Journal ArticleDOI
Design of rubble-mound breakwaters using M5 ′ machine learning method
TLDR
This study presents another soft computing approach, i.e. model trees for predicting the stability number of armor blocks, and shows that the developed models are more accurate than previous empirical and soft computing models.About:
This article is published in Applied Ocean Research.The article was published on 2009-07-01. It has received 55 citations till now. The article focuses on the topics: Soft computing & Stability (learning theory).read more
Citations
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Journal ArticleDOI
A survey on river water quality modelling using artificial intelligence models: 2000–2020
TL;DR: Overall, this survey provides a new milestone in water resource engineering on the AI model implementation, innovation and transformation in surface WQ modelling with many formidable problems in different blossoming area and objectives to be achieved in the future.
Journal ArticleDOI
Predicting Longitudinal Dispersion Coefficient in Natural Streams Using M5′ Model Tree
TL;DR: In this article, a M5′ model tree was used to develop a new model for predicting the longitudinal dispersion coefficient, which is a key parameter in determining the distribution of pollution concentration, especially in temporally timevarying source cases after full cross-sectional mixing has occurred.
Journal ArticleDOI
Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq
Khabat Khosravi,Prasad Daggupati,Mohammad Taghi Alami,Salih Muhammad Awadh,Mazen Ismaeel Ghareb,Mehdi Panahi,Binh Thai Pham,Fatemeh Rezaie,Chongchong Qi,Zaher Mundher Yaseen +9 more
TL;DR: Investigations on the modeling accuracy with different input parameter combinations showed that, despite the different structures of the models, no single input combination showed a consistent modeling outcome.
Journal ArticleDOI
Model tree approach for prediction of pile groups scour due to waves
Amir Etemad-Shahidi,Negin Ghaemi +1 more
TL;DR: New formulas are given that are easy to use, accurate and physically sound for estimating the pile group scour depth, which can be so useful for engineers.
Journal ArticleDOI
Assessment of M5′ model tree and classification and regression trees for prediction of scour depth below free overfall spillways
TL;DR: Results of the present study indicated that model trees were more accurate than classification and regression trees for the estimation of scour depth and the proposed soft computing approaches outperform empirical formulas.
References
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Rock slopes and gravel beaches under wave attack
TL;DR: In this article, the stability of cliff slopes and gravel beaches under wave attack has been investigated with the aid of small and large scale physical models, and the range from "no damage" to statically stable structures up to the profile development of very small (4 mm) shingle under prototype circumstan-
Journal ArticleDOI
Model trees as an alternative to neural networks in rainfall-runoff modelling
TL;DR: In this paper, the applicability of two data-driven modeling techniques, namely, artificial neural networks (ANNs) and model trees (MTs), in rainfall runoff transformation was investigated by predicting runoff one, three and six hours ahead for a European catchment.
Journal ArticleDOI
M5 Model Trees and Neural Networks: Application to Flood Forecasting in the Upper Reach of the Huai River in China
Dimitri Solomatine,Yunpeng Xue +1 more
TL;DR: It is shown that model trees, being analogous to piecewise linear functions, have certain advantages compared to ANNs—they are more transparent and hence acceptable by decision makers, are very fast in training and always converge.
Journal ArticleDOI
Application of fuzzy inference system in the prediction of wave parameters
TL;DR: Investigation of the performance of Adaptive-Network-Based Fuzzy Inference System (ANFIS) and Coastal Engineering Manual methods for predicting wave parameters found that ANFIS outperforms the CEM method in terms of prediction capability, while CEM results in more accurate predictions.
Journal ArticleDOI
Stability of breakwater armour layers — design formulae
TL;DR: In this paper, a series of practical design formulae have been developed which describe the stability of rubble mound revetments and breakwaters under random wave attack, based upon a seriesof model tests.
Related Papers (5)
Comparison between m5 model tree and neural networks for prediction of significant wave height in lake superior
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