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Meta Heuristic Techniques in Software Engineering and Its Applications

METASOFT 2022

  • Conference proceedings
  • © 2022

Overview

Editors:
  1. Mihir Narayan Mohanty

    1. Department of ECE, ITER, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, India

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  2. Swagatam Das

    1. Indian Statistical Institute, Kolkata, India

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  3. Mitrabinda Ray

    1. Department of CSE, ITER, Siksha 'O' Anusandhan, Bhubaneswar, India

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  4. Bichitrananda Patra

    1. Department of CA, ITER, Siksha 'O' Anusandhan, Bhubaneswar, India

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  • Presents recent Metaheuristic Techniques in Software Engineering and its Applications
  • Covers proceedings of the International Conference on Metaheuristics in Software Engineering and its Application
  • Written by experts in the field

Part of the book series: Artificial Intelligence-Enhanced Software and Systems Engineering (AISSE, volume 1)

Included in the following conference series:

Conference proceedings info: METASOFT 2022.

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Table of contents (35 papers)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Performance Analysis of Heuristic Optimization Algorithms for Transportation Problem

    • S. K. Behera, Ayeshkant Mallick, Nilima R. Das
    Pages 1-9

  3. Source Code Features Based Branch Coverage Prediction Using Ensemble Technique

    • Swadhin Kumar Barisal, Pushkar Kishore, Gayatri Nayak
    Pages 10-19

  4. Implicit Methods of Multi-factor Authentication

    • Chippada Monisha, Koli Pavan Kumar, Pasili Ajay, Pushpendra Kumar Chandra, Satish Kumar Negi
    Pages 20-31

  5. Comparative Analysis of Different Classifiers Using Machine Learning Algorithm for Diabetes Mellitus

    • Santosh Kumar Sharma, Ankur Priyadarshi, Srikanta Kumar Mohapatra, Jitesh Pradhan, Prakash Kumar Sarangi
    Pages 32-42

  6. Survey on Machine Learning Techniques for Software Reliability Accuracy Prediction

    • Suneel Kumar Rath, Madhusmita Sahu, Shom Prasad Das, Jitesh Pradhan
    Pages 43-55

  7. Classification of Pest in Tomato Plants Using CNN

    • K. N. S. Dharmasastha, K. Sharmila Banu, G. Kalaichevlan, B. Lincy, B. K. Tripathy
    Pages 56-64

  8. Deep Neural Network Approach for Identifying Good Answers in Community Platforms

    • Julius Femi Godslove, Ajit Kumar Nayak
    Pages 65-71

  9. Time Series Analysis of SAR-Cov-2 Virus in India Using Facebook’s Prophet

    • Sushree Gayatri Priyadarsini Prusty, Sashikanta Prusty
    Pages 72-81

  10. Model-Based Smoke Testing Approach of Service Oriented Architecture (SOA)

    • Pragya Jha, Madhusmita Sahu, Sukant Kishoro Bisoy
    Pages 82-91

  11. Role of Hybrid Evolutionary Approaches for Feature Selection in Classification: A Review

    • Jayashree Piri, Puspanjali Mohapatra, Raghunath Dey, Niranjan Panda
    Pages 92-103

  12. Evaluation of Deep Learning Models for Detecting Breast Cancer Using Mammograms

    • Subasish Mohapatra, Sarmistha Muduly, Subhadarshini Mohanty, Santosh Kumar Moharana
    Pages 104-112

  13. Evaluation of Crop Yield Prediction Using Arsenal and Ensemble Machine Learning Algorithms

    • Nikitha Pitla, Kayal Padmanandam
    Pages 113-123

  14. Notification Based Multichannel MAC (NM-MAC) Protocol for Wireless Body Area Network

    • Manish Chandra Roy, Tusarkanta Samal, Anita Sahoo
    Pages 124-133

  15. A Multi Brain Tumor Classification Using a Deep Reinforcement Learning Model

    • B. Anil Kumar, N. Lakshmidevi
    Pages 134-144

  16. A Brief Analysis on Security in Healthcare Data Using Blockchain

    • Satyajit Mohapatra, Pranati Mishra, Ranjan Kumar Dash
    Pages 145-155

  17. A Review on Test Case Selection, Prioritization and Minimization in Regression Testing

    • Swarnalipsa Parida, Dharashree Rath, Deepti Bala Mishra
    Pages 156-163

  18. Artificial Intelligence Advancement in Pandemic Era

    • Ritu Chauhan, Harleen Kaur, Bhavya Alankar
    Pages 164-172

  19. Predictive Technique for Identification of Diabetes Using Machine Learning

    • Ritu Chauhan, Harleen Kaur, Bhavya Alankar
    Pages 173-180

  20. Prognosis of Prostate Cancer Using Machine Learning

    • Ritu Chauhan, Neeraj Kumar, Harleen Kaur, Bhavya Alankar
    Pages 181-190
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  1. Meta Heuristic Techniques in Software Engineering and Its Applications

Keywords

About this book

This book discusses an integration of machine learning with metaheuristic techniques that provide more robust and efficient ways to address traditional optimization problems. Modern metaheuristic techniques, along with their main characteristics and recent applications in artificial intelligence, software engineering, data mining, planning and scheduling, logistics and supply chains, are discussed in this book and help global leaders in fast decision making by providing quality solutions to important problems in business, engineering, economics and science. Novel ways are also discovered to attack unsolved problems in software testing and machine learning. The discussion on foundations of optimization and algorithms leads beginners to apply current approaches to optimization problems. The discussed metaheuristic algorithms include genetic algorithms, simulated annealing, ant algorithms, bee algorithms and particle swarm optimization. New developments on metaheuristics attract researchers and practitioners to apply hybrid metaheuristics in real scenarios.

Editors and Affiliations

  • Department of ECE, ITER, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, India

    Mihir Narayan Mohanty

  • Indian Statistical Institute, Kolkata, India

    Swagatam Das

  • Department of CSE, ITER, Siksha 'O' Anusandhan, Bhubaneswar, India

    Mitrabinda Ray

  • Department of CA, ITER, Siksha 'O' Anusandhan, Bhubaneswar, India

    Bichitrananda Patra

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