Quantum-inspired algorithms for cognitive computing: Enhancing cloud-based problem-solving

Title

Quantum-inspired algorithms for cognitive computing: Enhancing cloud-based problem-solving

Creator

Sharma, Durgansh; Jose, Dennis; Johnson, Maria

Description

The convergence of quantum-inspired algorithms and cloud-based frameworks represents a transformative shift in computational capabilities tailored to the human-centric goals of Industry 5.0. Unlike Industry 4.0, which focused on automation and digitization, Industry 5.0 emphasizes intelligent systems that complement human decision-making. Quantum-inspired algorithms, derived from the principles of superposition and entanglement, offer superior capabilities in optimization and pattern recognition without requiring quantum hardware. When integrated with scalable and distributed cloud computing infrastructures, these algorithms enable high-performance cognitive computing, tackling previously intractable problems across domains. This chapter explores the theoretical foundation and practical implementation of such systems, including quantum-inspired neural networks (QiNNs), quantum-inspired immune algorithms (QiIAs), and quantum-inspired particle swarm optimization (QPSO). These models exhibit enhanced accuracy and efficiency in applications like pattern recognition, anomaly detection, and multiobjective optimization. Real-world case studies in finance, cybersecurity, healthcare, and smart grid management highlight their impact on risk modeling, threat mitigation, and decision support systems. The chapter further proposes a cloud integration framework, addressing challenges in scalability, performance, and security. Implementation strategies and architectural designs are discussed with a focus on dynamic resource management, real-time analytics, and secure deployment. The synthesis of these technologies marks a significant advancement toward achieving adaptive, intelligent, and secure computational ecosystems, aligned with the values and vision of Industry 5.0. 2026 selection and editorial matter, Jossy George, Kamal Upreti, Ramesh Chandra Poonia, Ankit Gautam, and Danish Nadeem; individual chapters, the contributors.

Source

Cognitive Cloud Computing: Building Intelligent Systems for Tomorrow;pp.96-123

Date

01-01-2025

Publisher

Taylor and Francis

Coverage

Sharma D., Department of MBA School of Business Management, CHRIST University, Bengaluru, India; Jose D., Department of MBA School of Business Management, CHRIST University, Bengaluru, India; Johnson M., Department of MBA School of Business Management, CHRIST University, Bengaluru, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISBN: 978-104054278-1; 978-103294165-3;

Format

online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1201/9781003569251-5

https://www.scopus.com/pages/publications/105024637206?origin=resultslist