Comparison of predicted vs. actual natural gas production (August 29–September 25, 2023), with predictive performance under high-temperature conditions verifying the model’s environmental adaptability.

<p>Comparison of predicted vs. actual natural gas production (August 29–September 25, 2023), with predictive performance under high-temperature conditions verifying the model’s environmental adaptability.</p>

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Main Author: Dong Wang (73290) (author)
Other Authors: Jian Lian (19690960) (author), Chengjiang Li (11430895) (author), Yanlei Wang (235566) (author)
Published: 2025
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_version_ 1852015895826661376
author Dong Wang (73290)
author2 Jian Lian (19690960)
Chengjiang Li (11430895)
Yanlei Wang (235566)
author2_role author
author
author
author_facet Dong Wang (73290)
Jian Lian (19690960)
Chengjiang Li (11430895)
Yanlei Wang (235566)
author_role author
dc.creator.none.fl_str_mv Dong Wang (73290)
Jian Lian (19690960)
Chengjiang Li (11430895)
Yanlei Wang (235566)
dc.date.none.fl_str_mv 2025-10-09T17:41:47Z
dc.identifier.none.fl_str_mv 10.1371/journal.pone.0333905.g012
dc.relation.none.fl_str_mv https://figshare.com/articles/figure/Comparison_of_predicted_vs_actual_natural_gas_production_August_29_September_25_2023_with_predictive_performance_under_high-temperature_conditions_verifying_the_model_s_environmental_adaptability_/30320921
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
reduced computational complexity
recurrent neural network
liquid level detection
feature engineering techniques
experimental results demonstrate
enhance model performance
efficient resource management
deep learning predictions
applying rigorous preprocessing
time series forecasting
capture temporal dependencies
bidirectional long short
natural gas production
term memory model
gas production
term memory
term dependencies
handle long
accurate forecasting
xlink ">
study proposes
study contributes
strong candidate
sequential data
recent advancement
providing insights
operational planning
new dataset
innovative self
future research
energy sector
dataset comparing
critical parameters
comprehensive dataset
attention mechanism
art algorithms
dc.title.none.fl_str_mv Comparison of predicted vs. actual natural gas production (August 29–September 25, 2023), with predictive performance under high-temperature conditions verifying the model’s environmental adaptability.
dc.type.none.fl_str_mv Image
Figure
info:eu-repo/semantics/publishedVersion
image
description <p>Comparison of predicted vs. actual natural gas production (August 29–September 25, 2023), with predictive performance under high-temperature conditions verifying the model’s environmental adaptability.</p>
eu_rights_str_mv openAccess
id Manara_367e68a85af667b4e5fcc4ae9c6ea2fe
identifier_str_mv 10.1371/journal.pone.0333905.g012
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/30320921
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling Comparison of predicted vs. actual natural gas production (August 29–September 25, 2023), with predictive performance under high-temperature conditions verifying the model’s environmental adaptability.Dong Wang (73290)Jian Lian (19690960)Chengjiang Li (11430895)Yanlei Wang (235566)Biological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedreduced computational complexityrecurrent neural networkliquid level detectionfeature engineering techniquesexperimental results demonstrateenhance model performanceefficient resource managementdeep learning predictionsapplying rigorous preprocessingtime series forecastingcapture temporal dependenciesbidirectional long shortnatural gas productionterm memory modelgas productionterm memoryterm dependencieshandle longaccurate forecastingxlink ">study proposesstudy contributesstrong candidatesequential datarecent advancementproviding insightsoperational planningnew datasetinnovative selffuture researchenergy sectordataset comparingcritical parameterscomprehensive datasetattention mechanismart algorithms<p>Comparison of predicted vs. actual natural gas production (August 29–September 25, 2023), with predictive performance under high-temperature conditions verifying the model’s environmental adaptability.</p>2025-10-09T17:41:47ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0333905.g012https://figshare.com/articles/figure/Comparison_of_predicted_vs_actual_natural_gas_production_August_29_September_25_2023_with_predictive_performance_under_high-temperature_conditions_verifying_the_model_s_environmental_adaptability_/30320921CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/303209212025-10-09T17:41:47Z
spellingShingle Comparison of predicted vs. actual natural gas production (August 29–September 25, 2023), with predictive performance under high-temperature conditions verifying the model’s environmental adaptability.
Dong Wang (73290)
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
reduced computational complexity
recurrent neural network
liquid level detection
feature engineering techniques
experimental results demonstrate
enhance model performance
efficient resource management
deep learning predictions
applying rigorous preprocessing
time series forecasting
capture temporal dependencies
bidirectional long short
natural gas production
term memory model
gas production
term memory
term dependencies
handle long
accurate forecasting
xlink ">
study proposes
study contributes
strong candidate
sequential data
recent advancement
providing insights
operational planning
new dataset
innovative self
future research
energy sector
dataset comparing
critical parameters
comprehensive dataset
attention mechanism
art algorithms
status_str publishedVersion
title Comparison of predicted vs. actual natural gas production (August 29–September 25, 2023), with predictive performance under high-temperature conditions verifying the model’s environmental adaptability.
title_full Comparison of predicted vs. actual natural gas production (August 29–September 25, 2023), with predictive performance under high-temperature conditions verifying the model’s environmental adaptability.
title_fullStr Comparison of predicted vs. actual natural gas production (August 29–September 25, 2023), with predictive performance under high-temperature conditions verifying the model’s environmental adaptability.
title_full_unstemmed Comparison of predicted vs. actual natural gas production (August 29–September 25, 2023), with predictive performance under high-temperature conditions verifying the model’s environmental adaptability.
title_short Comparison of predicted vs. actual natural gas production (August 29–September 25, 2023), with predictive performance under high-temperature conditions verifying the model’s environmental adaptability.
title_sort Comparison of predicted vs. actual natural gas production (August 29–September 25, 2023), with predictive performance under high-temperature conditions verifying the model’s environmental adaptability.
topic Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
reduced computational complexity
recurrent neural network
liquid level detection
feature engineering techniques
experimental results demonstrate
enhance model performance
efficient resource management
deep learning predictions
applying rigorous preprocessing
time series forecasting
capture temporal dependencies
bidirectional long short
natural gas production
term memory model
gas production
term memory
term dependencies
handle long
accurate forecasting
xlink ">
study proposes
study contributes
strong candidate
sequential data
recent advancement
providing insights
operational planning
new dataset
innovative self
future research
energy sector
dataset comparing
critical parameters
comprehensive dataset
attention mechanism
art algorithms