Works matching DE "ENERGY consumption forecasting"
Results: 377
A review of the influencing factors of building energy consumption and the prediction and optimization of energy consumption.
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- AIMS Energy, 2025, v. 13, n. 1, p. 1, doi. 10.3934/energy.2025003
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Forecasting of energy consumption rate and battery stress under real-world traffic conditions using ANN model with different learning algorithms.
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- AIMS Energy, 2025, v. 13, n. 1, p. 1, doi. 10.3934/energy.2025005
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Machine Learning Applications in Building Energy Systems: Review and Prospects.
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- Buildings (2075-5309), 2025, v. 15, n. 4, p. 648, doi. 10.3390/buildings15040648
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MACLSTM: A Weather Attributes Enabled Recurrent Approach to Appliance-Level Energy Consumption Forecasting.
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- Computers, Materials & Continua, 2025, v. 82, n. 2, p. 2969, doi. 10.32604/cmc.2025.060230
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A Novel Grey Prediction Model: A Hybrid Approach Based on Extension of the Fractional Order Discrete Grey Power Model with the Polynomial-Driven and PSO-GWO Algorithm.
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- Fractal & Fractional, 2025, v. 9, n. 2, p. 120, doi. 10.3390/fractalfract9020120
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Seasonality, cointegration, and forecasting UK residential energy demand.
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- Scottish Journal of Political Economy, 1999, v. 46, n. 2, p. 185, doi. 10.1111/1467-9485.00128
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FORECASTING THE PATH OF U.S. CO<sub>2</sub> EMISSIONS USING STATE-LEVEL INFORMATION.
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- Review of Economics & Statistics, 2012, v. 94, n. 1, p. 172, doi. 10.1162/REST_a_00152
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Strategic appraisal of energy models for Mozambique.
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- International Journal of Energy Research, 2003, v. 27, n. 2, p. 173, doi. 10.1002/er.866
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Application of long short-term memory (LSTM) neural network based on deep learning for electricity energy consumption forecasting.
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- Turkish Journal of Electrical Engineering & Computer Sciences, 2022, v. 30, n. 1, p. 140, doi. 10.3906/elk-2011-14
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Optimizing Electric Vehicle (EV) Charging with Integrated Renewable Energy Sources: A Cloud-Based Forecasting Approach for Eco-Sustainability.
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- Mathematics (2227-7390), 2024, v. 12, n. 17, p. 2627, doi. 10.3390/math12172627
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Special Issue "Statistical Data Modeling and Machine Learning with Applications II".
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- Mathematics (2227-7390), 2023, v. 11, n. 12, p. 2775, doi. 10.3390/math11122775
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Development of Grey Machine Learning Models for Forecasting of Energy Consumption, Carbon Emission and Energy Generation for the Sustainable Development of Society.
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- Mathematics (2227-7390), 2023, v. 11, n. 6, p. 1505, doi. 10.3390/math11061505
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Energy Consumption Forecasts by Gradient Boosting Regression Trees.
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- Mathematics (2227-7390), 2023, v. 11, n. 5, p. 1068, doi. 10.3390/math11051068
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Forecasting of Electrical Energy Consumption in Slovakia.
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- Mathematics (2227-7390), 2022, v. 10, n. 4, p. N.PAG, doi. 10.3390/math10040577
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Expect: EXplainable Prediction Model for Energy ConsumpTion.
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- Mathematics (2227-7390), 2022, v. 10, n. 2, p. 248, doi. 10.3390/math10020248
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Comparison and Explanation of Forecasting Algorithms for Energy Time Series.
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- Mathematics (2227-7390), 2021, v. 9, n. 21, p. 2794, doi. 10.3390/math9212794
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Towards Optimal Supercomputer Energy Consumption Forecasting Method.
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- Mathematics (2227-7390), 2021, v. 9, n. 21, p. 2695, doi. 10.3390/math9212695
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COMPARISON OF SHORT-TERM FORECASTING METHODS OF ELECTRICITY CONSUMPTION IN MICROGRIDS .
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- Radio Electronics, Computer Science, Control, 2023, n. 1, p. 14, doi. 10.15588/1607-3274-2023-1-2
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Online energy consumption forecast for battery electric buses using a learning-free algebraic method.
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- Scientific Reports, 2025, v. 15, n. 1, p. 1, doi. 10.1038/s41598-024-82432-5
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A novel conformable fractional-order accumulation grey model and its applications in forecasting energy consumption of China.
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- Scientific Reports, 2024, v. 14, n. 1, p. 1, doi. 10.1038/s41598-024-82128-w
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Urban Water-Energy consumption Prediction Influenced by Climate Change utilizing an innovative deep learning method.
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- Scientific Reports, 2024, v. 14, n. 1, p. 1, doi. 10.1038/s41598-024-81836-7
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An innovative MGM–BPNN–ARIMA model for China's energy consumption structure forecasting from the perspective of compositional data.
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- Scientific Reports, 2024, v. 14, n. 1, p. 1, doi. 10.1038/s41598-024-58966-z
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LCA of the South African sugar industry.
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- Journal of Environmental Planning & Management, 2010, v. 53, n. 6, p. 793, doi. 10.1080/09640568.2010.488120
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Intelligent optimal demand response implemented by blockchain and cooperative game in microgrids.
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- International Transactions in Operational Research, 2024, v. 31, n. 6, p. 3704, doi. 10.1111/itor.13296
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An estimation method of available transfer capabilities from viewpoint of power system transient stability under deregulated environment.
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- Electrical Engineering in Japan, 2009, v. 167, n. 1, p. 66, doi. 10.1002/eej.20781
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Energy Consumption Load Forecasting Using a Level-Based Random Forest Classifier.
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- Symmetry (20738994), 2019, v. 11, n. 8, p. 956, doi. 10.3390/sym11080956
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Energy Consumption Forecasting in Commercial Buildings during the COVID-19 Pandemic: A Multivariate Multilayered Long-Short Term Memory Time-Series Model with Knowledge Injection.
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- Sustainability (2071-1050), 2023, v. 15, n. 17, p. 12951, doi. 10.3390/su151712951
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Energy Consumption Prediction and Control Algorithm for Hybrid Electric Vehicles Based on an Equivalent Minimum Fuel Consumption Model.
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- Sustainability (2071-1050), 2023, v. 15, n. 12, p. 9394, doi. 10.3390/su15129394
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Partially Linear Component Support Vector Machine for Primary Energy Consumption Forecasting of the Electric Power Sector in the United States.
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- Sustainability (2071-1050), 2023, v. 15, n. 9, p. 7086, doi. 10.3390/su15097086
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Wild Horse Optimization with Deep Learning-Driven Short-Term Load Forecasting Scheme for Smart Grids.
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- Sustainability (2071-1050), 2023, v. 15, n. 2, p. 1524, doi. 10.3390/su15021524
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Grey Multivariable Prediction Model of Energy Consumption with Different Fractional Orders.
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- Sustainability (2071-1050), 2022, v. 14, n. 24, p. 16426, doi. 10.3390/su142416426
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An Analysis of the Energy Consumption Forecasting Problem in Smart Buildings Using LSTM.
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- Sustainability (2071-1050), 2022, v. 14, n. 20, p. N.PAG, doi. 10.3390/su142013358
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Neuro-Cybernetic System for Forecasting Electricity Consumption in the Bulgarian National Power System.
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- Sustainability (2071-1050), 2022, v. 14, n. 17, p. 11074, doi. 10.3390/su141711074
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A New Deep Learning Restricted Boltzmann Machine for Energy Consumption Forecasting.
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- Sustainability (2071-1050), 2022, v. 14, n. 16, p. 10081, doi. 10.3390/su141610081
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Development of Simplified Building Energy Prediction Model to Support Policymaking in South Korea—Case Study for Office Buildings.
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- Sustainability (2071-1050), 2022, v. 14, n. 10, p. 6000, doi. 10.3390/su14106000
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A New Method of Predicting the Energy Consumption of Additive Manufacturing considering the Component Working State.
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- Sustainability (2071-1050), 2022, v. 14, n. 7, p. 3757, doi. 10.3390/su14073757
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Evolution and Forecasting of the Renewable Energy Consumption in the Frame of Sustainable Development: EU vs. Romania.
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- Sustainability (2071-1050), 2021, v. 13, n. 18, p. 10327, doi. 10.3390/su131810327
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An Improved Forecasting Method and Application of China's Energy Consumption under the Carbon Peak Target.
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- Sustainability (2071-1050), 2021, v. 13, n. 15, p. 8670, doi. 10.3390/su13158670
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Sustainable Energy-Related Infrastructure Development in the Mekong Subregion: Key Drivers and Policy Implications.
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- Sustainability (2071-1050), 2021, v. 13, n. 10, p. 5720, doi. 10.3390/su13105720
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Forecasting Clean Energy Consumption in China by 2025: Using Improved Grey Model GM (1, N).
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- Sustainability (2071-1050), 2020, v. 12, n. 2, p. 698, doi. 10.3390/su12020698
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Daily Average Wind Power Interval Forecasts Based on an Optimal Adaptive-Network-Based Fuzzy Inference System and Singular Spectrum Analysis.
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- Sustainability (2071-1050), 2016, v. 8, n. 2, p. 125, doi. 10.3390/su8020125
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Ten Reasons to Take Peak Oil Seriously.
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- Sustainability (2071-1050), 2013, v. 5, n. 2, p. 664, doi. 10.3390/su5020664
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SEGMENTAREA PIEŢEI CONSUMATORILOR DE GAZE NATURALE DIN ROMÂNIA.
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- Review of Management & Economic Engineering, 2012, v. 11, n. 3, p. 207
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FORECASTING ENERGY CONSUMPTION IN TAMIL NADU USING HYBRID HEURISTIC BASED REGRESSION MODEL.
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- Thermal Science, 2019, v. 23, n. 5B, p. 2885, doi. 10.2298/TSCI171117085S
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LONG-TERM PREDICTIONS OF THE ENERGY DEVELOPMENT Possibilities and Challenges.
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- Thermal Science, 2016, v. 20, p. S69, doi. 10.2298/TSCI160126017K
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A novel power-driven fractional accumulated grey model and its application in forecasting wind energy consumption of China.
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- PLoS ONE, 2019, v. 14, n. 12, p. 1, doi. 10.1371/journal.pone.0225362
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Forecasting electrical energy consumption using efficient Gaussian processes: A case study.
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- Journal of Electrical Systems, 2020, v. 16, n. 1, p. 30
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Machine learning for electric energy consumption forecasting: Application to the Paraguayan system.
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- Logic Journal of the IGPL, 2024, v. 32, n. 6, p. 1048, doi. 10.1093/jigpal/jzae035
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Obsolescence in Urban Energy Infrastructures: The Influence of Scaling Laws on Consumption Forecasting.
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- Journal of Urban Technology, 2015, v. 22, n. 2, p. 3, doi. 10.1080/10630732.2014.955340
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Levinson’s Recursion for Forecasting Electrical Energy Consumption in the Household Sector in Indonesia.
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- International Review of Electrical Engineering, 2023, v. 18, n. 5, p. 347, doi. 10.15866/iree.v18i5.22869
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