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All Journal Bulletin of Engineering Science, Technology and Industry
Diwakar Pandey
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering

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ARTIFICIAL INTELLIGENCE IN COMPUTER ENGINEERING: PSYCHOLOGICAL APPROACHES TO UNDERSTANDING HUMAN BEHAVIOR Shreyasa Rani Dubey; Diwakar Pandey
Bulletin of Engineering Science, Technology and Industry Vol. 2 No. 3 (2024): September
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v2i3.49

Abstract

The integration of Artificial Intelligence (AI) in computer engineering has significantly advanced the field's ability to understand and predict human behavior. This research article explores the intersection of AI and psychological approaches, examining how computational models can simulate cognitive processes and emotional responses. By leveraging machine learning algorithms and neural networks, the study demonstrates how AI systems can analyze vast datasets to identify patterns in human behavior, providing insights into decision-making, social interactions, and mental health. The article also discusses the ethical implications of AI-driven behavioral analysis and the potential for enhancing human-computer interactions. Through a comprehensive review of current methodologies and case studies, this research highlights the transformative impact of AI on understanding human behavior and proposes future directions for integrating psychological theories with AI technologies to further enhance the accuracy and applicability of behavioral predictions in computer engineering.
NEURAL NETWORKS IN COMPUTER ENGINEERING: INSIGHTS FROM COGNITIVE PSYCHOLOGY Diwakar Pandey
Bulletin of Engineering Science, Technology and Industry Vol. 2 No. 3 (2024): September
Publisher : PT. Radja Intercontinental Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59733/besti.v2i3.52

Abstract

Neural networks have become instrumental in advancing computer engineering by drawing insights from cognitive psychology. This research article explores the synergy between neural network models and cognitive psychology theories, highlighting how computational models simulate human cognitive processes. By integrating principles of memory, learning, and decision-making from cognitive psychology, neural networks emulate complex human behaviors and intelligence. The article reviews current methodologies and case studies to illustrate the application of neural networks in solving engineering challenges, such as pattern recognition, natural language processing, and autonomous systems. Ethical considerations and future directions for enhancing neural network capabilities through cognitive psychology are also discussed, emphasizing the transformative impact of this interdisciplinary approach on computer engineering and cognitive science research.
Co-Authors Shreyasa Rani Dubey