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JCDR. 2021; 12(3): 1329-1336


Shivaratri Narasimha Rao,S.China Ramu.


This paper offers an summary of present day literature related to time series classification by implementing using Deep Neural Network (DNN) related methods in initial time series for classifying based on distinct distance procedures similar to Euclidean or active distances based on time warping as the paper initiates by reviewing standard approaches of time series classification which aspires for classifying time series through minimal chronological classifications that are potential for possessing the minimal classification accuracy. Additionally most of the papers emphasis in influencing the essential machine learning procedures as the process explores various machine learning tools that are required to implement various projects of machine learning that describes chronological information combined for predicting each model that highlights recent advancements in hybrid deep learning models that are based on statistical models using with neural network constituents for improving each of the categories of time series data.

Key words: Deep Neural Networks, Artificial Intelligence, Time Series Data, Prediction

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