Proposing a hybrid metaheuristic optimization algorithm and machine learning model for energy use forecast in non-residential buildings
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Proposing a hybrid metaheuristic optimization algorithm and machine learning model for energy use forecast in non-residential buildings
Authors
Keywords
-
Journal
Scientific Reports
Volume 12, Issue 1, Pages -
Publisher
Springer Science and Business Media LLC
Online
2022-01-20
DOI
10.1038/s41598-022-04923-7
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Machine learning towards intelligent systems: applications, challenges, and opportunities
- (2021) MohammadNoor Injadat et al. ARTIFICIAL INTELLIGENCE REVIEW
- A hybrid model for building energy consumption forecasting using long short term memory networks
- (2020) Nivethitha Somu et al. APPLIED ENERGY
- Deep learning-based appearance features extraction for automated carp species identification
- (2020) Ashkan Banan et al. AQUACULTURAL ENGINEERING
- The use of Artificial Neural Networks to estimate seismic damage and derive vulnerability functions for traditional masonry
- (2020) Tiago Miguel Ferreira et al. Frontiers of Structural and Civil Engineering
- Data-driven estimation of building energy consumption with multi-source heterogeneous data
- (2020) Yue Pan et al. APPLIED ENERGY
- Short-term prediction of building energy consumption employing an improved extreme gradient boosting model: A case study of an intake tower
- (2020) Hongfang Lu et al. ENERGY
- Predicting energy consumption in multiple buildings using machine learning for improving energy efficiency and sustainability
- (2020) Anh-Duc Pham et al. JOURNAL OF CLEANER PRODUCTION
- Artificial intelligence techniques and their application in oil and gas industry
- (2020) Sachin Choubey et al. ARTIFICIAL INTELLIGENCE REVIEW
- A hybrid deep meta-ensemble networks with application in electric utility industry load forecasting
- (2020) Shaohui Ma INFORMATION SCIENCES
- Sliding-window metaheuristic optimization-based forecast system for foreign exchange analysis
- (2019) Jui-Sheng Chou et al. SOFT COMPUTING
- Comparative study of different wavelet-based neural network models to predict sewage sludge quantity in wastewater treatment plant
- (2019) Maryam Zeinolabedini et al. ENVIRONMENTAL MONITORING AND ASSESSMENT
- Data-Driven Building Load Profiling and Energy Management
- (2019) Jin Zhu et al. Sustainable Cities and Society
- Modeling and forecasting building energy consumption: A review of data-driven techniques
- (2019) Mathieu Bourdeau et al. Sustainable Cities and Society
- Predictive modelling of building energy consumption based on a hybrid nature-inspired optimization algorithm
- (2019) Shidrokh Goudarzi et al. ENERGY AND BUILDINGS
- A methodology for energy multivariate time series forecasting in smart buildings based on feature selection
- (2019) Aurora González-Vidal et al. ENERGY AND BUILDINGS
- Energy optimization and greenhouse gas emissions mitigation for agricultural and horticultural systems in Northern Iran
- (2019) Fatemeh Mostashari-Rad et al. ENERGY
- Study on deep reinforcement learning techniques for building energy consumption forecasting
- (2019) Tao Liu et al. ENERGY AND BUILDINGS
- Prediction of Slope Stability Based on Hybrid PSO and LSSVM
- (2017) Xinhua Xue JOURNAL OF COMPUTING IN CIVIL ENGINEERING
- Prediction of residential building energy consumption: A neural network approach
- (2016) M.A. Rafe Biswas et al. ENERGY
- Engineering strength of fiber-reinforced soil estimated by swarm intelligence optimized regression system
- (2016) Jui-Sheng Chou et al. NEURAL COMPUTING & APPLICATIONS
- Improved probabilistic neural networks with self-adaptive strategies for transformer fault diagnosis problem
- (2016) Jiao-Hong Yi et al. Advances in Mechanical Engineering
- Self-adaptive extreme learning machine
- (2015) Gai-Ge Wang et al. NEURAL COMPUTING & APPLICATIONS
- Grey Wolf Optimizer
- (2014) Seyedali Mirjalili et al. ADVANCES IN ENGINEERING SOFTWARE
- Prediction of rainfall time series using modular soft computingmethods
- (2012) C.L. Wu et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now