Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences
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Summary
This paper presents a general introduction and discussion of recent applications of the multilayer perceptron, one type of artificial neural network, in the atmospheric sciences.
- Type
- article
- Published
- 1998-08-01
- Cited by
- 3,180
- References
- 45
- OpenAlex
- https://openalex.org/W1977177161
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:109217282
Keywords
Artificial neural network, Perceptron, Multilayer perceptron, Computer science, Artificial intelligence
References
- Artificial neural network classification using a minimal training set - Comparison to conventional supervised classification
- Introducing Artificial Intelligence
- Neural networks for pattern recognition
- Interpreting neural-network connection weights
- Wind ambiguity removal by the use of neural network techniques
- A First-Guess Feature-Based Algorithm for Estimating Wind Speed in Clear-Air Doppler Radar Spectra
- Polar Cloud and Surface Classification Using AVHRR Imagery: An Intercomparison of Methods
- Forecasting carbon monoxide concentrations near a sheltered intersection using video traffic surveillance and neural networks
- A neural network model forecasting for prediction of daily maximum ozone concentration in an industrialized urban area.
- Artificial Neural Networks: A Tutorial
- First- and Second-Order Methods for Learning: Between Steepest Descent and Newton's Method
- An intercomparison of artificial intelligence approaches for polar scene identification
- Thin-line detection in meteorological radar images using wavelet transforms
- Results from the UN/ECE ICP-Crops indicate the extent of exceedance of the critical levels of ozone in Europe
- Prediction of solar and geomagnetic activity data using neural networks
- A neural network approach for modeling nonlinear transfer functions: Application for wind retrieval from spaceborne scatterometer data
- Toward Automated Interpretation of Satellite Imagery for Navy Shipboard Applications
- A Neural Network for Tornado Prediction Based on Doppler Radar-Derived Attributes
- A Simple Neural Network for Estimating Emission Rates of Hydrogen Sulfide and Ammonia from Single Point Sources.
- Development of a neural network model to predict daily solar radiation
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- Vers une métrologie olfactive de la qualité de l'air intérieur. Correspondances entre les données de l'analyse sensorielle, de l'analyse chimique et d'un "nez électronique".
- Prediction of CO maximum ground level concentrations in the Bay of Algeciras, Spain using artificial neural networks.
- Mechanical properties of materials for fusion power plants
- Comparison of linear model and artificial neural network using antler beam diameter and length of white-tailed deer (Odocoileus virginianus) dataset
- Predicting Methane Concentration in Longwall Regions Using Artificial Neural Networks
- A real-time system to recognize static gestures of Brazilian sign language (libras) alphabet using Kinect
- ARTIFICIAL NEURAL NETWORK APPLICATIONS IN GEOTECHNICAL ENGINEERING
- A method for knowledge discovery and development with health data
- Pollution modelling for Hong Kong downtown area using principal component analysis and artificial neural networks
- A Cyclostationary Neural Network model for the prediction of the NO2 concentration
- Bayesian Networks for Probabilistic Weather Prediction
- Event Classification and Estimation of Low Mass Diffraction at the TOTEM Experiment at the LHC
- Analysis of urban land use and land cover changes: a case of study in Bahir Dar, Ethiopia
- Unsupervised Artificial Neural Network for Efficient Mapping of Doweled Concrete Pavement Joints Condition
- Emergence of internal representations in evolutionary robotics : influence of multiple selective pressures
- Analysis of Immunosignaturing Case Studies
- Detecting Command and Control Channels of a Botnet Using a N-packet-based Approach
- Vehicular pollution modeling using artificial neural network technique: A review
- Analysis of Pollutant Levels in Central Hong Kong Applying Neural Network Method with Particle Swarm Optimization
- A neural network model for predicting typhoon intensity
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