multi-layer feedforward neural network (MathWorks Inc)

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MathWorks Inc multi-layer feedforward neural network
Multi Layer Feedforward Neural Network, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/multi-layer+feedforward+network/pmc09274644-308-1-7
Average 90 stars, based on 1 article reviews

multi-layer feedforward neural network - by Bioz Stars, 2026-10

90/100 stars

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Article Title: Selective Identification of Hazardous Gases Using Flexible, Room-Temperature Operable Sensor Array Based on Reduced Graphene Oxide and Metal Oxide Nanoparticles via Machine Learning.
Article Snippet: Selective detection and monitoring of hazardous gases with similar properties are highly desirable to ensure human safety.. The development of flexible and room-temperature (RT) operable chemiresistive gas sensors provides an excellent opportunity to create wearable devices for detecting hazardous gases surrounding us.. However, chemiresistive gas sensors typically suffer from poor selectivity and zero-cross selectivity toward similar types of gases.

Article Title: A Recurrent Neural Network-based Approach for Ballistic Coefficient Estimation of Resident Space Objects in Low Earth Orbit
Article Snippet: The WNN is a feedforward neural network with 1 fully-connected hidden layer of 100 neurons, available on the MATLAB Regression Learner App (MathWorks, 2024b).

Article Title: Overview of the TCV digital real-time plasma control system and its applications
Article Snippet: These upgrades have enabled a number of experimental advances in terms of TCV control, some primary ones including: • SAMONE, a comprehensive real-time plasma supervision and actuator management system [10,11] • Plasma event detectors based upon physics models and neural networks [12] • Reinforcement-learning based magnetic control algorithms deployed as feedforward neural networks [13] • Novel linear controllers for improved vertical control [14] • Model-based multi-input multi-output gas controllers, aiming at simultaneous control of multiple gas influx related plasma parameters [15] Thanks to the strict separation between control codes (written and maintained in MATLAB/Simulink) and the real-time frameworks used to run them on the machine, most of the legacy real-time codes have already been ported within this new approach allowing them to seamlessly operate on every TCV discharge; notably they comprise LIUQE, TCV’s real-time magnetic equilibrium reconstruction running with a 1 ms cycle time [16], RT-MHD (Real Time Magneto Hydro Dynamics), a comprehensive real-time MHD analysis algorithm set [17], realtime main interferometer analysis, a multiple chord real-time Thomson scattering diagnostic code and real-time divertor radiation front detection with multispectral 2D imaging diagnostics (MANTIS).

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Article Title: Image based ice-field characterization and load prediction in managed ice field
Article Snippet: .. The purpose of feedforward neural networks is to approximate function and can be used for any kind of input to output mapping (MathWorks Inc, 2022b) It has been successfully applied to pattern classification, clustering, regression, association, optimization, control, and forecasting problems. ..

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