Journal ArticleDOI
Forecasting hurricane wave height in Gulf of Mexico using soft computing methods
Somayeh Mafi,Gholamreza Amirinia +1 more
About:
This article is published in Ocean Engineering.The article was published on 2017-12-01. It has received 37 citations till now. The article focuses on the topics: Wave height & Wind speed.read more
Citations
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Journal ArticleDOI
Machine Learning Methods to Analyze Injury Severity of Drivers from Different Age and Gender Groups
TL;DR: In this article, non-biased and accurate models capable of predicting driver injury severity of collision events are used for determining what safety measures should be implemented at intersections, which is vital for determining whether or not to implement safety measures at intersections.
Journal ArticleDOI
Wave height predictions in complex sea flows through soft-computing models: Case study of Persian Gulf
TL;DR: In this paper , the capability of Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), M5P, and Random Forest (RF) soft-computing approaches for the prediction of wave height over Persian Gulf was examined.
Journal ArticleDOI
A wavelet - Particle swarm optimization - Extreme learning machine hybrid modeling for significant wave height prediction
TL;DR: In this article, a wavelet-particle swarm optimization (PSO)-ELM (WPSO-ELM) model was proposed to predict the ocean wave height via developing a novel hybrid algorithm.
Journal ArticleDOI
A review of Genetic Programming and Artificial Neural Network applications in pile foundations
TL;DR: This paper provides a review of GP and ANN applications in estimation of the pile foundations bearing capacity and concludes that Genetic Programming and Artificial Neural Network are popular and particularly amenable option in geotechnical engineering applications.
Journal ArticleDOI
Probabilistic Prediction of Significant Wave Height Using Dynamic Bayesian Network and Information Flow
Ming Li,Kefeng Liu +1 more
TL;DR: A machine learning model by combining the dynamic Bayesian network with the information flow designated as DBN-IF that could deal with the uncertainty and shows great performance in significant wave height prediction compared with the artificial neural network, random forest, and support vector machine for all lead times.
References
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Journal ArticleDOI
Random Forests
TL;DR: Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.
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The Nature of Statistical Learning Theory
TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
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Least Squares Support Vector Machine Classifiers
TL;DR: A least squares version for support vector machine (SVM) classifiers that follows from solving a set of linear equations, instead of quadratic programming for classical SVM's.
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A third-generation wave model for coastal regions: 1. Model description and validation
TL;DR: In this article, a third-generation numerical wave model to compute random, short-crested waves in coastal regions with shallow water and ambient currents (Simulating Waves Nearshore (SWAN)) has been developed, implemented, and validated.
Journal ArticleDOI
Open Ocean Momentum Flux Measurements in Moderate to Strong Winds
W. G. Large,Stephen Pond +1 more
TL;DR: In this article, a comparison of the dissipation and Reynolds flux results shows excellent agreement on average, for wind speeds from 4 to 20 m s−1, for a modified Gill propeller-vane anemometer was used to measure the velocity.
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