
Deep Learning Applications in Operations Research by Aryan Chaudhary
The model-based approach for carrying out the classification and identification of tasks has led to progression of the machine learning paradigm in diversified fields of technology. Deep Learning Applications in Operations Research presents the varied applications of this model-based approach. Apart from the classification process, the machine learning (ML) model has become effective enough to predict future trends of any sort of phenomenon. Such fields as object classification, speech recognition, and face detection have sought extensive applications of artificial intelligence (AI) and machine learning as well. The application of AI and ML has also become increasingly common in the domains of agriculture, health sectors, and insurance.
Operations research is the branch of mathematics used to perform many operational tasks in other allied domains, and the book explains how the implementation of automated strategies in optimization and parameter selection can be carried out by AI and ML. Operations research has many beneficial aspects to aid in decision making. Arriving at the proper decision depends on a number of factors; this book examines how AI and ML can be used to model equations and define constraints to solve problems more easily and discover proper and valid solutions. This book also looks at how automation plays a significant role in minimizing human labor and thereby minimizes overall time and cost. Case studies examine how to streamline operations and unearth data to make better business decisions. The concepts presented in this book can bring about and guide unique research directions to the future application of AI-enabled technologies.
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Computational Intelligence for Analysis of Trends in Industry 4.0 and 5.0
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Emotional Intelligence in the Digital Era
- Artificial Intelligence Frontiers
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Artificial Intelligence for Renewable Energy Systems
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Innovations and Applications of Technology in Language Education
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Smarter Healthcare Through Generative Intelligence
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AI and ML in IoT Security
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Metaverse and Blockchain
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AI for Environmental Innovation and Stewardship
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Artificial Intelligence in Action
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IoT Cybersecurity
- Parallel and High-Performance Computing in Artificial Intelligence
- Deep Learning and Blockchain Technology for Smart and Sustainable Cities
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Patient-Centric 6G
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Deep Learning Concepts in Operations Research
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Generative AI Tools
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Computational Intelligence in Industry 4.0 and 5.0 Applications
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Data-Driven IoT Ecosystems
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Industry 5.0
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Decoding Global Marketing Decisions
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AI and IoT Technology and Applications for Smart Healthcare Systems
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Explainable Artificial Intelligence in Medical Imaging
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Data-Driven Modelling and Predictive Analytics in Business and Finance
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Technologies for Sustainable Global Higher Education
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Artificial Intelligence Techniques in Power Systems Operations and Analysis
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Edge Computational Intelligence for AI-Enabled IoT Systems
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Social Media and Crowdsourcing
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Augmented Reality and Sustainability
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Artificial Intelligence, Geographic Information Systems, and Multi-Criteria Decision-Making for Improving Sustainable Development
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Leveraging Artificial Intelligence in Cloud, Edge, Fog and Mobile Computing
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Intelligent Business Analytics
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Using AI to Develop Sustainability Strategies for a Changing Global Economy
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Metaverse and Blockchain Use Cases and Applications
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Advanced AI and Data Science Applications
| SKU | Unavailable |
| ISBN 13 | 9781032725451 |
| Title | Deep Learning Applications in Operations Research |
| Author | Aryan Chaudhary |
| Series | Advances In Computational Collective Intelligence |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Taylor & Francis Ltd |
| Year published | 2026-07-20 |
| Number of pages | 262 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |



































