Deep echo state network (deepesn): A brief survey

C Gallicchio, A Micheli - arxiv preprint arxiv:1712.04323, 2017‏ - arxiv.org
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 …

Time series analytics using sliding window metaheuristic optimization-based machine learning system for identifying building energy consumption patterns

JS Chou, NT Ngo - Applied energy, 2016‏ - Elsevier
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 …

Electric efficiency indicators and carbon dioxide emission factors for power generation by fossil and renewable energy sources on hourly basis

E Marrasso, C Roselli, M Sasso - Energy Conversion and Management, 2019‏ - Elsevier
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 …

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 …

Energy consumption prediction of office buildings based on echo state networks

G Shi, D Liu, Q Wei - Neurocomputing, 2016‏ - Elsevier
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 …

Smart grid data analytics framework for increasing energy savings in residential buildings

JS Chou, NT Ngo - Automation in construction, 2016‏ - Elsevier
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 …

Genetic algorithm optimized double-reservoir echo state network for multi-regime time series prediction

S Zhong, X **e, L Lin, F Wang - Neurocomputing, 2017‏ - Elsevier
In prognostics and health management (PHM), the sensor measurement time series of
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

JS Chou, JPP Thedja - Automation in Construction, 2016‏ - Elsevier
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 …

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 …

[HTML][HTML] Performance indicators of electricity generation at country level—The case of Italy

M Noussan, R Roberto, B Nastasi - Energies, 2018‏ - mdpi.com
Power Grids face significant variability in their operation, especially where there are high
proportions of non-programmable renewable energy sources constituting the electricity mix …