Monitoring of long-term static deformation data of Fei-Tsui arch dam using artificial neural network-based approaches

2011 ◽  
Vol 20 (3) ◽  
pp. 282-303 ◽  
Author(s):  
Ching-Yun Kao ◽  
Chin-Hsiung Loh
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Arch Dam ◽  
Static Deformation ◽  
Artificial Neural

Using an artificial neural network to patternize long-term fisheries data from South Korea

2005 ◽  
Vol 67 (3) ◽  
pp. 382-389
Author(s):  
Karen Hyun ◽  
Mi-Young Song ◽  
Suam Kim ◽  
Tae-Soo Chon
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
South Korea ◽  
Artificial Neural

AN ARTIFICIAL NEURAL NETWORK APPROACH TO HOTEL EMPLOYEE SATISFACTION: THE CASE OF CHINA

2008 ◽  
Vol 36 (4) ◽  
pp. 467-482 ◽  
Author(s):  
Xizhou Tian ◽  
Yongjian Pu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Employee Satisfaction ◽  
High Rate ◽  
Neural Network Approach ◽  
Artificial Neural ◽  
Hotel Employee ◽  
And Gender ◽  
Artificial Neural Network Ann

At present, the hotel employment sector in China has a high rate of employee turnover compared to other services. This is not unlike other countries. The reason for the turnover among hotel employees may be lower worker satisfaction resulting in decreased – or no – loyalty to employers. This study was based on an Artificial Neural Network (ANN). The factors influencing employee satisfaction were examined and the impacts of demographic characteristics on hotel employee satisfaction were analyzed. Results show that hotel employee satisfaction in China is low, hotel employee satisfaction differs by age and gender, and that professional development opportunities for employees and the long-term growth prospects of the hotels themselves are the most important contributors to employee satisfaction. On the basis of these findings, several recommendations for improving employee satisfaction, thereby sustaining the long-term economic health of China's hospitality industry, are provided.

Long-Term Sales Forecast Method Based on Grey Model and Artificial Neural Network

2013 ◽  
Vol 385-386 ◽  
pp. 1726-1729
Author(s):  
Yi Jun Wang ◽  
Hong Ying Tang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Simulation Experiment ◽  
Grey Model ◽  
Forecast Method ◽  
Sales Forecast ◽  
Long Time ◽  
Artificial Neural ◽  
The U.S

Long-term sales forecasting is a problem that has been focused on for a long time. In order to forecast the long-term sales of an industry or an enterprise accurately, a new method based on Grey Model and Artificial Neural Network is proposed in this paper. The effectiveness and feasibility of the proposed method is verified by simulation experiment using sales data of the manufacturing and trade industry provided by the U.S. government.

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