STUDY ON CHARACTERISTICS OF A WAVE PREDICTION SYSTEM BASED ON NEURAL NETWORK ALONG THE COAST OF JAPAN

Author(s):  
Yusuke IGARASHI ◽  
Yoshimitsu TAJIMA
Author(s):  
Tracey H. A. TOM ◽  
Hajime MASE ◽  
Ai IKEMOTO ◽  
Takehisa SAITOH ◽  
Koji KAWASAKI ◽  
...  

Author(s):  
Yusuke IGARASHI ◽  
Akira IMAI ◽  
Atsushi ITO ◽  
Hiroyuki KAITSU

Author(s):  
Sudarshan Nandy ◽  
Mainak Adhikari ◽  
Venki Balasubramanian ◽  
Varun G. Menon ◽  
Xingwang Li ◽  
...  

Author(s):  
May Liana ◽  
Christine Sanjaya ◽  
Agus Widodo ◽  
Marshall Martinus

XYZ Company has a program to predict leasing income that only predict in constant condition where every tenant assumed for leasing renewal. This research is done to build accurate income prediction system that accommodate in making strategic decision towards the company. Premier data collecting is through direct interview with the company management. The analysis is through data training from the previous years to build neural network model. The analysis result shows that this model has produced error total value that is smaller than the previous error total value in years before. Therefore, it could be concluded that data mining with neural network technique that produced more accurate leasing income that could help the company making decision based on the hidden information in the database.


2021 ◽  
pp. 291-302
Author(s):  
Mauricio Andrés Gómez Zuluaga ◽  
Ahmad Ordikhani ◽  
Christoph Bauer ◽  
Peter Glösekötter

Applied laser ◽  
2014 ◽  
Vol 34 (2) ◽  
pp. 122-125
Author(s):  
李建敏 Li Jianmin ◽  
李国柱 Li Guozhu ◽  
王春明 Wang Chunming ◽  
胡席远 Hu Xiyuan ◽  
闫飞 Yan Fei ◽  
...  

Author(s):  
Tang Yushou Su Jianhuan

College Students’ mental health is an important part of higher education, so the current research and prediction of College Students’ mental health are of great significance to better solve the problem of College Students’ mental health. Taking a local university as an example, the data from 2011 to 2019 are selected and analyzed. The normalized data processing method is used to assign weights to 11 kinds of factors that affect the health of college students. The training samples of a neural network are selected, and the structural characteristics of the neural network and the artificial neural network toolbox of MATLAB are used to establish the BP based model the mathematical model of the prediction system of College Students’ mental health based on neural network. The results show that the error between the predicted value and the measured value is only 0.88%. On this basis, this paper uses the model to predict the weight of the influencing factors of the mental health status of college students in a local university in 2020 and analyzes the causes of the prediction results, to provide the basis for the current mental health education of college students.


2020 ◽  
Vol 129 ◽  
pp. 271-279 ◽  
Author(s):  
Giacomo Capizzi ◽  
Grazia Lo Sciuto ◽  
Christian Napoli ◽  
Marcin Woźniak ◽  
Gianluca Susi

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