DownloadThis project includes the implementation of a neural network MLP, RBF, SOM and Hopfield networks in several popular programming languages. The project also includes examples of the use of neural networks as function approximation and time series prediction. Includes a special program makes it easy to test neural network based on training data and the optimization of the network.
Features
- multilayer perceptron neural network
- linear, sigmoid and bipolar sigmoid activation functions
- training, generalization and validation datasets
- backpropagation learning algorithm
- save the trained neural network to a file using binary serialization
- load neural network from file using binary deserialization
- approximation of functions of several variables
- time series prediction
- pattern recognition
- usefulness to solve most of the problems
- simple expert systems
- included simulation program for .NET
Project Samples
License
GNU Library or Lesser General Public License version 2.0 (LGPLv2)Follow Neural Libs
You Might Also Like
SafetyIQ is revolutionizing the way businesses approach safety. As a leading provider of comprehensive workplace safety software, we cater to four key areas: Mobile Worker Safety, EHS (Environment, Health, and Safety), Fatigue Management, and Training. Our platform is designed to safeguard your workers, no matter their location or task, ensuring all-around safety compliance.
Unlike most safety software providers that only react to incidents or implement proactive measures, SafetyIQ introduces a third pillar to safety management - predictive analytics. We transform the untapped wealth of safety data within your organization into actionable insights to inform safety strategies, mitigating risks even before they aris
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of Neural Libs!