A Novel Approach for Human Behaviour Prediction Using Deep Learning Algorithms

Authors

  • Babhuti Kashyap Assistant Professor Psychology Centre for online education, Department of Psychology, Chandigarh University, Mohali
  • Vrinda Sachdeva Associate professor ITS engineering college, greater Noida Computer science department
  • Abhinandan Shirahatti Associate Professor Department of Computer Science and Engineering KIT College of Engineering (Autonomous) Kolhapur Maharashtra
  • Gurwinder Singh Assistant Professor, Department of AIT-CSE, Chandigarh University, Punjab, India
  • Amit Arya Assistant Professor Madanapalle Institute of Technology & Science
  • Senthilkumar Jagatheesan Associate Professor,Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, No.42, Avadi-Vel Tech Road, Vel Nagar, Avadi, Chennai, Tamil Nadu, India
  • Chaman Kumar Department of computer science IIMT College of engineering greater Noida

Keywords:

Human behaviour prediction, Deep learning, LSTM (Long Short-Term Memory), CNN (Convolutional Neural Network), Data preprocessing

Abstract

Predicting human behaviour is a complex and multifaceted endeavour with implications spanning various domains, from healthcare and marketing to security and social sciences. This research paper delves into the application of deep learning techniques for the prediction of human behaviour. The study explores the use of neural networks, including Long Short-Term Memory (LSTM), convolutional neural networks (CNNs), and other advanced deep learning architectures in capturing intricate patterns and dependencies in human behaviour data.

We begin by discussing the importance of human behaviour prediction, its real-world applications, and the challenges associated with this task. We also highlight the significance of feature engineering and data preprocessing techniques in enhancing prediction accuracy. The research emphasizes the critical role of data quality, model interpretability, and ethical considerations in the deployment of deep learning for human behaviour prediction. Moreover, it addresses the ongoing research challenges and future directions in this field, such as addressing biases, handling sparse data, and integrating multimodal data sources. In conclusion, this paper underscores the promise of deep learning in advancing our ability to predict human behaviour, with the potential for transformative applications in numerous sectors. The findings presented herein contribute to the ongoing dialogue on harnessing artificial intelligence for a better understanding of and adaptability to human behaviour.

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References

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Published

25.12.2023

How to Cite

Kashyap, B. ., Sachdeva, V. ., Shirahatti, A. ., Singh, G. ., Arya, A. ., Jagatheesan, S. ., & Kumar, C. . (2023). A Novel Approach for Human Behaviour Prediction Using Deep Learning Algorithms. International Journal of Intelligent Systems and Applications in Engineering, 12(1), 793–801. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4192

Issue

Vol. 12 No. 1 (2024)

Section

Research Article

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