نتایج جستجو برای: esn neural network

تعداد نتایج: 832316  

Journal: :international journal of smart electrical engineering 0
milad sasani my self

abstract forecasting electrical energy demand and consumption is one of the important decision-making tools in distributing companies for making contracts scheduling and purchasing electrical energy. this paper studies load consumption modeling in hamedan city province distribution network by applying esn neural network. weather forecasting data such as minimum day temperature, average day temp...

Abstract Forecasting electrical energy demand and consumption is one of the important decision-making tools in distributing companies for making contracts scheduling and purchasing electrical energy. This paper studies load consumption modeling in Hamedan city province distribution network by applying ESN neural network. Weather forecasting data such as minimum day temperature, average day temp...

2015
Xiaomin Xu Dongxiao Niu Ming Fu Huicong Xia Han Wu Guido Carpinelli

The uncertainty and regularity of wind power generation are caused by wind resources’ intermittent and randomness. Such volatility brings severe challenges to the wind power grid. The requirements for ultrashort-term and short-term wind power forecasting with high prediction accuracy of the model used, have great significance for reducing the phenomenon of abandoned wind power , optimizing the ...

2011
Ali Rodan Peter Tiño

Echo State Network (ESN) is a special type of recurrent neural network with fixed random recurrent part (reservoir) and a trainable reservoir-to-output readout mapping (typically obtained by linear regression). In this work we utilise an ensemble of ESNs with diverse reservoirs whose collective read-out is obtained through Negative Correlation Learning (NCL) of ensemble of Multi-Layer Perceptro...

2009
Friedhelm Schwenker Amr Labib

Echo state networks (ESN) and ensembles of neural networks are developed for the prediction of the monthly sunspots series. Through numerical evaluation on this benchmark data set it has been shown that the feedback ESN models outperform feedforward MLP. Furthermore, it is shown that median fusion lead to robust predictors, and even can improve the prediction accuracy of the best individual pre...

Journal: :CoRR 2017
Pau Vilimelis Aceituno Yan Gang Yang-Yu Liu

As one of the most important paradigms of recurrent neural networks, the echo state network (ESN) has been applied to a wide range of fields, from robotics to medicine to finance, and language processing. A key feature of the ESN paradigm is its reservoir —a directed and weighted network— that represents the connections between neurons and projects the input signals into a high dimensional spac...

Journal: :Open Journal of Astrophysics 2023

Modeling the dynamics of formation and evolution protostellar disks as well history stellar mass accretion typically involve numerical solution complex systems coupled differential equations. The resulting protostars is known to be highly episodic due recurrent instabilities also exhibits short timescale flickering. By leveraging strong predictive abilities neural networks, we extract some crit...

Journal: :Neural networks : the official journal of the International Neural Network Society 2007
Ganesh K. Venayagamoorthy

With deregulation and growth of the power industry, many power system elements such as generators, transmission lines, are driven to operate near their maximum capacity, especially those serving heavy load centres. Wide Area Controllers (WACs) using wide area or global signals can provide remote auxiliary control signals to local controllers such as automatic voltage regulators, power system st...

2009
Sawsan M. Mahmoud Ahmad Lotfi Nasser Sherkat Caroline S. Langensiepen Taha Osman

Pattern analysis and prediction of sensory data is becoming an increasing scientific challenge and a massive economical interest supports the need for better pattern mining techniques. The aim of this paper is to investigate efficient mining of useful information from a sensor network representing an ambient intelligence environment. The goal is to extract and predict behavioral patterns of a p...

2008
Michal Cernanský Peter Tiño

A lot of attention is now being focused on connectionist models known under the name “reservoir computing”. The most prominent example of these approaches is a recurrent neural network architecture called an echo state network (ESN). ESNs were successfully applied in several time series modeling tasks and according to the authors they performed exceptionally well. Multiple enhancements to stand...

نمودار تعداد نتایج جستجو در هر سال

با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید