Modified multiscale weighted permutation entropy and optimized support vector machine method for rolling bearing fault diagnosis with complex signals
Z Wang, L Yao, G Chen, J Ding - ISA transactions, 2021 - Elsevier
The rolling bearing vibration signals are complex, non-linear, and non-stationary, it is difficult
to extract the sensitive features and diagnose faults by conventional signal processing …
to extract the sensitive features and diagnose faults by conventional signal processing …
Rolling bearing fault diagnosis using generalized refined composite multiscale sample entropy and optimized support vector machine
Z Wang, L Yao, Y Cai - Measurement, 2020 - Elsevier
Rolling bearing fault diagnosis is an important and time sensitive task, to ensure the normal
operation of rotating machinery. This paper proposes a fault diagnosis for rolling bearings …
operation of rotating machinery. This paper proposes a fault diagnosis for rolling bearings …
A two-stage fault diagnosis methodology for rotating machinery combining optimized support vector data description and optimized support vector machine
J Zhang, Q Zhang, X Qin, Y Sun - Measurement, 2022 - Elsevier
Most intelligent fault diagnosis methods of rotating machinery generally consider that normal
samples and fault samples as equally important for pattern recognition training. It ignores …
samples and fault samples as equally important for pattern recognition training. It ignores …
Performance evaluation of hybrid GA–SVM and GWO–SVM models to predict earthquake-induced liquefaction potential of soil: a multi-dataset investigation
The prediction of the potential of soil liquefaction induced by the earthquake is a vital task in
construction engineering and geotechnical engineering. To provide a possible solution to …
construction engineering and geotechnical engineering. To provide a possible solution to …
An improved hybrid grey wolf optimization algorithm
Z Teng, J Lv, L Guo - Soft computing, 2019 - Springer
The existing grey wolf optimization algorithm has some disadvantages, such as slow
convergence speed, low precision and so on. So this paper proposes a grey wolf …
convergence speed, low precision and so on. So this paper proposes a grey wolf …
Hybrid intelligent framework for carbon price prediction using improved variational mode decomposition and optimal extreme learning machine
J Wang, Q Cui, M He - Chaos, Solitons & Fractals, 2022 - Elsevier
As the climate problem continues to worsen, carbon trading markets for energy conservation
and emission reduction have been established in many countries. Accurate forecasting of …
and emission reduction have been established in many countries. Accurate forecasting of …
[HTML][HTML] Optimization of WAG in real geological field using rigorous soft computing techniques and nature-inspired algorithms
MN Amar, AJ Ghahfarokhi, CSW Ng… - Journal of Petroleum …, 2021 - Elsevier
To meet the ever-increasing global energy demands, it is more necessary than ever to
ensure increments in the recovery factors (RF) associated with oil reservoirs. Owing to this …
ensure increments in the recovery factors (RF) associated with oil reservoirs. Owing to this …
Experimental solubility and thermodynamic modeling of empagliflozin in supercritical carbon dioxide
G Sodeifian, C Garlapati, F Razmimanesh… - Scientific Reports, 2022 - nature.com
The solubility of empagliflozin in supercritical carbon dioxide was measured at temperatures
(308 to 338 K) and pressures (12 to 27 MPa), for the first time. The measured solubility in …
(308 to 338 K) and pressures (12 to 27 MPa), for the first time. The measured solubility in …
Effective assessment of blast-induced ground vibration using an optimized random forest model based on a Harris hawks optimization algorithm
Most mines choose the drilling and blasting method which has the characteristics of being a
cheap and efficient method to fragment rock mass, but blast-induced ground vibration …
cheap and efficient method to fragment rock mass, but blast-induced ground vibration …
Prediction of blast-induced rock movement during bench blasting: use of gray wolf optimizer and support vector regression
A large ore loss and dilution can be expected when using a pre-blast ore boundary for
shovel guidance because of the movement and re-distribution of ore in the muck pile under …
shovel guidance because of the movement and re-distribution of ore in the muck pile under …