Impact of artificial intelligence energy management technologies on commercial multi-energy consumption
Authors:
- Zhong-Lin FuZFZhong-Lin Fu
- Can CaoCCCan Cao
- Feng GaoFGFeng Gao
Abstract
No abstract availableFunding Information
- Guangdong Power Grid Company (030100KC23020009)
- Key Technologies Research and Development Program of Guangzhou Municipality
- Guangzhou Municipal Science and Technology Bureau (20220602JBGS04)
This publication has 52 references indexed in Scilit:
- Deep neural network-based music user preference modeling, accurate recommendation, and IoT-enabled personalizationAlexandria Engineering Journal, 2025
- Energy management and industry 4.0: Analysis of the enabling effects of digitalization on the implementation of energy management practicesApplied Energy, 2025
- Reinforcement learning for Multi-Flight Dynamic PricingComputers & Industrial Engineering, 2024
- Intelligent decision support system for optimizing inventory management under stochastic eventsApplied Intelligence, 2023
- Intelligent energy management systems: a reviewArtificial Intelligence Review, 2023
- A Framework for Analysing Energy Consumption Factors in Commercially Built EnvironmentsJournal of The Institution of Engineers (India): Series A, 2022
- Application of fuzzy logic in lift energy efficiency classificationEnergy Efficiency, 2019
- A novel remote control system for air conditioning in low carbon emission buildings using sensor fusion and mobile communication technologiesBuilding and Environment, 2019
- Machine learning approaches for estimating commercial building energy consumptionApplied Energy, 2017
- Data analytics and optimization of an ice-based energy storage system for commercial buildingsApplied Energy, 2017