A Neural Network Model for Forecasting CO2 Emission

Three NN-based predictors have been developed and applied to short-term forecasting of daily peak load, total daily energy, and hourly daily load, respectively.. Three months of

It includes all input units em- ployed in the representation for the HNM, except the unit which represents the load at 1 week and 24 h be- hind the hour whose load is to be

[10] describe the third genera- tion of an hourly short-term load forecasting system, named artificial neural network short-term load fore- caster (ANNSTLF).. Its architecture

We present a novel approach, using a Generalized Regression Neural Networks (GRNN) ensemble to the forecasting of time series and future volatility.. The remainder of this paper

In this paper, genetic algorithm based artificial neural network hybrid prediction model is proposed to foretell surface roughness and tool wear.. A multiple

For the design of the Dumb and Deaf Special Interface (DDSI) Expert Systems, the neural network model is implemented.. Architecture of

Using the ANN model developed, rainfall from 1 to 6 h was forecasted for 75 rain gauge stations (as forecast point) in Bangkok, Thailand, using continuous hourly rainfall data...

In this paper Ontario electricity market is used to predict one hour a head electricity price that is a very important issue for power generation and electricity markets,