State-of-Health Estimation and End of Life Prediction for the Lithium-Ion Battery by Correlatable Feature-based Machine Learning Approach

2021 ◽  
Vol 17 (9) ◽  
pp. 825
Author(s):  
Bhattacharyya Himadri Sekhar ◽  
Seethamraju Sindhu ◽  
Choudhury Amalendu Bikash ◽  
Chanda chandan Kumar
Keyword(s):  
Machine Learning ◽  
Lithium Ion Battery ◽  
End Of Life ◽  
Life Prediction ◽  
Lithium Ion ◽  
Learning Approach ◽  
State Of Health ◽  
Machine Learning Approach ◽  
Feature Based

scholarly journals A Machine Learning Approach to Extract Opinions from Social Media Content

2018 ◽  
Vol 7 (4.5) ◽  
pp. 257
Author(s):  
Salina Adinarayana ◽  
E Ilavarasan
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Opinion Mining ◽  
Media Content ◽  
Learning Approach ◽  
Mobile Environment ◽  
Classification Approach ◽  
Machine Learning Approach ◽  
Semantic Orientation ◽  
Feature Based

The Opinion Mining (OM) from mobile based social media content (SMC) is more challenging compared to topic-based mining, and it cannot be performed based on just examining the presence of single words in the text containing opinion expressions. Moreover, the existing systems of opinion   classification find that a large number of features that are not feasible for the mobile environment. The existing methods of OM in this mobile environment do not consider the semantic orientation of the SMC in the review. The proposed machine learning approach extends the feature-based classification approach to identify the orientation of the phrase on taking context into account to improve the accuracy.   

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