. The relationship between data quality …
data on data mining and machine learning results. The relationship between data quality …
[HTML][HTML] A novel intelligent system based on machine learning for hydrochar multi-target prediction from the hydrothermal carbonization of biomass
W Zhang, J Zhou, Q Liu, Z Xu, H Peng, L Leng, H Li - Biochar, 2024 - Springer
Hydrothermal carbonization (HTC) is a thermochemical conversion technology to produce
hydrochar from wet biomass without drying, but it is time-consuming and expensive to …
hydrochar from wet biomass without drying, but it is time-consuming and expensive to …
Impacts of dirty data on classification and clustering models: an experimental evaluation
ZX Qi, HZ Wang, AJ Wang - Journal of Computer Science and Technology, 2021 - Springer
Data quality issues have attracted widespread attentions due to the negative impacts of dirty
data on data mining and machine learning results. The relationship between data quality …
data on data mining and machine learning results. The relationship between data quality …