Archeological and Historical Database on the Medieval Earthquakes of the Central Himalaya: Ambiguities and Inferences

2013 ◽  
Vol 84 (6) ◽  
pp. 1098-1108 ◽  
Author(s):  
C. P. Rajendran ◽  
K. Rajendran ◽  
J. Sanwal ◽  
M. Sandiford

2020 ◽  
Vol 12 (2) ◽  
pp. 84-99
Author(s):  
Li-Pang Chen

In this paper, we investigate analysis and prediction of the time-dependent data. We focus our attention on four different stocks are selected from Yahoo Finance historical database. To build up models and predict the future stock price, we consider three different machine learning techniques including Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN) and Support Vector Regression (SVR). By treating close price, open price, daily low, daily high, adjusted close price, and volume of trades as predictors in machine learning methods, it can be shown that the prediction accuracy is improved.





Author(s):  
Pratima Pandey ◽  
Sheikh Nawaz Ali ◽  
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2021 ◽  
Author(s):  
Jakob F. Steiner ◽  
Tika R. Gurung ◽  
Sharad P. Joshi ◽  
Inka Koch ◽  
Tuomo Saloranta ◽  
...  


2021 ◽  
Vol 24 (3) ◽  
pp. 510-518
Author(s):  
Lalit S. Bisht ◽  
Anand B. Melkani ◽  
Rajendra Prasad ◽  
Lalit Mohan ◽  
Manisha Palni ◽  
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Geomorphology ◽  
2020 ◽  
Vol 367 ◽  
pp. 107298 ◽  
Author(s):  
Ananya Divyadarshini ◽  
Vimal Singh ◽  
Manoj K. Jaiswal ◽  
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1995 ◽  
Vol 78 (1-3) ◽  
pp. 217-224 ◽  
Author(s):  
Rajesh Thadani ◽  
P.M.S. Ashton


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