Predicting Price Direction of Bitcoin based on Hybrid Model of LSTM and Dense Neural Network Approach-Reference-Cited by-同舟云学术

Predicting Price Direction of Bitcoin based on Hybrid Model of LSTM and Dense Neural Network Approach

Published:2023-07-06 Issue: Volume: Page:
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Container-title:2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)
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Author:

Karahyla Dr Jai Kishan¹,Sharma Neelam²,Chamoli Sushant³,Shirgire Dr Anil⁴,Kant Ravi⁵,Chauhan Amit⁶

Affiliation:

1. PGCC Hospital Management Professor and Head Respiratory Medicine MMIMSR MM Deemed University,Human Rights, LLB,Mullana Ambala,Haryana,India

2. Lovely Professional University,Physical Education,Phagwara,Punjab,India

3. Graphic Era Hill University,Department of Computer Science and Engineering,Dehradun,India

4. Dr D Y Patil Institute of Technology,Department of Civil Engineering,Pimpri, Pune,Maharashtra,India

5. Shoolini University,CSE Department,Solan,Himachal Pradesh,India

6. CHRIST (Deemed to be University),Department of life Sciences,Bengaluru,Karnataka,India

Publisher

IEEE

Link

Reference28 articles.

1. Testing the weak form of efficient market in cryptocurrency;latif;J Eng Appl Sci,2017

3. Trading bit coin and online time series prediction;amjad;NIPS 2016 Time Series Workshop,2017

5. Time-series forecasting of Bitcoin prices using highdimensional features: a machine learning approach;mudassir;Neural Comput Appl,2020

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