Yield prediction of “Thermal-dissolution based carbon enrichment” treatment on biomass wastes through coupled model of artificial neural network and AdaBoost

2022 ◽  
Vol 343 ◽  
pp. 126083
Author(s):  
Zhenzhong Hu ◽  
Yue Yuan ◽  
Xian Li ◽  
Zhengjun Tu ◽  
Omar Donovan Dacres ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Coupled Model ◽  
Yield Prediction ◽  
Thermal Dissolution ◽  
Artificial Neural

scholarly journals Application of Artificial Neural Network for Yield Prediction of Lipase-Catalyzed Synthesis of Dioctyl Adipate

2009 ◽  
Vol 158 (3) ◽  
pp. 722-735 ◽  
Author(s):  
Mohd Basyaruddin Abdul Rahman ◽  
Naz Chaibakhsh ◽  
Mahiran Basri ◽  
Abu Bakar Salleh ◽  
Raja Noor Zaliha Raja Abdul Rahman
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Yield Prediction ◽  
Artificial Neural ◽  
Dioctyl Adipate

Seed yield prediction of sesame using artificial neural network

2015 ◽  
Vol 68 ◽  
pp. 89-96 ◽  
Author(s):  
Samad Emamgholizadeh ◽  
M. Parsaeian ◽  
Mehdi Baradaran
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Seed Yield ◽  
Yield Prediction ◽  
Artificial Neural

scholarly journals Coupled Model of Artificial Neural Network and Grey Model for Tendency Prediction of Labor Turnover

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Yueru Ma ◽  
Lijun Peng
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Coupled Model ◽  
Labor Turnover ◽  
Grey Theory ◽  
Random Disturbance ◽  
Grey Prediction ◽  
Ann Model ◽  
Model Approximation ◽  
Artificial Neural

The tendency of labor turnover in the Chinese enterprise shows the characteristics of seasonal fluctuations and irregular distribution of various factors, especially the Chinese traditional social and cultural characteristics. In this paper, we present a coupled model for the tendency prediction of labor turnover. In the model, a time series of tendency prediction of labor turnover was expressed as trend item and its random item. Trend item of tendency prediction of labor turnover is predicted using Grey theory. Random item of trend item is calculated by artificial neural network model (ANN). A case study is presented by the data of 24 months in a Chinese matured enterprise. The model uses the advantages of “accumulative generation” of a Grey prediction method, which weakens the original sequence of random disturbance factors and increases the regularity of data. It also takes full advantage of the ANN model approximation performance, which has a capacity to solve economic problems rapidly, describes the nonlinear relationship easily, and avoids the defects of Grey theory.

Sign in / Sign up

Export Citation Format

Share Document