1st Edition
Deep Learning Applications in Operations Research
The model-based approach for carrying out classification and identification of tasks has led to the pervading progress of 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 phenomena. Such fields as object classification, speech recognition, and face detection have sought extensive application of artificial intelligence (AI) and machine learning as well. The application of AI and ML has also the domains of agriculture, health sectors, and insurance.
Operations research is the branch of mathematics for performing so 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 the proper decision depends on a number of factors, the book examines how AI and ML can be used to model equations and define constraints to solve more easily problems and discover proper and valid solutions. It also looks at how automation plays a significant role in minimizing human labor and thereby minimizes overall time and cost. Case studies look at 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.
1. Predicting Crop Yield using Quantum Neural Networks
Banu Priya Prathaban, R. Subash, and M. Sathesh
2. A Comprehensive Survey on Risk Factor Monitoring Using Deep Learning Methods on Electrocardiogram Data
Dipanwita Saha, Gunjan Mukherjee, Arpitam Chatterjee, and Bipan Tudu
3. Data-centric in AI Perspective Challenges in Deep Learning
S. Mythili and S. Kowsalya
4. Multi-Attribute Decision Modeling
Fluturim Saliu, Minghai Yang, and Waqar Akbar Khan
5. Unmasking Transformations: CNNs for Detecting Land Cover Changes in Satellite Imagery
Sejal Thakkar, Chirag Patel, Ahmed Shaikh, Divyanshi Detroja, and Ved Suthar
6. Leafine: An AI Tool to Recognize and Perceive Leaf Illness with Manure Suggestions
S. Prince Sahaya Brighty, Brindha M, and R. Anuradha
7. An Expansive Performance Analysis and Comparison Between Different Supervised and Unsupervised ML Algorithms for Categorization of Some Indian Hospital’s ICU Patients
Amrita Ghosh, Partha Das, Subrata Jana, Bibhas Chandra. Giri, and Anirban Sarkar
8. Darknet in Multiple Gun Detection for Suspicious Activity Detection and Crime Prediction
V. S. Gulhane and A. M. Bhugul
9. Image Edge Detection Using Fireflies Fine-Tuned Deep Convolution Networks
M.Jansirani and Dr.P.Sumitra
10. Application of Machine Learning, Deep Learning and Econometric Models in Stock Price Movement of Rain Industry: An In-Depth Analysis
Mr. Abhijit Biswas and Meghdoot Ghosh
11. Performance Analysis of U-Net and Fully Convolutional Regression Network on Jetson Nano for the Real-Time Inventory Analysis
Vinayak Bharadi, Suha Mukadam, Rahul Prasad, Kavyashree Upparakakula, and Janhavi Jaygade
12. Clinical Decision Support System for Prevention of Puberty Disorders and Infertility Problems due to Noyyal River Pollution using Ensemble Learning Techniques
Anitha Shanmugam, Chandrasekaran Viswanathan, and Pradhanika Mohankumar
13. Obesity Prediction Using Machine Learning
Kala Raja Mohan, Nagadevi Bala Nagaram, R. Narmada Devi, Regan Murugesan, and Subashini Chandrasekar
14. Intuitionistic Fuzzy Dombi-Archimedean Weighted Aggregation Operators and Their Applications in Sustainable Material Selection
Abhijit Saha and P. Sumitra
15. Identification of Rice Leaf Disease Detection Using Gaussian Mixture Model: A Machine Learning Approach Using Image Classification Technique
Binoy Sasmal, Rajat Subhra Goswami, Manas Pratim Dutta
16. Multi-Objective Optimization of Economic Development and Environmental Issues on Yangtze River Basin, China
Minh Thu Nguyen
17. Qualitative Study on E-Commerce and Brick-and-Mortar: A Machine Learning Approach
Sanjay Das, Soumen Santra, and Anirban Sarkar
18. Design of Novel Energy Management System in Solar PV Powered EV Charging Station Using Artificial Gorilla Troops Optimization
M. Sathesh, Banu Priya Prathaban, and R. Priyanka
19. School Students Cataract Prediction Using Machine Learning
Nagadevi Bala Nagaram, R. Narmada Devi, Kala Raja Mohan, and Sathish Kumar Kumaravel
20. Minimization of the Threat of Diabetic Kidney Disease through the Lens of Machine Learning
Sudipta Adhikary, Kaushik Chanda, Gunjan Mukherjee, and Kaushik Banerjee
21. A Novel Segmentation and Feature Extraction-Based Plant Disease Diagnosis Method Based on Stacked Ensemble Learning
Karthickmanoj .R, S.Aasha Nandhini, and Sasilatha .T
Biography
Biswadip Basu Mallik is a Senior Assistant Professor of Mathematics in the Department of Basic Sciences & Humanities at Institute of Engineering & Management, Kolkata, India.
Gunjan Mukherjee is an Assistant professor in the Department of Computational Science, Brainware University, Barasat, India.
Rahul Kar holds a master's degree in mathematics from Burdwan University and is currently working as a SACT-II Mathematics faculty of Kalyani Mahavidyalaya, Kalyani, Nadia, West Bengal.
Aryan Chaudhary is the Research Head and Lead Member of the research project launched by Nijji Healthcare Pvt Ltd.
