Using Machine Learning to Examine Impact of Type of Performance Indicator on Flexible Pavement Deterioration Modeling

Piryonesi, S. Madeh; El-Diraby, Tamer E.

doi:10.1061/(asce)is.1943-555x.0000602

Cited by 81 publications

(29 citation statements)

References 44 publications

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“…We applied gradient boosting algorithms with a to solve the problem of DMBP. Gradient boosting algorithms performed effectively and gave a solution within 0.25% of the global optimum [20][21][22][23][24][25][26][27][28][29][30][31].…”

Section: Discussionmentioning

confidence: 99%

Optimization of Multiproduct Batch Plant Design for Protein Production Using Gradient Boosting Algorithms

2021

J B & Bio Engine;

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This work deals with the problem of modeling and prediction of compressive strength of concrete structure in multiproduct batch plant design of protein production found in a chemical engineering process with uncertain demand. Modeling the strength of concrete for this process is very complex. However, it can be solved by minimizing the investment cost. Therefore, the aim of this work is to minimize the investment cost and find out the number and size of parallel equipment units in each stage. For this purpose, it is proposed to solve the problem by using gradient boosting algorithms, could be interpreted as an optimization algorithm on a suitable cost function. Which take into account, the uncertainty on the demand using gaussian process modeling. The results about number and size of equipments investment cost, production time, process time and Idle times in plant obtained by gradient boosting algorithms are the best. This methodology can help the decision makers and constitutes a very promising framework for finding a set of “good solutions”.

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Section: Discussionmentioning

confidence: 99%

Optimization of Multiproduct Batch Plant Design for Protein Production Using Gradient Boosting Algorithms

2021

J B & Bio Engine;

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“…Boosting is an additional generic ensemble technique that attempts to boost the accuracy of any given learning algorithm (Piryonesi and El-Diraby, 2020). The focus of boosting methods is to produce a series of weak learners in order to produce a powerful combination (Hastie et al, 2009;Piryonesi and El-Diraby, 2021). A weak learner is a learner that has accuracy only slightly better than chance.…”

Section: Gradient Boosted Treesmentioning

confidence: 99%

Prediction of daily global solar radiation and air temperature using six machine learning algorithms; a case of 27 European countries

Nematchoua

Orosa

Afaifia

2022

Ecological Informatics

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“…When a decision tree is used as the weak learner, the boosting algorithm is usually called gradient boosted trees. Gradient boosted trees usually outperforms the random forest and have been used successfully to solve civil engineering problems [41,42].…”

Section: The Vessel Movement Predictors Creationmentioning

confidence: 99%

Machine Learning Based Moored Ship Movement Prediction

Alvarellos

Figuero

Carro

et al. 2021

JMSE

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Several port authorities are involved in the R+D+i projects for developing port management decision-making tools. We recorded the movements of 46 ships in the Outer Port of Punta Langosteira (A Coruña, Spain) from 2015 until 2020. Using this data, we created neural networks and gradient boosting models that predict the six degrees of freedom of a moored vessel from ocean-meteorological data and ship characteristics. The best models achieve, for the surge, sway, heave, roll, pitch and yaw movements, a 0.99, 0.99, 0.95, 0.99, 0.98 and 0.98 R2 in training and have a 0.10 m, 0.11 m, 0.09 m, 0.9°, 0.11° and 0.15° RMSE in testing, all below 10% of the corresponding movement range. Using these models with forecast data for the weather conditions and sea state and the ship characteristics and berthing location, we can predict the ship movements several days in advance. These results are good enough to reliably compare the models' predictions with the limiting motion criteria for safe working conditions of ship (un) loading operations, helping us decide the best location for operation and when to stop operations more precisely, thus minimizing the economic impact of cargo ships unable to operate.

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Using Machine Learning to Examine Impact of Type of Performance Indicator on Flexible Pavement Deterioration Modeling

Cited by 81 publications

References 44 publications

Optimization of Multiproduct Batch Plant Design for Protein Production Using Gradient Boosting Algorithms

Optimization of Multiproduct Batch Plant Design for Protein Production Using Gradient Boosting Algorithms

Prediction of daily global solar radiation and air temperature using six machine learning algorithms; a case of 27 European countries

Machine Learning Based Moored Ship Movement Prediction

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