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This book introduces algorithms for graph based problems, namely combinatorial optimization problems, path formation problems, etc. Each chapter includes the introduction of the basic traditional nature inspired algorithm and discussion of the modified version for discrete algorithms including problems pertaining to discussed algorithms.
- Geräte: PC
- mit Kopierschutz
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- Größe: 8.04MB
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This book introduces algorithms for graph based problems, namely combinatorial optimization problems, path formation problems, etc. Each chapter includes the introduction of the basic traditional nature inspired algorithm and discussion of the modified version for discrete algorithms including problems pertaining to discussed algorithms.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis
- Seitenzahl: 336
- Erscheinungstermin: 15. Dezember 2017
- Englisch
- ISBN-13: 9781351260879
- Artikelnr.: 50518955
- Verlag: Taylor & Francis
- Seitenzahl: 336
- Erscheinungstermin: 15. Dezember 2017
- Englisch
- ISBN-13: 9781351260879
- Artikelnr.: 50518955
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Anupam Shukla is currently a professor with ABV-Indian Institute of Information Technology and Management and has a total of 25 years of experience in both teaching and research. He received the Young Scientist Award from the Madhya Pradesh Council of Science & Technology, Bhopal in 1995 and the Gold Medal from Jadavpur University, Kolkata in 1998 for his postgraduate studies. Professor Shukla's main research area is Artificial Intelligence, and he is currently focusing on Neural Networks and 'Evolutionary and Nature Inspired Computations' that have incalculable applications in Bioinformatics, Medical Expert System, and Robotics. He has supervised 8 PhD students and 67 M Tech thesis in this area. Professor Shukla has published 161 research papers in various national and international journals/conferences, 7 book chapters, and edited two books in the area of biomedical engineering from IGI Global Publishers. Additionally, he has also authored three books entitled: "Real Life Applications of Soft Computing" CRC Press, Taylor and Francis; "Intelligent Planning for Mobile Robotics: Algorithmic Approaches" IGI Global; and "Towards Hybrid and Adaptive Computing: A Perspective", Springer Verlag Publishers.
Ritu Tiwari is an Associate Professor (Department of Information and Communications Technology) at ABV-IIITM, Gwalior. She has 14 years of teaching and research experience which includes 10 years of post PhD Teaching and research Experience. Her field of research includes Robotics, Artificial Intelligence, Soft Computing and Applications (Biometrics, Biomedical, Prediction). She has two patents to her name and has authored three books titled: "Real Life Applications of Soft Computing", Taylor and Francis; "Intelligent Planning for Mobile Robotics: Algorithmic Approaches", IGI Global and "Towards Hybrid and Adaptive Computing: A Perspective", Springer-Verlag Publishers. She has also edited two books in the area of biomedical engineering from IGI Global . She has supervised 5 Ph.D. and 90 master's students and has published 104 research papers in various national and international journals/conferences. She has received Young Scientist Award from Chhattisgarh Council of Science & Technology in the year 2006. She has also received Gold Medal in her post graduation from NIT, Raipur. She has completed ten prestigious research projects sponsored by Department of science and technology (DST) and Department Information Technology (DIT), Government of India. She is currently involved with the Government of India and is working on three sponsored research projects. She is a reviewer of various international journals including ACM Computing Review, IEEE Transactions on Information Technology in Biomedicine, Elsevier Journal of Biomedical Informatics and Elsevier Neurocomputing journal.
Ritu Tiwari is an Associate Professor (Department of Information and Communications Technology) at ABV-IIITM, Gwalior. She has 14 years of teaching and research experience which includes 10 years of post PhD Teaching and research Experience. Her field of research includes Robotics, Artificial Intelligence, Soft Computing and Applications (Biometrics, Biomedical, Prediction). She has two patents to her name and has authored three books titled: "Real Life Applications of Soft Computing", Taylor and Francis; "Intelligent Planning for Mobile Robotics: Algorithmic Approaches", IGI Global and "Towards Hybrid and Adaptive Computing: A Perspective", Springer-Verlag Publishers. She has also edited two books in the area of biomedical engineering from IGI Global . She has supervised 5 Ph.D. and 90 master's students and has published 104 research papers in various national and international journals/conferences. She has received Young Scientist Award from Chhattisgarh Council of Science & Technology in the year 2006. She has also received Gold Medal in her post graduation from NIT, Raipur. She has completed ten prestigious research projects sponsored by Department of science and technology (DST) and Department Information Technology (DIT), Government of India. She is currently involved with the Government of India and is working on three sponsored research projects. She is a reviewer of various international journals including ACM Computing Review, IEEE Transactions on Information Technology in Biomedicine, Elsevier Journal of Biomedical Informatics and Elsevier Neurocomputing journal.
1. Introduction to Optimization Problems 2. Particle Swarm Optimization 3.
Genetic Algorithms 4. Ant Colony Optimization 5. Bat Algorithm 6. Cuckoo
Search Algorithm 7. Artificial Bee Colony 8. Shuffled Frog Leap Algorithm
9. Brain Storm Swarm Optimization Algorithm 10. Intelligent Water Drop
Algorithm 11. Egyptian Vulture Algorithm 12. Biogeography-Based
Optimization 13. Invasive Weed Optimization 14. Glowworm Swarm Optimization
15. Bacteria Foraging Optimization Algorithm 16. Flower Pollination
Algorithm
Genetic Algorithms 4. Ant Colony Optimization 5. Bat Algorithm 6. Cuckoo
Search Algorithm 7. Artificial Bee Colony 8. Shuffled Frog Leap Algorithm
9. Brain Storm Swarm Optimization Algorithm 10. Intelligent Water Drop
Algorithm 11. Egyptian Vulture Algorithm 12. Biogeography-Based
Optimization 13. Invasive Weed Optimization 14. Glowworm Swarm Optimization
15. Bacteria Foraging Optimization Algorithm 16. Flower Pollination
Algorithm
1. Introduction to Optimization Problems 2. Particle Swarm Optimization 3.
Genetic Algorithms 4. Ant Colony Optimization 5. Bat Algorithm 6. Cuckoo
Search Algorithm 7. Artificial Bee Colony 8. Shuffled Frog Leap Algorithm
9. Brain Storm Swarm Optimization Algorithm 10. Intelligent Water Drop
Algorithm 11. Egyptian Vulture Algorithm 12. Biogeography-Based
Optimization 13. Invasive Weed Optimization 14. Glowworm Swarm Optimization
15. Bacteria Foraging Optimization Algorithm 16. Flower Pollination
Algorithm
Genetic Algorithms 4. Ant Colony Optimization 5. Bat Algorithm 6. Cuckoo
Search Algorithm 7. Artificial Bee Colony 8. Shuffled Frog Leap Algorithm
9. Brain Storm Swarm Optimization Algorithm 10. Intelligent Water Drop
Algorithm 11. Egyptian Vulture Algorithm 12. Biogeography-Based
Optimization 13. Invasive Weed Optimization 14. Glowworm Swarm Optimization
15. Bacteria Foraging Optimization Algorithm 16. Flower Pollination
Algorithm