Neural Networks for Modeling and Control of Particle Accelerators
Explore this paper's citation graph
- Type
- article
- Published
- 2016-04-20
- Cited by
- 117
- References
- 141
- Access
- Open access
- OpenAlex
- https://openalex.org/W2339485419
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:25280674
Keywords
Artificial neural network, Computer science, Artificial intelligence, Control system, Control (management)
References
- Extremum Seeking for stabilization
- An Intelligent Control Architecture for Accelerator Beamline Tuning
- Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner’s Handbook
- Learning Recurrent Neural Networks with Hessian-Free Optimization
- Gradient Flow in Recurrent Nets: the Difficulty of Learning Long-Term Dependencies
- Neural networks - methodology and applications
- Adaptive neuro-fuzzy controller for non-linear chemical mixing process
- Neural network technique for orbit correction in accelerators/storage rings
- Developing a general purpose intelligent control system for particle accelerators
- CNN-based real-time video detection of plasma instability in nuclear fusion applications
- Faster reinforcement learning after pretraining deep networks to predict state dynamics
- On the difficulty of training recurrent neural networks
- Nonlinear Identification and Control: A Neural Network Approach
- Modeling of transport phenomena in tokamak plasmas with neural networks
- Neural networks for control systems - A survey
- Applications and Science of Neural Networks, Fuzzy Systems and Evolutionary Computation IV
- Reinforcement learning in robotics: A survey
- Constrained model predictive control: Stability and optimality
- Optimization of injection molding process parameters using combination of artificial neural network and genetic algorithm method
- Multi-agent cooperation for particle accelerator control
Cited by
- Advanced controls for light sources
- Accurate prediction of X-ray pulse properties from a free-electron laser using machine learning
- Resonant Frequency Control For the PIP-II Injector Test RFQ: Control Framework and Initial Results
- Elman neural network identify elders fall signal base on second-order train method
- Machine learning for analysis of plasma driven Ion source
- Method and technology of synthesis of neural network models of object control with their hardware implementation on FPGA
- Evaluation of Machine Learning Methods for LHC Optics Measurements and Corrections Software
- Machine learning at the energy and intensity frontiers of particle physics
- Demonstration of Model-Independent Control of the Longitudinal Phase Space of Electron Beams in the Linac-Coherent Light Source with Femtosecond Resolution.
- Intelligent Controls for the Electron Storage Ring DELTA
- Machine learning-based longitudinal phase space prediction of particle accelerators
- Optimal matching control of a low energy charged particle beam in particle accelerators
- Machine learning for orders of magnitude speedup in multiobjective optimization of particle accelerator systems
- Accelerating lattice quantum Monte Carlo simulations using artificial neural networks: Application to the Holstein model
- Neural Network Model Of The PXIE RFQ Cooling System and Resonant Frequency Response
- Model-independent tuning for maximizing free electron laser pulse energy
- Unsupervised constrained neural network modeling of boundary value corneal model for eye surgery
- Studies in Applying Machine Learning to LLRF and Resonance Control in Superconducting RF Cavities
- Predicting particle accelerator failures using binary classifiers
- Toward the Application of Reinforcement Learning to the Intensity Control of a Seeded Free-Electron Laser
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