Active Learning Using a Constructive Neural Network Algorithm

2009 ◽  
pp. 193-206 ◽  
Author(s):  
José L. Subirats ◽  
Leonardo Franco ◽  
Ignacio Molina ◽  
José M. Jerez
Keyword(s):  
Neural Network ◽  
Active Learning ◽  
Network Algorithm ◽  
Neural Network Algorithm

Active Learning Using a Constructive Neural Network Algorithm

2008 ◽  
pp. 803-811 ◽  
Author(s):  
José Luis Subirats ◽  
Leonardo Franco ◽  
Ignacio Molina Conde ◽  
José M. Jerez
Keyword(s):  
Neural Network ◽  
Active Learning ◽  
Network Algorithm ◽  
Neural Network Algorithm

A New Back-Propagation Neural Network Algorithm for a Big Data Environment Based on Punishing Characterized Active Learning Strategy

2013 ◽  
Vol 4 (4) ◽  
pp. 32-45 ◽  
Author(s):  
Qiuhong Zhao ◽  
Feng Ye ◽  
Shouyang Wang
Keyword(s):  
Neural Network ◽  
Big Data ◽  
Active Learning ◽  
Learning Strategy ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Bp Algorithm ◽  
Network Algorithm ◽  
Neural Network Algorithm ◽  
Active Learning Strategy

This paper introduces the active learning strategy to the classical back-propagation neural network algorithm and proposes punishing-characterized active learning Back-Propagation (BP) Algorithm (PCAL-BP) to adapt to big data conditions. The PCAL-BP algorithm selects samples and punishments based on the absolute value of the prediction error to improve the efficiency of learning complex data. This approach involves reducing learning time and provides high precision. Numerical analysis shows that the PCAL-BP algorithm is superior to the classical BP neural network algorithm in both learning efficiency and precision. This advantage is more prominent in the case of extensive sample data. In addition, the PCAL-BP algorithm is compared with 16 types of classical classification algorithms. It performs better than 14 types of algorithms in the classification experiment used here. The experimental results also indicate that the prediction accuracy of the PCAL-BP algorithm can continue to increase with an increase in sample size.

A NEURAL NETWORK ALGORITHM FOR DENSITY MEASUREMENT OF MULTIPHASE FLOW

2012 ◽  
Vol 24 (2) ◽  
pp. 89-103 ◽  
Author(s):  
Nabeel Al-Rawahi ◽  
Mahmoud Meribout ◽  
Ahmed Al-Naamany ◽  
Ali Al-Bimani ◽  
Adel Meribout
Keyword(s):  
Neural Network ◽  
Multiphase Flow ◽  
Density Measurement ◽  
Network Algorithm ◽  
Neural Network Algorithm

Logistics demand forecasting model based on improved neural network algorithm

2020 ◽  
pp. 1-11
Author(s):  
Hongjiang Ma ◽  
Xu Luo
Keyword(s):  
Neural Network ◽  
Influencing Factor ◽  
Demand Forecasting ◽  
Forecasting Model ◽  
Logistics System ◽  
Model Based ◽  
Network Algorithm ◽  
Neural Network Algorithm ◽  
Demand Forecasting Model ◽  
Logistics Demand

The irrationality between the procurement and distribution of the logistics system increases unnecessary circulation links and greatly reduces logistics efficiency, which not only causes a waste of transportation resources, but also increases logistics costs. In order to improve the operation efficiency of the logistics system, based on the improved neural network algorithm, this paper combines the logistic regression algorithm to construct a logistics demand forecasting model based on the improved neural network algorithm. Moreover, according to the characteristics of the complexity of the data in the data mining task itself, this article optimizes the ladder network structure, and combines its supervisory decision-making part with the shallow network to make the model more suitable for logistics demand forecasting. In addition, this paper analyzes the performance of the model based on examples and uses the grey relational analysis method to give the degree of correlation between each influencing factor and logistics demand. The research results show that the model constructed in this paper is reasonable and can be analyzed from a practical perspective.

Modeling the SOFC by BP neural network algorithm

2021 ◽  
Author(s):  
Shaohui Song ◽  
Xingyu Xiong ◽  
Xin Wu ◽  
Zhenzhong Xue
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Network Algorithm ◽  
Neural Network Algorithm
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