UID:
almafu_9959767606502883
Format:
1 online resource (xiv, 637 pages) :
,
illustrations.
Edition:
1st ed. 2020.
ISBN:
981-15-0222-6
Series Statement:
Algorithms for Intelligent Systems,
Content:
This book gathers selected papers presented at the International Conference on Advancements in Computing and Management (ICACM 2019). Discussing current research in the field of artificial intelligence and machine learning, cloud computing, recent trends in security, natural language processing and machine translation, parallel and distributed algorithms, as well as pattern recognition and analysis, it is a valuable resource for academics, practitioners in industry and decision-makers. .
Note:
Includes index.
,
Chapter 1. Intuitionistic Fuzzy Shannon Entropy Weight Based Multi Criteria Decision Model with TOPSIS to Analyse Security Risks and Select Online Transaction Method -- Chapter 2. Fermat Spiral Based Moth-Flame Optimization Algorithm for Object-Oriented Testing -- Chapter 3. A Comparative Study of Information Retrieval Using Machine Learning -- Chapter 4. Adaptive Background Subtraction Using Manual Approach for Static Images -- Chapter 5. Tweets Daily: Categorised News from Twitter -- Chapter 6. Compressing Meta Class Files through String Optimization -- Chapter 7. An Algorithm to Generate Largest Prime Number -- Chapter 8. Development of a Discretization Methodology for 2.5D Milling Toolpath optimization Using Genetic Algorithm -- Chapter 9. Machine Learning Based Prediction of PM 2.5 Pollution Level in Delhi -- Chapter 10. A Comparative Study of Load Balancing Algorithms in a Cloud Environment -- Chapter 11. Information Retrieval from Search Engine Using Particle Swarm Optimization -- Chapter 12. Genetic Algorithm Based Multi Objective Optimization Framework to Solve Travelling Salesman Problem -- Chapter 13. Design of Optimal PID Controller for Varied System Using Teaching-Learning-Based Optimization -- Chapter 14. Innovative Review on Artificial Bee Colony Algorithm and it’s Variants -- Chapter 15. Multi Linear Regression Model to Predict Correlation between IT Graduate Attributes for Employability using R. .
Additional Edition:
ISBN 981-15-0221-8
Language:
English
DOI:
10.1007/978-981-15-0222-4
