Classification Techniques in Analysis of Salem District Soil condition for Cultivation of Sunflower

2018 ◽  
Vol 6 (8) ◽  
pp. 642-646
Author(s):  
N. Hemageetha ◽  
N. Nagalakshmi
2012 ◽  
Author(s):  
Alasdair Matthew Goodwill ◽  
Skye Stephens ◽  
Sandra Oziel ◽  
Nicola Bowes

2017 ◽  
Vol 23 (1) ◽  
Author(s):  
SHELLEY ACHARYA ◽  
ADITI DUTTA

The studies were mostly concentrated in Nine forest ranges of the WLS including the core areas. The soil of this region mostly is dry, red and with iron and silica content. Though the soil mites are prevalent in moist humid condition, we got a diversed population of 20 different species under 14 genera which is less than average probably due to the soil condition. Protoribates magnus is the dominant species in this study. The species with larger ranges were Scheloribates curvialatus.


2017 ◽  
Vol 13 (9) ◽  
pp. 6480-6488 ◽  
Author(s):  
A.D. Jeyarani ◽  
Reena Daphne ◽  
Solomon Roach

The main contribution of this paper has been to introduce nonlinear classification techniques to extract more information from the PCG signal. Especially, Artificial Neural Network classification techniques have been used to reconstruct the underlying system’s state space based on the measured PCG signal. This processing step provides a geometrical interpretation of the dynamics of the signal, whose structure can be utilized for both system characterization and classification as well as for signal processing tasks such as detection and prediction.


2019 ◽  
Vol 11 (2) ◽  
pp. 71-75
Author(s):  
B Jayaprakash ◽  
◽  
R Rajeshkannan ◽  
K Ezhilvendhan ◽  
◽  
...  

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