Results 71 to 80 of about 9,783,476 (167)

Prediction of the optimal hybrid train trajectory by using artificial neural network models

IET Intelligent Transport Systems
This paper presents the development and validation of two artificial neural networks (ANN) models, utilising time and power‐based architectures, to accurately predict key parameters of a hydrogen hybrid train profile and its optimal trajectory.
Tajud Din, Zhongbei Tian, Syed Muhammad Ali Mansur Bukhari, Misbahud Din, Stuart Hillmansen, Clive Roberts   +5 more
doaj   +1 more source

Day-ahead photovoltaic power generation forecasting with the HWGC-WPD-LSTM hybrid model assisted by wavelet packet decomposition and improved similar day method

Engineering Science and Technology, an International Journal
Precisely forecasting output of solar photovoltaics is crucial for (i) effective solar power management, (ii) integration into the electrical grid, (iii) flexible allocation of power resources.
Ruxue Bai, Jinsong Li, Jinsong Liu, Yuetao Shi, Suoying He, Wei Wei   +5 more
doaj   +1 more source

Hybrid machine learning model combining of CNN-LSTM-RF for time series forecasting of Solar Power Generation

e-Prime: Advances in Electrical Engineering, Electronics and Energy
Forecasting solar power generation (SPG) is vital for the development and planning of power systems, offering significant benefits in terms of technical performance and financial efficiency.
Mobarak Abumohsen, Amani Yousef Owda, Majdi Owda, Ahmad Abumihsan   +3 more
doaj   +1 more source

On relation between the power mean and the logarithmic mean

, 2010
碩士假設x及y是不同的正數，則 Mp = Mp (x , y) 稱冪平均數， L = L (x , y) 稱對數平均數。 Chang[2]已證明 : 在某些限制下的x和y，當q0，Mp < L 。 我們將證明在某些限制下的x和y，當q 0，L > Mp。If x , y are distinct positive numbers, then Mp= Mp (x , y) is called the power mean of x and y .
李玄楨; Lee, Hsuan-chen
core   +1 more source

Strengthening the resilience and adaptive capacity of societies at risk from hybrid threats [PDF]

, 2021
How would the civilian population of a specific country respond to significant disruptions caused by hybrid threats? This paper explores different response scenarios and considers what can be done to strengthen the resilience and adaptive capacities of a
de Coning, Cedric
core  

Sizing and Energy Management of a Hybrid Locomotive Based on Flywheel and Accumulators [PDF]

, 2009
The French National Railways Company (SNCF) is interested in the design of a hybrid locomotive based on various storage devices (accumulator, flywheel, and ultracapacitor) and fed by a diesel generator.
Jaafar, Amine, Sareni, Bruno, Roboam, Xavier, Jeunesse, A., Jeunesse, Alain, Akli, Cossi Rockys, B. Sareni, A. Jeunesse, A. Jaafar, X. Roboam, C.R. Akli   +10 more
core   +1 more source

A low cost air hybrid concept [PDF]

, 2010
This article is a pre-print version of the full and final article which is available at the link below.Copyright © 2010 Institut français du pétrole Permission to make digital or hard copies of part or all of this work for personal or classroom use is ...
Lee, CY, Ma, T, Zhao H., Zhao, H, Lee C. Y., C. Y. Lee, H. Zhao, Ma T., T. Ma, Ma, T., Lee, C. Y., Zhao, H.   +11 more
core   +1 more source

Enabling Modular Simulation of Hybrid Power Plants by Pre-Defined Interfaces for FMU

2633Hybrid power plants combine energy production, storage, and consumption into a single power plant, providing more flexibility in power generation and utilisation, leading to increased capacity factors.
Requate, Niklas, Jersch, Torben, Wiens, Marcus   +2 more
core   +1 more source

Empowering Wind Energy Output Optimization: Comparative Assessment of Hybrid Artificial Intelligence Models Towards Wind Speed Forecasting Accuracy

Energies
Wind power forecasting is essential for the reliable and efficient operation of wind farms based on power grids, which is significantly important for stakeholders like wind farm owners, power pools, and power traders.
Latif Bukari Rashid, Shafiqur Rehman, Mohamed E. Zayed, Rashad Ibrahim, Fakebba Drammeh, S. M. Shalaby, Iqbal M. Mujtaba   +6 more
doaj   +1 more source

Dung beetle optimization algorithm-based hybrid deep learning model for ultra-short-term PV power prediction

iScience
Summary: A hybrid model combining self-attention temporal convolutional networks (SATCN) with bidirectional long short-term memory (BiLSTM) networks was developed to improve the accuracy of ultra-short-term photovoltaic (PV) power prediction.
Rui Quan, Zhizhuo Qiu, Hang Wan, Zhiyu Yang, Xuerong Li   +4 more
doaj   +1 more source