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[HTML][HTML] Forecasting particle Froude number in non-deposition scenarios within sewer pipes through hybrid machine learning approaches
Sediment deposition has a substantial effect on the hydraulic capacity of channels in urban
drainage and sewer systems. In this sense, the self-cleaning concept has been extensively …
drainage and sewer systems. In this sense, the self-cleaning concept has been extensively …
Performance evaluation of machine learning algorithms for the prediction of particle Froude number (Frn) using hyper-parameter optimizations techniques
The sewer system is a critical component of urban infrastructure, responsible for transporting
wastewater and stormwater away from populated areas. Proper design and management of …
wastewater and stormwater away from populated areas. Proper design and management of …
Predicting flow velocity in a vegetative alluvial channel using standalone and hybrid machine learning techniques
The presence of vegetation in the water bodies has a profound effect on the flow velocity in
an open channel due to the resistance offered by it. In rivers, estuaries, and coastal …
an open channel due to the resistance offered by it. In rivers, estuaries, and coastal …
Forecasting of time-dependent scour depth based on bagging and boosting machine learning approaches
Forecasting the time-dependent scour depth (dst) is very important for the protection of
bridge structures. Since scour is the result of a complicated interaction between structure …
bridge structures. Since scour is the result of a complicated interaction between structure …
A metaheuristic-based task offloading scheme with a trade-off between delay and resource utilization in IoT platform
Fog computing has emerged as the most popular technology for processing delay-sensitive
tasks in the Internet of Things platform. However, offloading tasks to suitable fog nodes (FNs) …
tasks in the Internet of Things platform. However, offloading tasks to suitable fog nodes (FNs) …
Radial basis function regression (RBFR), ARRBFR models for estimation of particle Froude number in sewer pipes under deposited conditions
The amount of water that can flow through a channel is affected by sediment deposition in
water drainage. Because of this, the self-cleaning mechanism is used a lot in sewer systems …
water drainage. Because of this, the self-cleaning mechanism is used a lot in sewer systems …
Estimation of particle Froude number in deposited bed condition using hybrid machine learning models
In hydrology, maintaining self-cleaning capabilities in drainage systems is crucial to prevent
sediment deposition at the bottom of channels. This deposition can disrupt the hydraulic …
sediment deposition at the bottom of channels. This deposition can disrupt the hydraulic …
Efficient functioning of a sewer system: application of novel hybrid machine learning methods for the prediction of particle Froude number
Sewer systems are usually built with a self-cleaning system that keeps the bottom of the
channel free of sediment to lessen the effects of the constant buildup of sediment particles …
channel free of sediment to lessen the effects of the constant buildup of sediment particles …
Predict Total Sediment Load Using Standalone and Ensemble Machine Learning Models
Sediment load includes bed and suspended loads. Bed load is sediment on a river's bottom,
while a suspended load is sediment floating in water currents. The nonlinear and …
while a suspended load is sediment floating in water currents. The nonlinear and …
Performance Evaluation of Thresholding-Based Segmentation Algorithms for Aerial Imagery
The effectiveness of various threshold-based segmentation algorithms is examined in this
study utilizing aerial images, with a focus on accuracy metrics including intersection over …
study utilizing aerial images, with a focus on accuracy metrics including intersection over …