Buch, Englisch, 275 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 600 g
Buch, Englisch, 275 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 600 g
Reihe: Springer Tracts in Nature-Inspired Computing
ISBN: 978-981-13-9262-7
Verlag: Springer Nature Singapore
This book presents a cutting-edge research procedure in the Nature-Inspired Computing (NIC) domain and its connections with computational intelligence areas in real-world engineering applications. It introduces readers to a broad range of algorithms, such as genetic algorithms, particle swarm optimization, the firefly algorithm, flower pollination algorithm, collision-based optimization algorithm, bat algorithm, ant colony optimization, and multi-agent systems. In turn, it provides an overview of meta-heuristic algorithms, comparing the advantages and disadvantages of each.
Moreover, the book provides a brief outline of the integration of nature-inspired computing techniques and various computational intelligence paradigms, and highlights nature-inspired computing techniques in a range of applications, including: evolutionary robotics, sports training planning, assessment of water distribution systems, flood simulation and forecasting, traffic control, gene expression analysis, antenna array design, and scheduling/dynamic resource management.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Technik Allgemein Modellierung & Simulation
- Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker
- Mathematik | Informatik EDV | Informatik Professionelle Anwendung Computersimulation & Modelle, 3-D Graphik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
Weitere Infos & Material
Chapter 1. Particle Swarm Optimization of Morphological Filters for Electrocardiogram Baseline Drift Estimation.- Chapter 2. Detection of Breast Cancer using Fusion of MLO and CC View Features Through a Hybrid Technique Based on Binary Firefly algorithm and Optimum Path Forest Classification.- Chapter 3. Recommending Healthy Personalized Daily Menus – A Cuckoo Search based Hyper-Heuristic Approach.- Chapter 4. A Hybrid Bat-Inspired Algorithm for Power Transmission Expansion Planning on a Practical Brazilian Network.- Chapter 5. An Application of Binary Grey Wolf Optimizer (BGWO) variants for Unit Commitment Problem.- Chapter 6. Sensorineural hearing loss identification via discrete wavelet packet entropy and cat swarm optimization.- Chapter 7. Chaotic Variants of Grasshopper Optimisation Algorithm and their application to Protein Structure Prediction.- Chapter 8. Examination of Retinal Anatomical Structures – A Study with Spider Monkey Optimization Algorithm.- Chapter 9. Nature-Inspired Metaheuristics Search Algorithms for Solving the Economic Load Dispatch Problem of Power System: A Comparative Study.- Chapter 10. Parallel-series System Optimization by Weighting Sum Methods and Nature-inspired Computing.- Chapter 11. Development of Artificial Neural Networks trained by Heuristic Algorithms for Prediction of Exhaust Emissions and Performance of a Diesel Engine Fuelled with Biodiesel Blends.