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Machine Intelligence, Tools, and Applications

Proceedings of the International Conference on Machine Intelligence, Tools, and Applications—ICMITA 2024

  • Conference proceedings
  • © 2024

Overview

Editors:
  1. Satchidananda Dehuri

    1. Fakir Mohan University, Balasore, India

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  2. Sung-Bae Cho

    1. Yonsei University, Seoul, Korea (Republic of)

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  3. Venkat Prasad Padhy

    1. VIT Bhopal University, Bhopal, India

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  4. Poonkuntrun Shanmugam

    1. VIT Bhopal University, Bhopal, India

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  5. Ashish Ghosh

    1. Indian Statistical Institute, Kolkata, India

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  • Presents recent research in Machine Intelligence
  • Is the proceedings of the International Conference on Machine Intelligence, Tools, and Applications—ICMITA 2023
  • Written by experts in the field

Part of the book series: Learning and Analytics in Intelligent Systems (LAIS, volume 40)

Included in the following conference series:

Conference proceedings info: ICMITA 2024.

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About this book

This book presents the recent advances including tools and techniques in the constantly changing landscape of machine learning (ML). This would enable the readers with a strong understanding of critical issues in ML by providing both broad and detailed perspectives on cutting-edge theories, algorithms, and tools. This will become a single source of reference on conceptual, methodological, technical, and managerial issues, as well as provide insight into emerging trends and future opportunities in the discipline of ML. This book contains altogether 36 chapters in the area of ML and its applications.

Keywords

Table of contents (36 papers)

  1. Front Matter

    Pages i-xii
    Download chapter PDF

  2. Fuzzy-Guided Genetic Algorithm Routing for Energy Conservation in Wireless Sensor Networks

    • Virendra Tiwari, Shankar Bera, Anand Kumar Dwivedi, Balendra Kumar Garg, Akhilesh A. Waoo
    Pages 1-18

  3. Comparative Analysis of Prediction Models for Software Bug Prediction

    • Tirimula Rao Benala, Soniya Satti, Satchidananda Dehuri
    Pages 19-28

  4. Mandelbug Classification Engine: Transfer Learning and NLP Approach

    • Biswajit Biswal
    Pages 29-39

  5. Software Maintenance Prediction Using Regression Models

    • Bikash Agrawalla, Shristi Chirania, Hera Tahreem, Ayushi, B. Ramachandra Reddy
    Pages 40-47

  6. Rough Set, ELM Classifier and Deep Architecture for Remote Sensing Images

    • Neeta Sharma, Ravi Sindal, Saroj K. Meher
    Pages 48-59

  7. Design of an Efficient Model for Satellite Image Classification Using Graph Neural Networks and Elephant Herding Optimization

    • Rosy Bhoi, Ashok Kumar Patel
    Pages 60-69

  8. Multifaceted Analysis of Climate Trends and Air Quality in Indian Metropolises: A Machine Learning and Time Series Forecasting Approach

    • Harsh Soni, Akhil, Prakhar Raj Pandey, Gaurav Garwa, Shivansh Rastogi, Sandip Mal
    Pages 70-80

  9. Machine Learning-Based Analysis and Forecasting of Electricity Demand in Misamis Occidental, Philippines

    • Murphy T. Saumat, Abid Yahya
    Pages 81-90

  10. Implementation and Optimization of Swarm Based System for Multi-agent Coordination and Task Execution in Marine Environment

    • Puneet S. Lamamuri, Janmesh Singh, Yashraj Karwa, Soumitra K. Nayak
    Pages 91-101

  11. Implementing Deep NN for Plant Disease Detection and Diagnosis

    • Ranjan Singh, Pranshu Pranjal, Rajneesh Kumar Patel, Bhupendra Panchal
    Pages 102-115

  12. A PSO Approach for Two Warehouse Inventory Problem with Imperfect Quality Items and Variable Discount

    • Rashmi Rani Patro, Rojalini Patro, Parimal Kr. Giri, Bibudhendu Pati
    Pages 116-127

  13. Design of Intraday Stock Price Prediction Model Using Machine Learning via Technical Indicators

    • Pinky Gangwani, Vikas Panthi
    Pages 128-139

  14. Towards Precision: A Comparative Analysis of Crude Oil Price Forecasting Approaches

    • Manan Sodha, Rudra Kalyan Nayak, Nilamadhab Mishra, Santosh Kumar Tripathy, Ramamani Tripathy, Dhawaleswara Rao CH
    Pages 140-151

  15. 3D Segmentation and Subtypes Classification of Breast Cancer Using Ultrasound Images Through Hybrid Approach of CNN and LSTM

    • P. Manju Bala, S. Priyadharshini, U. Palani
    Pages 152-163

  16. A Hybrid Machine Learning Based Cuckoo Search Clustering with Application of Image Recognition Techniques for Tomato Flu Skin Lesion Detection

    • Akshaya Kumar Mandal, Pankaj Kumar Deva Sarma, Satchidananda Dehuri
    Pages 164-176

  17. Comparative Analysis of Machine Learning Classifiers for Differentially Methylated Gene Classification in Rheumatoid Arthritis

    • A. Ezhil Grace, R. Thandaiah Prabu
    Pages 177-188

  18. An IoT Device for Intelligent Healthcare Monitoring Based on Machine Learning

    • Roshan Jahan, Mohammad Amaan Khan
    Pages 189-200

  19. Glaucoma Diagnosis Based on Fusion of Shape and Texture Features from Neuroretinal Rim Area of Retinal Fundus Image

    • Nibedita Kalita, Samir Kumar Borgohain
    Pages 201-208

  20. AI Based Machine Learning Prediction Measure Parkinson Disease Severity

    • Dhivya Bharathi Krishnamoorthy, Sasmitha Padhy
    Pages 209-219
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Other volumes

  1. Machine Intelligence, Tools, and Applications

Editors and Affiliations

  • Fakir Mohan University, Balasore, India

    Satchidananda Dehuri

  • Yonsei University, Seoul, Korea (Republic of)

    Sung-Bae Cho

  • VIT Bhopal University, Bhopal, India

    Venkat Prasad Padhy, Poonkuntrun Shanmugam

  • Indian Statistical Institute, Kolkata, India

    Ashish Ghosh

Bibliographic Information

  • Book Title: Machine Intelligence, Tools, and Applications

  • Book Subtitle: Proceedings of the International Conference on Machine Intelligence, Tools, and Applications—ICMITA 2024

  • Editors: Satchidananda Dehuri, Sung-Bae Cho, Venkat Prasad Padhy, Poonkuntrun Shanmugam, Ashish Ghosh

  • Series Title: Learning and Analytics in Intelligent Systems

  • DOI: https://doi.org/10.1007/978-3-031-65392-6

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024

  • Hardcover ISBN: 978-3-031-65391-9Published: 30 July 2024

  • Softcover ISBN: 978-3-031-65394-0Due: 13 August 2025

  • eBook ISBN: 978-3-031-65392-6Published: 29 July 2024

  • Series ISSN: 2662-3447

  • Series E-ISSN: 2662-3455

  • Edition Number: 1

  • Number of Pages: XII, 422

  • Number of Illustrations: 51 b/w illustrations, 160 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence, Machine Learning

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