Deep Learning Concepts in Operations Research

Biswadip Basu Mallik, Gunjan Mukherjee, Rahul Kar, Aryan Chaudhary

• Publisher: Auerbach Publications
• Year: 2024
• ISBN:
  9781040102381
• Edition: 1
• Topic: Computer Science
• Subtopic: Artificial Intelligence (AI) & Semantics
• Index: Computer Science

The model-based approach for carrying out classification and identification of tasks has led to the pervading progress of the machine learning paradigm in diversified fields of technology. Deep Learning Concepts in Operations Research looks at the concepts that are the foundation 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 phenomena. Such fields as object classification, speech recognition, and face detection have sought extensive application of artificial intelligence (AI) and ML as well. Among a variety of topics, the book examines:

• An overview of applications and computing devices
• Deep learning impacts in the field of AI
• Deep learning as state-of-the-art approach to AI
• Exploring deep learning architecture for cutting-edge AI solutions

Operations research is the branch of mathematics for performing 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 for decision making. Discussing how a proper decision depends on several factors, the book examines how AI and ML can be used to model equations and define constraints to solve problems and discover proper and valid solutions more easily. It also looks at how automation plays a significant role in minimizing human labor and thereby minimizes overall time and cost.

Table of contents

• Cover
• Half-Title Page
• Series Page
• Title Page
• Copyright Page
• Table of Contents
• Preface
• Contributors
• 1 Deep Learning: Overview, Applications and Computing Devices
• 2 Deep Learning Impacts in the Field of Artificial Intelligence
• 3 Deep Learning is a State-of-the-Art Approach to Artificial Intelligence
• 4 Unleashing the Power: Exploring Deep Learning Architecture for Cutting-Edge AI Solutions
• 5 Deep Learning for ECG Classification: Techniques, Applications, and Challenges
• 6 Social Distancing Detection System Using Single Shot Detection (SSD) and Neural Networks
• 7 Recognition of Voice and Speech Using NLP Techniques
• 8 Transfer Learning with Joint Fine-Tuning for Multimodal Sentiment Analysis
• 9 Machine Learning for Traffic Flow Prediction Addressing Congestion Challenges
• 10 Enhancing Autistic Spectrum Disorder Diagnosis Using ML Techniques: A Study on Deep Neural Network and Drop-out Deep Neural Network
• 11 Deep Learning: A State-Of-The-Art Approach To Artificial Intelligence “AI”
• 12 An Approach through Different Mathematical Models to Enhance the Utility in Different Areas of Machine Learning
• 13 Study of Different Regression Methods, Models and Application in Deep Learning Paradigm
• 14 Deep Learning Impacts in the Field of Artificial Intelligence
• 15 Stock Prices Prediction of the FMCG Sector in NSE India: An Artificial Intelligence Approach
• 16 Multi-Attribute Decision Modelling
• 17 Regression Methods and Models
• 18 The Machine Learning Pipeline: Algorithms, Applications, and Managerial Implications
• 19 Role of Fertamean Neutrosophic Sets for Decision Making Modelling in Machine Learning
• 20 Performance Evaluation of Machine Learning Algorithms in the Field of Security-Malware Detection
• Index