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Deep echo state network (deepesn): A brief survey
The study of deep recurrent neural networks (RNNs) and, in particular, of deep Reservoir
Computing (RC) is gaining an increasing research attention in the neural networks …
Computing (RC) is gaining an increasing research attention in the neural networks …
Time series analytics using sliding window metaheuristic optimization-based machine learning system for identifying building energy consumption patterns
Smart grids are a promising solution to the rapidly growing power demand because they can
considerably increase building energy efficiency. This study developed a novel time-series …
considerably increase building energy efficiency. This study developed a novel time-series …
Electric efficiency indicators and carbon dioxide emission factors for power generation by fossil and renewable energy sources on hourly basis
The power system has faced unprecedented challenges in the last decade caused by many
factors: the introduction of the open electricity market, the diffusion of distributed generation …
factors: the introduction of the open electricity market, the diffusion of distributed generation …
Integrated management of urban resources toward Net-Zero smart cities considering renewable energies uncertainty and modeling in Digital Twin
X Zhao, Y Zhang - Sustainable Energy Technologies and Assessments, 2024 - Elsevier
This research introduces a groundbreaking strategy for urban microgrid (MG) management
and social economics, focusing on enhancing energy efficiency, reliability, and steering …
and social economics, focusing on enhancing energy efficiency, reliability, and steering …
Energy consumption prediction of office buildings based on echo state networks
In this paper, energy consumption of an office building is predicted based on echo state
networks (ESNs). Energy consumption of the office building is divided into consumptions …
networks (ESNs). Energy consumption of the office building is divided into consumptions …
Smart grid data analytics framework for increasing energy savings in residential buildings
Human energy consumption has gradually increased greenhouse gas concentrations and is
considered the main cause of global warming. Currently, the building sector is a major …
considered the main cause of global warming. Currently, the building sector is a major …
Genetic algorithm optimized double-reservoir echo state network for multi-regime time series prediction
In prognostics and health management (PHM), the sensor measurement time series of
equipment is collected, and predicting future sensor measurements accurately is crucial to …
equipment is collected, and predicting future sensor measurements accurately is crucial to …
Metaheuristic optimization within machine learning-based classification system for early warnings related to geotechnical problems
This study proposes a novel classification system integrating swarm and metaheuristic
intelligence, ie, a smart firefly algorithm (SFA), with a least squares support vector machine …
intelligence, ie, a smart firefly algorithm (SFA), with a least squares support vector machine …
Real-time pricing scheme based on Stackelberg game in smart grid with multiple power retailers
Y Dai, Y Gao, H Gao, H Zhu - Neurocomputing, 2017 - Elsevier
As an essential characteristic of smart grid, demand response may reduce the power
consumption of users and the operating expense of power suppliers. Real-time pricing is the …
consumption of users and the operating expense of power suppliers. Real-time pricing is the …
[HTML][HTML] Performance indicators of electricity generation at country level—The case of Italy
Power Grids face significant variability in their operation, especially where there are high
proportions of non-programmable renewable energy sources constituting the electricity mix …
proportions of non-programmable renewable energy sources constituting the electricity mix …