Handbook of Neural Computation

Pijush Samui, Sanjiban Sekhar Roy, Valentina Emilia Balas (Herausgeber)

Buch | Softcover

658 Seiten

2017
Academic Press Inc (Verlag)
978-0-12-811318-9 (ISBN)

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Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world.

Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text.

Dr. Samui is an Associate Professor in the Department of Civil Engineering at NIT Patna, India. He received his PhD in Geotechnical Engineering from the Indian Institute of Science Bangalore, India, in 2008. His research interests include geohazard, earthquake engineering, concrete technology, pile foundation and slope stability, and application of AI for solving different problems in civil engineering. Dr. Samui is a repeat Elsevier editor but also a prolific contributor to journal papers, book chapters, and peer-reviewed conference proceedings. Dr. Sanjiban Sekhar Roy (Member, IEEE) is a distinguished academic and researcher, currently serving as a Professor in the School of Computer Science and Engineering at Vellore Institute of Technology (VIT). He earned his Ph.D. in 2016 from VIT, and from 2019 to 2020, he served as an Associate Researcher at Ton Duc Thang University, Vietnam. With an extensive academic career, Dr. Roy has published over 80 peer-reviewed articles in renowned international journals and conferences, making significant contributions to the fields of deep learning, advanced machine learning, and artificial intelligence. He has authored and co-authored several books published by Elsevier and CRC Press. In addition to these, he has edited 10 books with prestigious international publishers, demonstrating his expertise in computer science and technology. Dr. Roy holds two patents and is an active member of various doctoral committees, providing valuable guidance to Ph.D. scholars. He has mentored numerous postgraduate and undergraduate students, helping them navigate their research projects and academic pursuits. Beyond his research and teaching, Dr. Sanjiban Sekhar Roy has served as an editorial member for several highly respected journals and has edited special issues for prominent publications in his field. His research and academic contributions have been recognized globally, earning him the prestigious “Diploma of Excellence Award for academic research from the Ministry of National Education, Romania, in 2019. Dr. Roy’s work continues to push the boundaries of artificial intelligence, particularly in deep learning and machine learning. His contributions to the academic community and his leadership in research have made a lasting impact on the advancement of these transformative technologies. Valentina Emilia Balas is currently a Full Professor in the Department of Automatics and Applied Software at the Faculty of Engineering, “Aurel Vlaicu University of Arad, Romania. She holds a PhD cum Laude in Applied Electronics and Telecommunications from the Polytechnic University of Timisoara. Dr. Balas is the author of more than 350 research papers. She is the Editor-in-Chief of the 'International Journal of Advanced Intelligence Paradigms' and the 'International Journal of Computational Systems Engineering', an editorial board member for several other national and international publications, and an expert evaluator for national and international projects and PhD theses.

1. Gravitational Search Algorithm With Chaos
2. Textures and Rough Sets
3. Hydrological time series forecasting using three different heuristic regression techniques
4. A reflection on image classifications for forest ecology management: Towards landscape mapping and monitoring
5. An Intelligent Hybridization of ABC and LM Algorithms with Constraint Engineering Applications
6. Network Intrusion Detection Model based on Fuzzy-Rough Classifiers
7. Efficient System Reliability Analysis of Earth Slopes Based on Support Vector Machine Regression Models
8. Predicting Short-Term Congested Traffic Flow on Urban Motorway Networks
9. Object Categorization Using Adaptive Graph-based Semi-supervised Learning
10. Hemodynamic Model Inversion by Iterative Extended Kalman Smoother
11. Improved Sparse Approximation Models for Stochastic Computations
12. Symbol Detection in Multiple Antenna Wireless Systems via Ant Colony Optimization
13. Application of particle swarm optimization to solve robotic assembly line balancing problems
14. The cuckoo optimization algorithm and its applications
15. Hybrid Intelligent Model Based on Least Squared Support Vector Regression and Artificial Bee Colony Optimization for Time Series Modeling and Forecasting Horizontal Displacement of Hydropower Dam
16. Modelling the axial capacity of bored piles using multi-objective feature selection, functional network and multivariate adaptive regression spline
17. Transient stability constrained optimal power flow using chaotic whale optimization algorithm
18. Slope Stability Evaluation Using Radial Basis Function Neural Network, Least Squares Support Vector Machines, and Extreme Learning Machine
19. Alternating Decision Trees
20. Scene Understanding Using Deep Learning
21. Deep Learning for Coral Classification
22. A Deep Learning Framework for Classifying Mysticete Sounds
23. Unsupervised deep learning for data-driven reliability and risk analysis of engineered systems
24. Applying Machine Learning Algorithms in Landslide Susceptibility Assessments
25. MDHS-LPNN: A hybrid FOREX predictor model using a Legendre polynomial Neural Network with a Modified Differential Harmony Search technique
26. A Neural Model of Attention and Feedback for Computing Perceived Brightness in Vision
27. Support Vector Machine: Principles, Parameters and Applications
28. Evolving Radial Basis Function Networks using Moth-Flame Optimizer
29. Application of Fuzzy Methods in Power system Problems
30. Application of Particle Swarm Optimization Algorithm in Power system Problems
31. Optimum Design of Composite Steel-Concrete Floors Based on a Hybrid Genetic Algorithm
32. A Comparative Study of Image Segmentation Algorithms and Descriptors for Building Detection
33. Object-Oriented Random Forest for High Resolution Land Cover Mapping Using Quickbird-2 Imagery

Erscheinungsdatum	22.07.2017
Verlagsort	San Diego
Sprache	englisch
Maße	191 x 235 mm
Gewicht	1290 g
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
Themenwelt	Technik ► Umwelttechnik / Biotechnologie
ISBN-10	0-12-811318-9 / 0128113189
ISBN-13	978-0-12-811318-9 / 9780128113189
Zustand	Neuware