An improved pelican optimization-kernel extreme learning machine for highly accurate state of charge estimation of lithium-ion batteries in energy storage systems DOI
Sheng Li, Shunli Wang,

Wen Cao

et al.

Ionics, Journal Year: 2025, Volume and Issue: unknown

Published: April 27, 2025

Language: Английский

Short-term wind power prediction based on IBOA-AdaBoost-RVM DOI Creative Commons
Yongliang Yuan,

Qingkang Yang,

Jianji Ren

et al.

Journal of King Saud University - Science, Journal Year: 2024, Volume and Issue: 36(11), P. 103550 - 103550

Published: Nov. 22, 2024

Language: Английский

Citations

5

A novel ensemble network based on CNNAMBiLSTM learner for temperature prediction of distillation columns DOI Open Access
Jianji Ren,

Linpeng Fu,

Yanan Li

et al.

The Canadian Journal of Chemical Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: March 5, 2025

Abstract In recent years, complexity has significantly increased in chemical processes where a distillation column serves as crucial unit. It is worthwhile to develop an accurate and reliable predictive model maintain the steady operation condition of column. Although data‐driven models that do not rely on any prior knowledge present promising approach, they encounter challenges associated with nonlinearity dynamic behaviour within process data. To tackle these challenges, deep learning‐based combined distilled spatiotemporal attention ensemble network (CDSAEN) proposed. The CDSAEN constructed by sequentially integrating multiple base learners, which are iteratively generated decreasing span lengths through boosting method implemented specially designed extraction evaluation function. learner, convolutional neural (CNN), mechanism (AM), bidirectional long short‐term memory (BiLSTM) utilized adaptively capture intricate features establish robust mapping relationship from inputs output. Real‐world data system plant reconstructed time series dataset subsequently fed into for training forecast temperature apparatus advance. results exhibited effectiveness reliability. Additionally, comparison six other approaches, proposed attained superior performance mean absolute error (MAE) = 0.084, root squared (RMSE) 0.108, R 2 0.974. This study can provide support maintaining stable columns processes.

Language: Английский

Citations

0

Hybrid Beluga whale and jellyfish search optimizer for optimizing proton exchange membrane fuel cell parameter estimation DOI
Mohammad Aljaidi, Pradeep Jangir,

Arpita

et al.

Ionics, Journal Year: 2025, Volume and Issue: unknown

Published: April 14, 2025

Language: Английский

Citations

0

An improved pelican optimization-kernel extreme learning machine for highly accurate state of charge estimation of lithium-ion batteries in energy storage systems DOI
Sheng Li, Shunli Wang,

Wen Cao

et al.

Ionics, Journal Year: 2025, Volume and Issue: unknown

Published: April 27, 2025

Language: Английский

Citations

0