ARTÍCULO
TITULO

Belief Networks - A New Uncertainty Measure for Belief Networks with Applications to Optimal Evidential Inferencing

Liu    
J    
Maluf    
D A    
Desmarais    
M C    

Resumen

No disponible

 Artículos similares

       
 
Sultan Ahmed Almalki, Ahmed Abdel-Rahim and Frederick T. Sheldon    
The adoption of cooperative intelligent transportation systems (cITSs) improves road safety and traffic efficiency. Vehicles connected to cITS form vehicular ad hoc networks (VANET) to exchange messages. Like other networks and systems, cITSs are targete... ver más
Revista: Algorithms

 
Tu T. Nguyen, Pham Thanh Tung, Nguyen Ngoc Tan, Nguyen Ngoc Linh and Trinh Tu Luc    
The applications of the deep belief network (DBN) for addressing practical engineering issues have recently emerged all over the world thanks to its accuracy and availability of data. In this paper, a predictive model using DBN was employed to investigat... ver más
Revista: Infrastructures

 
Shenglong Zhang    
A high-accuracy objective function evaluation method is crucial in ship hull form optimization. This study proposes a novel approximate ship hull form optimization framework using the deep learning technology, deep belief network algorithm. To illustrate... ver más

 
Hussein Abdel-Jaber, Disha Devassy, Azhar Al Salam, Lamya Hidaytallah and Malak EL-Amir    
Deep learning uses artificial neural networks to recognize patterns and learn from them to make decisions. Deep learning is a type of machine learning that uses artificial neural networks to mimic the human brain. It uses machine learning methods such as... ver más
Revista: Algorithms

 
Neofytos Dimitriou and Ognjen Arandjelovic    
Normalization as a layer within neural networks has over the years demonstrated its effectiveness in neural network optimization across a wide range of different tasks, with one of the most successful approaches being that of batch normalization. The con... ver más
Revista: Information