Add to ORKGIn this paper, carbon emissions and the related problems are studied based on carbon emission time series data and the chaos theory, in order to make clear the relationship among the data, and we reconstruct the time series by phase space reconstruction. Finally, the predicting model of the carbon emission is established with BP neural network. The simulation results show that the hybrid of chaos theory and BP neural network can be used to fit and predict the carbon emissions time series without considering other factors, which is easier and more accurate than other predicting method
Abstract Artificial neural network (ANN) provides a new way for mine water inflow prediction. Howeve...
In view of the nonlinear characteristics of gas emission in a coal working face, a prediction method...
AbstractEffect factors on coal and gas outburst are analyzed using grey correlation method so as to ...
In this paper, carbon emissions and the related problems are studied based on carbon emission time s...
AbstractIn order to realize the dynamic prediction on gas emission rate and avoid constructing a mod...
Closely connected to human carbon emissions, global climate change is affecting regional economic an...
A unique technique based on chaos theory and artificial neural networks (ANN) is developed to analys...
Theoretic analysis shows that the output power of the distributed generation system is nonlinear and...
The goal of reaching the peak of carbon in the construction industry is urgent. However, the researc...
Global climate change, which mainly effected by human carbon emissions, would affect the regional ec...
As a major province of energy consumption and carbon emission, Jiangsu Province is also a major prov...
In this paper, the BP neural network model is established to predict the carbon trading price and ca...
Excessive carbon emissions seriously threaten the sustainable development of society and the environ...
This work aims at combining the Chaos theory postulates and Artificial Neural Networks classificatio...
With the increasingly drastic competition in the market, consumers ’ minds are more and more complex...
Abstract Artificial neural network (ANN) provides a new way for mine water inflow prediction. Howeve...
In view of the nonlinear characteristics of gas emission in a coal working face, a prediction method...
AbstractEffect factors on coal and gas outburst are analyzed using grey correlation method so as to ...
In this paper, carbon emissions and the related problems are studied based on carbon emission time s...
AbstractIn order to realize the dynamic prediction on gas emission rate and avoid constructing a mod...
Closely connected to human carbon emissions, global climate change is affecting regional economic an...
A unique technique based on chaos theory and artificial neural networks (ANN) is developed to analys...
Theoretic analysis shows that the output power of the distributed generation system is nonlinear and...
The goal of reaching the peak of carbon in the construction industry is urgent. However, the researc...
Global climate change, which mainly effected by human carbon emissions, would affect the regional ec...
As a major province of energy consumption and carbon emission, Jiangsu Province is also a major prov...
In this paper, the BP neural network model is established to predict the carbon trading price and ca...
Excessive carbon emissions seriously threaten the sustainable development of society and the environ...
This work aims at combining the Chaos theory postulates and Artificial Neural Networks classificatio...
With the increasingly drastic competition in the market, consumers ’ minds are more and more complex...
Abstract Artificial neural network (ANN) provides a new way for mine water inflow prediction. Howeve...
In view of the nonlinear characteristics of gas emission in a coal working face, a prediction method...
AbstractEffect factors on coal and gas outburst are analyzed using grey correlation method so as to ...