Skip to main navigation
Skip to search
Skip to main content
University of Portsmouth Home
Help & FAQ
Home
Profiles
Organisations
Research outputs
Student theses
Datasets
Projects
Activities
Prizes
Press/Media
Equipment
Search by expertise, name or affiliation
Neural network training and stochastic global optimization
I. Jordanov
*
*
Corresponding author for this work
School of Computing
De Montfort University
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Neural network training and stochastic global optimization'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Computer Science
Global Optimization
100%
Local Minimum
100%
Neural Network Training
100%
Optimization Problem
50%
Learning Process
50%
Supervised Learning
50%
Benchmark Problem
50%
Optimization Technique
50%
Discrepancy Sequence
50%
Stochastic Optimization
50%
Unconstrained Optimization
50%
Neural Network
50%
Objective Function
50%
back-propagation neural network
50%
Parameter Space
50%
INIS
optimization
100%
neural networks
100%
stochastic processes
100%
learning
50%
algorithms
50%
comparative evaluations
25%
space
25%
weight
25%
benchmarks
25%
Mathematics
Stochastics
100%
Neural Network
100%
Local Minimum
50%
Parameter Space
25%
Objective Function
25%
Mathematical Function
25%
Weight Function
25%
Network Weight
25%
Unconstrained Optimization Problem
25%
Global Optimum
25%
Chemical Engineering
Neural Network
100%
Supervised Learning
25%
Engineering
Neural Network Weight
50%