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Hybrid Intelligent Modeling Technology and Optimization Strategy for Industrial Energy Consumption Processes

This is to explore the multifaceted aspects of hybrid intelligent modeling technology and optimization strategy for industrial energy consumption processes. With the increasing emphasis on sustainable practices, efficient management of industrial energy consumption has become a critical concern. It...

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Salvato in:
Natura: Online
Lingua:inglese
Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute 2025
Soggetti:
integrated energy systems
economically optimized dispatch
landscape uncertainty
carbon trading
P2G-CCS
sustainable transition
energy saving
reinforcement learning
meta-learning
violation dictionary construction
operation risk prediction
random forests
independent component analysis
mutual information
proton-exchange membrane fuel cells
degradation prediction
durability test
gated recurrent unit
grey wolf optimizer
accuracy
complexity
transformer insulating oil recovery
data-driven monitoring
thermal cycle of insulating oil
recovery rate
supercritical unit
coordination control
model predictive control
energy-saving analysis
rapid load change
open-pit mine
transportation costs
truck waiting times
excavator boom-and-dipper operation durations
improved genetic algorithm
machine learning
production forecast
data preprocessing
principal component analysis
AutoGluon
hybrid energy storage
energy management
state of charge
DC microgrid
load frequency control
dynamic event-triggered mechanism
distributed model predictive control
cloud-edge-terminal
virtual power plant
hybrid intelligent modeling
industrial processes
optimization strategy
artificial intelligence
energy conservation and consumption reduction
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
Accesso online:ONIX_20250812T110751_9783725838837_228
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