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Tiyasha Tiyasha

Researcher at Ton Duc Thang University

Publications -  13
Citations -  328

Tiyasha Tiyasha is an academic researcher from Ton Duc Thang University. The author has contributed to research in topics: Computer science & Support vector machine. The author has an hindex of 5, co-authored 8 publications receiving 58 citations.

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Artificial intelligence models for suspended river sediment prediction: state-of-the art, modeling framework appraisal, and proposed future research directions

TL;DR: Sediment transport in a river basin is therefore a multifa... as discussed by the authors, which is an important indicator for ecological and geomorphological assessments of soil erosion within any watershed region.
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State-of-the Art-Powerhouse, Dam Structure, and Turbine Operation and Vibrations

TL;DR: In this article, the authors conducted a comprehensive review of studies performed on dams, powerhouses, and turbine vibration, focusing on the vibration of two turbine units: Kaplan and Francis turbine units.
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Prediction of lead (Pb) adsorption on attapulgite clay using the feasibility of data intelligence models

TL;DR: In this article, the performance of support vector machine (SVM), multivariate adaptive regression spline (MARS), and random forest (RF) models for predicting the lead (Pb) adsorption by attapulgite clay was investigated.
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Integrative artificial intelligence models for Australian coastal sediment lead prediction: An investigation of in-situ measurements and meteorological parameters effects.

TL;DR: In this paper , three feature selection algorithms namely the Boruta method, genetic algorithm (GA) and extreme gradient boosting (XGBoost) were investigated to select the highly important predictors for Pb concentration in the coastal bay sediments of Australia.
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Dual Water Choices: The Assessment of the Influential Factors on Water Sources Choices Using Unsupervised Machine Learning Market Basket Analysis

TL;DR: An unsupervised machine learning model of association rule known as market basket analysis is proposed in this paper to analyze the influence of various socio-economic factors on the choice of the water source.