Feasibility evaluation of large-scale underground hydrogen storage in bedded salt rocks of China: A case study in Jiangsu province

Energy, Journal Year: 2020, Volume and Issue: 198, P. 117348 - 117348

Published: March 9, 2020

Language: Английский

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An efficient Harris hawks-inspired image segmentation method

Expert Systems with Applications, Journal Year: 2020, Volume and Issue: 155, P. 113428 - 113428

Published: April 7, 2020

Language: Английский

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Orthogonal Nelder-Mead moth flame method for parameters identification of photovoltaic modules

Energy Conversion and Management, Journal Year: 2020, Volume and Issue: 211, P. 112764 - 112764

Published: April 3, 2020

Language: Английский

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A new hybrid algorithm model for prediction of internal corrosion rate of multiphase pipeline

Journal of Natural Gas Science and Engineering, Journal Year: 2020, Volume and Issue: 85, P. 103716 - 103716

Published: Nov. 18, 2020

Language: Английский

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Predicting Entrepreneurial Intention of Students: An Extreme Learning Machine With Gaussian Barebone Harris Hawks Optimizer

IEEE Access, Journal Year: 2020, Volume and Issue: 8, P. 76841 - 76855

Published: Jan. 1, 2020

This study aims to propose an effective intelligent model for predicting entrepreneurial intention, which can provide a reasonable reference the formulation of talent training programs and guidance intention students. The prediction is mainly based on kernel extreme learning machine (KELM) optimized by improved Harris hawk's optimizer (HHO). In order obtain better parameters feature subsets, Gaussian barebone (GB) strategy introduced improve HHO algorithm, so as strengthen optimization ability tuning KELM identifying compact subsets. Then, optimal (GBHHO-KELM) established according obtained subsets predict experiment, GBHHO compared with other nine well-known methods in 30 CEC 2014 benchmark problems. experimental findings suggest that proposed method significantly superior existing most At same time, GBHHO-KELM intention. results indicate achieve classification performance higher stability accordance four metrics. Therefore, we conclude expected be tool

Language: Английский

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Parameters identification of photovoltaic cell models using enhanced exploratory salp chains-based approach

Energy, Journal Year: 2020, Volume and Issue: 198, P. 117333 - 117333

Published: March 9, 2020

Language: Английский

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Research on gas leakage and collapse in the cavern roof of underground natural gas storage in thinly bedded salt rocks

Journal of Energy Storage, Journal Year: 2020, Volume and Issue: 31, P. 101669 - 101669

Published: Aug. 11, 2020

Language: Английский

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Time Interval Effect in Triaxial Discontinuous Cyclic Compression Tests and Simulations for the Residual Stress in Rock Salt

Rock Mechanics and Rock Engineering, Journal Year: 2020, Volume and Issue: 53(9), P. 4061 - 4076

Published: May 27, 2020

Language: Английский

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Fastest‐growing source prediction of US electricity production based on a novel hybrid model using wavelet transform

International Journal of Energy Research, Journal Year: 2021, Volume and Issue: 46(2), P. 1766 - 1788

Published: Oct. 3, 2021

Electricity is an important indicator for economic development, especially electricity production (EP), which industry managers making strategic decisions. There are many ways to produce electricity, the source of rapid growth in EP rarely studied. Due nonstationary and nonlinearity time series, traditional methods less robust predict it. In this study, a novel combination prediction model proposed based on wavelet transform (WT), long short-term memory (LSTM), stacked autoencoder (SAE). Comparisons between SAE-LSTM advanced model. We compared including BP (Back Propagation) etc. addition, performance comparison different layers EMD EEMD also compared. At last, future average rates (June 2021 → December 2022) predicted. The empirical result shows that view exceeds benchmark models. results imply WT-SAE-LSTM outperforms EMD, EEMD-SAE-LSTM, SAE. Based optimal orders Coiflets combining with SAE-LSTM, natural gas fastest-growing United States.

Language: Английский

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Sine cosine grey wolf optimizer to solve engineering design problems

Engineering With Computers, Journal Year: 2020, Volume and Issue: 37(4), P. 3123 - 3149

Published: Feb. 29, 2020

Language: Английский

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