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Computational Intelligence Techniques and Their Applications to Software Engineering Problems -

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      Avis sur Computational Intelligence Techniques And Their Applications To Software Engineering Problems Format Relié  - Livre Informatique

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      Présentation Computational Intelligence Techniques And Their Applications To Software Engineering Problems Format Relié

       - Livre Informatique

      Livre Informatique - 01/09/2020 - Relié - Langue : Anglais

      . .

    • Editeur : Crc Press
    • Langue : Anglais
    • Parution : 01/09/2020
    • Format : Moyen, de 350g à 1kg
    • Nombre de pages : 268.0
    • Expédition : 553
    • Dimensions : 23.4 x 15.6 x 1.9
    • ISBN : 0367529742



    • Résumé :
      1. Implementation of Artificial Intelligence Techniques for Improving Software Engineering. 2. Software effort estimation: Machine learning vs. Hybrid algorithms. 3. Implementation of Data Mining Techniques for Software Development Effort Estimation. 4. Empirical Software Measurements with Machine Learning. 5. Project Estimation And Scheduling Using Computational Intelligence. 6. Application of Intuitionistic Fuzzy Similarity Measures in Strategic Decision-Making. 7. Nature-Inspired Approaches to Test Suite Minimization for Regression Testing. 8. Identification and Construction of Reusable Components from Object-Oriented Legacy Systems using various Software Artifacts. 9. A Software Component Evaluation and Selection Approach Using Fuzzy Logic. 10. Smart Predictive Analysis for Testing Messaging-passing Applications. 11. Status of Agile Practices in the Software Industry in 2019. 12.?Agile Methodologies: A Performance Analysis To Enhance Software Quality. 13. Pre-Trained Deep Neural Networks for Age Prediction from IRIS Biometrics. 14. Hybrid Intelligent Decision Support Systems to Select The Optimum Fuel Blend in CI Engine. 15. Understanding the Significant Challenges of Software Engineering in Cloud Environment....

      Sommaire:

      1. Implementation of Artificial Intelligence Techniques for Improving Software Engineering. 2. Software effort estimation: Machine learning vs. Hybrid algorithms. 3. Implementation of Data Mining Techniques for Software Development Effort Estimation. 4. Empirical Software Measurements with Machine Learning. 5. Project Estimation And Scheduling Using Computational Intelligence. 6. Application of Intuitionistic Fuzzy Similarity Measures in Strategic Decision-Making. 7. Nature-Inspired Approaches to Test Suite Minimization for Regression Testing. 8. Identification and Construction of Reusable Components from Object-Oriented Legacy Systems using various Software Artifacts. 9. A Software Component Evaluation and Selection Approach Using Fuzzy Logic. 10. Smart Predictive Analysis for Testing Messaging-passing Applications. 11. Status of Agile Practices in the Software Industry in 2019. 12. Agile Methodologies: A Performance Analysis To Enhance Software Quality. 13. Pre-Trained Deep Neural Networks for Age Prediction from IRIS Biometrics. 14. Hybrid Intelligent Decision Support Systems to Select The Optimum Fuel Blend in CI Engine. 15. Understanding the Significant Challenges of Software Engineering in Cloud Environment.

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