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Full Description
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.
Contents
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
