Search Results for "artificial neural network python"
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Showing 26 open source projects for "artificial neural network python"
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Frevo
Frevo is probably the simplest tool for evolutionary design
FREVO is an open-source framework developed in Java to help engineers and scientists in evolutionary design or optimization tasks. The major feature of FREVO is the componentwise decomposition and separation of the key building blocks for each optimization tasks. We identify these as the problem definition, solution representation and the optimization method. This structure enables the components to be designed separately allowing the user to easily swap and evaluate different configurations... -
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GNNePCSAFT
Smart Thermodynamic Modeling with Graph Neural Networks
Our project harnesses the power of Graph Neural Network (GNN) to estimate pure-component parameters of the state-of-the-art Equation of State, PC-SAFT. We aim to empower users to leverage this robust equation without the need for prior experimental data, revolutionizing the calculation of thermodynamic properties and enhancing process simulations. FeOS is used for the PC-SAFT calculations. The estimated parameters can be used in DWSIM and Aspen HYSYS process simulators. -
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Kinetic.jl
Universal modeling and simulation of fluid mechanics upon ML
Kinetic is a computational fluid dynamics toolbox written in Julia. It aims to furnish efficient modeling and simulation methodologies for fluid dynamics, augmented by the power of machine learning. Based on differentiable programming, mechanical and neural network models are fused and solved in a unified framework. Simultaneous 1-3 dimensional numerical simulations can be performed on CPUs and GPUs. -
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Neuroph is lightweight Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and GUI editor makes it easy to learn and use.
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Fully Connected Neural Network
Neural Network with Neurons with Multidimensional Activation Function.
Fully Connected Neural Network with Neurons with Multidimensional Activation Function. -
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eANN
eANN is an implementation of several kind of neural networks.
eANN is an implementation of several kind of neural networks written with the intention of providing a (hopefully) easy to use, and easy to modify, OOP source code. It is possible to have several different sized networks running simultaneously, each functioning independently of the others or acting as inputs between them. It also easy to modify the structure so that neurons (or even whole layers) can be created/pruned during simulation allowing dynamic expansion/contraction of the network. -
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nevesim
NEVESIM is an event-driven neural simulation tool.
NEVESIM is a software package for event-driven simulation of networks of spiking neurons with a fast simulation core in C++, and a scripting user interface in the Python programming language. It supports simulation of heterogeneous networks with different types of neurons and synapses, and can be easily extended by the user with new neuron and synapse types. To enable heterogeneous networks and extensibility, NEVESIM is designed to decouple the simulation logic of communicating events... -
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NOTE: This project was moved to: https://github.com/eetorres The BPANNA is a flexible Back propagation neural network, which include the Conjugate Gradient and the Levenberg-Marquardt. You can change the number of inputs, number of layers, number of neurons per layer and outputs. It included an structure editor.
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Fast flexible simulator of spiking neural networks. Easy to use graphical user interface with comprehensive monitoring facilities. Integrates with the NeMo CUDA simulator and the iSpike interface for the iCub robot.
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Open Exchange (OpEx)
The open source Algorithmic Trading System
OpEx is an application suite that includes the main building blocks of commercial electronic trading systems. All OpEx applications run on distributed system architectures. -
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Delayed Response Network
Neural network based on signal delays.
An artificial neural network, currently specialized to save a specific bit pattern, mainly by changing the signal propagation delays in links. More features, variables and algorithms will be added in time. -
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NeMo is a high-performance spiking neural network simulator which simulates networks of Izhikevich neurons on CUDA-enabled GPUs. NeMo is a C++ class library, with additional interfaces for pure C, Python, and Matlab.
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NeurAnim is a research aid for computational neuroscience. It is used to visualise and animate neural network simulations in 3D, and to render movies of these animations for use in presentations.
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SPLITNEURON is a completely new approach to large-scale, biologically plausible, neural-network simulation library based on data structures and methods directly coded into database and conceived to explicitly share load on multiple machines.
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The Mars Rover Simulator project is based on the evolutionary robotics paradigm where an artificial agent acquires its skills through the process of artificial evolution. This simulator can be useful to evolve neural network controllers for the rover
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Neural Network
Neural Network with Hypercube Neurons.
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This is an attempt to port Douglas Blank's neural network "Analogator" into Matlab. It does not yet work and any helping hands out there would be nice. A recent update to 'pyrobot' includes a contemporary implementation of Analogator but there are a
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Brainlab is a Python toolkit to aid in the design, simulation, and analysis of spiking neural networks with the NeoCortical Simulator (NCS).
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OpenDiscreteDynamicProgrammingTemplate : founds optimal constrainted parameters of a discrete controls with second order optimization template replacing Hessian with directional derivatives and backpropagation for digital filter(as neural network)
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A class library written in Objective-C++ for building models of connectionist networks (neural networks). The class-hierarchy is designed to be maximally general and expandable, but also to support specific types of network.
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We experiment with Evolution of Artifical Neural Networks, combining the two fields of Evolutionary Computation and ANNs. Our methods are applied to a variety of interesting problems. To learn more, click on "Home Page", "Mail", or "Files".
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Application of neural network to predict the future of stock exchange, aerospace ( ufo trajectory ), sound, image, noise, scientific or medical data. You need , by example, 100 days of a numeric data and the number of days to predict (by example 7 days).
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Simulator of virtual animals made up of biological neural networks for research in the Computational Neuroscience field.
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LiNNS is not just a Neural Network Simulator, but a Neural Network System - a framework which covers the full lifecycle of a neural network, from design and research till usage in an external application.
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