Research on the Stability and Treatments of Natural Gas Storage Caverns With Different Shapes in Bedded Salt Rocks DOI Creative Commons
Wei Liu, Zhixin Zhang, Jinyang Fan

et al.

IEEE Access, Journal Year: 2020, Volume and Issue: 8, P. 18995 - 19007

Published: Jan. 1, 2020

Because of complex geo-conditions, many caverns by solution mining in bedded salt rocks have different irregular shapes. To verify the feasibility using irregular-shaped for underground gas storage (UGS), four typical cavern-shapes are selected, and stability each type is evaluated compared numerical simulation methods. The results show that UGS cavern with wall shape has lowest volume shrinkage displacement rock, but larger plastic zones appear their overhanging concave parts. Ellipsoid-shape best stability. Cylinder-shape cuboid-shape poorest In these two types caverns, large deformations occur roof sidewall, which pose a great potential inducing collapse rock. By comparison characteristics positions we found much greater influence than sidewall on cavern. must be designed as an arch to improve Treatments irregularly shaped changing operational pressure utilization way or modifying caverns' also discussed. So, this study not only determined state rocks, provides ways modify applications.

Language: Английский

Whale optimization algorithm: a systematic review of contemporary applications, modifications and developments DOI
Nadim Rana, Muhammad Shafie Abd Latiff, Shafi’i Muhammad Abdulhamid

et al.

Neural Computing and Applications, Journal Year: 2020, Volume and Issue: 32(20), P. 16245 - 16277

Published: March 30, 2020

Language: Английский

Citations

251
Carbon trading volume and price forecasting in China using multiple machine learning models DOI
Hongfang Lü, Xin Ma, Kun Huang

et al.

Journal of Cleaner Production, Journal Year: 2019, Volume and Issue: 249, P. 119386 - 119386

Published: Nov. 21, 2019

Language: Английский

Citations

238
Boosted mutation-based Harris hawks optimizer for parameters identification of single-diode solar cell models DOI
Hussein Mohammed Ridha, Ali Asghar Heidari, Mingjing Wang

et al.

Energy Conversion and Management, Journal Year: 2020, Volume and Issue: 209, P. 112660 - 112660

Published: March 9, 2020

Language: Английский

Citations

191
Network Intrusion Detection Based on PSO-Xgboost Model DOI Creative Commons
Hui Jiang, Zheng He, Gang Ye

et al.

IEEE Access, Journal Year: 2020, Volume and Issue: 8, P. 58392 - 58401

Published: Jan. 1, 2020

Network intrusion detection system (NIDS) is a commonly used tool to detect attacks and protect networks, while one of its general limitations the false positive issue. On basis our comparative experiments analysis for characteristics particle swarm optimization (PSO) Xgboost, this paper proposes PSO-Xgboost model given overall higher classification accuracy than other alternative models such like Random Forest, Bagging Adaboost. Firstly, based on Xgboost constructed, then PSO adaptively search optimal structure Xgboost. The benchmark NSL-KDD dataset evaluate proposed model. Our experimental results demonstrate that outperforms in precision, recall, macro-average (macro) mean average precision (mAP), especially when identifying minority groups U2R R2L. This work also provides arguments application intelligence NIDS.

Language: Английский

Citations

178
Forecast the electricity price of U.S. using a wavelet transform-based hybrid model DOI
Weibiao Qiao, Zhe Yang

Energy, Journal Year: 2019, Volume and Issue: 193, P. 116704 - 116704

Published: Dec. 16, 2019

Language: Английский

Citations

161
Frequency characteristics of FG-GPLRC viscoelastic thick annular plate with the aid of GDQM DOI
Mehran Safarpour, Aria Ghabussi, Farzad Ebrahimi

et al.

Thin-Walled Structures, Journal Year: 2020, Volume and Issue: 150, P. 106683 - 106683

Published: Feb. 24, 2020

Language: Английский

Citations

140
A Systematic Review of the Whale Optimization Algorithm: Theoretical Foundation, Improvements, and Hybridizations DOI Open Access
Mohammad H. Nadimi-Shahraki, Hoda Zamani, Zahra Asghari Varzaneh

et al.

Archives of Computational Methods in Engineering, Journal Year: 2023, Volume and Issue: 30(7), P. 4113 - 4159

Published: May 27, 2023

Language: Английский

Citations

115
An innovative coupled model in view of wavelet transform for predicting short-term PM10 concentration DOI
Weibiao Qiao, Yining Wang,

Jianzhuang Zhang

et al.

Journal of Environmental Management, Journal Year: 2021, Volume and Issue: 289, P. 112438 - 112438

Published: April 16, 2021

Language: Английский

Citations

109
Short-Term Load Forecasting Models: A Review of Challenges, Progress, and the Road Ahead DOI Creative Commons
Saima Akhtar, Sulman Shahzad,

Asad Zaheer

et al.

Energies, Journal Year: 2023, Volume and Issue: 16(10), P. 4060 - 4060

Published: May 12, 2023

Short-term load forecasting (STLF) is critical for the energy industry. Accurate predictions of future electricity demand are necessary to ensure power systems’ reliable and efficient operation. Various STLF models have been proposed in recent years, each with strengths weaknesses. This paper comprehensively reviews some models, including time series, artificial neural networks (ANNs), regression-based, hybrid models. It first introduces fundamental concepts challenges STLF, then discusses model class’s main features assumptions. The compares terms their accuracy, robustness, computational efficiency, scalability, adaptability identifies approach’s advantages limitations. Although this study suggests that ANNs may be most promising ways achieve accurate additional research required handle multiple input features, manage massive data sets, adjust shifting conditions.

Language: Английский

Citations

52
Seasonal peak load prediction of underground gas storage using a novel two-stage model combining improved complete ensemble empirical mode decomposition and long short-term memory with a sparrow search algorithm DOI
Weibiao Qiao,

Zonghua Fu,

Mingjun Du

et al.

Energy, Journal Year: 2023, Volume and Issue: 274, P. 127376 - 127376

Published: March 30, 2023

Language: Английский

Citations

42