Evolutionary deep recurrent neural networks architecture for forecasting real-time stock stop loss Points-Reference-Cited by-同舟云学术

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Evolutionary deep recurrent neural networks architecture for forecasting real-time stock stop loss Points

Published:2023-05-12 Issue: Volume: Page:
ISSN:
Container-title:2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)
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Author:

S Deepa¹,P Sasikumar²,T.Saravanan ³,Alkhafaji Mohammed Ayad⁴,A.Jabbar Kadim⁴,Mohammed Aymen⁵

Affiliation:

1. Government College of Engineering,Department of Physics, Department of CSE,Salem,India

2. Malla Reddy Institute of Engineering & Technology,Department of CSE,Secunderabad,India

3. GITAM (Deemed to be University),GITAM School of Technology,Department of CSE,Bengaluru,India

4. National University of Science and Technology,Collage of Engineering,Dhi Qar,Iraq

5. Al-Farahidi University,Medical Laboratory Techniques Department,Baghdad,Iraq

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10182388/10182370/10182828.pdf?arnumber=10182828

Reference15 articles.

1. Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction

2. Recurrent neural network based real-time failure detection of storage devices;su;Microsystem Technologies,2019

3. Cooperation-Aware Lane Change Maneuver in Dense Traffic based on Model Predictive Control with Recurrent Neural Network

4. Performance Evaluation of Deep Recurrent Neural Networks Architectures: Application to PV Power Forecasting

5. Comparative Analysis of Software Life Cycle Models

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