Nonlinear maximum likelihood estimation of electricity spot prices using recurrent neural networks

2010 ◽  
Vol 20 (1) ◽  
pp. 79-89 ◽  
Author(s):  
Derrick Mirikitani ◽  
Nikolay Nikolaev
Keyword(s):  
Neural Networks ◽  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Recurrent Neural Networks ◽  
Likelihood Estimation ◽  
Spot Prices

scholarly journals Improved Neural Networks Based on Mutual Information via Information Geometry

Algorithms ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 103
Author(s):  
Meng Wang ◽  
Chuang-Bai Xiao ◽  
Zhen-Hu Ning ◽  
Jing Yu ◽  
Ya-Hao Zhang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Mutual Information ◽  
Likelihood Estimation ◽  
Information Geometry ◽  
Geodesic Line ◽  
Classification And Regression ◽  
Theory Of Information

This paper presents a new algorithm based on the theory of mutual information and information geometry. This algorithm places emphasis on adaptive mutual information estimation and maximum likelihood estimation. With the theory of information geometry, we adjust the mutual information along the geodesic line. Finally, we evaluate our proposal using empirical datasets that are dedicated for classification and regression. The results show that our algorithm contributes to a significant improvement over existing methods.

Sign in / Sign up

Export Citation Format

Share Document