Results 141 to 150 of about 10,057,169 (215)

Peer-to-Peer Energy Trading Using Prediction Intervals of Renewable Energy Generation

IEEE Transactions on Smart Grid, 2023
The rapid development of renewable energy generation and demand side flexible resource makes the operation of distribution network and the organisation of power market facing greater uncertainty challenges.
Yanbo Jia, Can Wan, Wenkang Cui, Yonghua Song, Ping Ju   +4 more
openaire   +2 more sources

Preprocessing Energy Intervals on Spectrum for Real-Time Radionuclide Identification

IEEE Transactions on Nuclear Science, 2021
In this study, we present a preprocess method using radiation energy intervals on a gamma-ray spectrum based on a deep learning algorithm to achieve real-time radionuclide identification.
Inyong Kwon, D. Shin, Jin-Hyu Oh, Chang-Hwoi Kim, Hyeonmin Kim   +4 more
semanticscholar   +1 more source

Confidence intervals of energies predicted by MODal ENergy Analysis method

Journal of Sound and Vibration, 2021
Abstract MODal ENergy Analysis (MODENA) was previously developed in the same framework as Statistical Energy Analysis (SEA) and Statistical modal Energy distribution Analysis (SmEdA) methods. It deals with energy exchanges between weakly coupled subsystems in vibro-acoustics.
N. Totaro, J.L. Guyader
openaire   +1 more source

A deep learning framework for building energy consumption forecast

, 2021
Increasing global building energy demand, with the related economic and environmental impact, upsurges the need for the design of reliable energy demand forecast models. This work presents k CNN-LSTM, a deep learning framework that operates on the energy
Nivethitha Somu, Gauthama Raman M R, K. Ramamritham   +2 more
semanticscholar   +1 more source

Two-Timescale Dynamic Energy and Reserve Dispatch With Wind Power and Energy Storage

IEEE Transactions on Sustainable Energy, 2023
The integration of volatile renewable resources and energy storage entails making dispatch decisions for conventional coal-fired units and fast-response devices in different timescales.
Zhongjie Guo, Wei Wei, M. Shahidehpour, Laijun Chen, S. Mei   +4 more
semanticscholar   +1 more source

Energy-efficient interspike interval codes

Neurocomputing, 2005
We investigate the energy efficiency of interspike interval (ISI) neural codes. Using the hypothesis that nature maximizes the energy efficiency of information processing, it is possible to derive neuronal firing frequencies which maximize the information/energy ratio.
Patrick Crotty, William B Levy
openaire   +1 more source

EECP-EI: energy-efficient clustering protocol based on energy intervals for wireless sensor networks

International Congress on Information and Communication Technology, 2019
Wireless Sensor Network is comprised of sensor nodes with a limited energy supply in the form of built-in batteries. Efficient utilization of limited energy supply of sensor nodes is one of the key design issues in wireless sensor networks. Hence, energy
Muhammad Ali Khan, M. Qureshi, I. Raza, S. Hussain   +3 more
semanticscholar   +1 more source

Low-Energy Diets and Prolonged QT Intervals

JAMA: The Journal of the American Medical Association, 1987
To the Editor.— In a recent review entitled "Prolonged QT-Interval Syndromes," 1 the author indicates that "prolongation of the QT interval, malignant ventricular arrhythmias, and unexpected sudden death have been reported in patients who have lost considerable weight on the very-low-energy liquid protein diets." Dr Moss states that "sustained use of ...
S, Frank, J A, Colliver, A, Frank
openaire   +2 more sources

Review of integration of small modular reactors in renewable energy microgrids

Renewable & Sustainable Energy Reviews, 2021
Integration of renewable energy sources in the form of microgrids can increase the resilience of power systems and decrease their carbon footprints.
D. Michaelson, J. Jiang
semanticscholar   +1 more source

A novel prediction intervals method integrating an error & self-feedback extreme learning machine with particle swarm optimization for energy consumption robust prediction

Energy, 2018
Nowadays, petrochemical industries with many integrated units and equipment have characteristics of high uncertainty and nonlinearity. Therefore, it becomes more and more difficult to make reliable and accurate point measurement of energy modeling.
Yuan Xu, Mingqing Zhang, Ye Liangliang, Qunxiong Zhu, Zhiqiang Geng, Yanlin He, Yongming Han   +6 more
semanticscholar   +1 more source