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Spectral Topography of the Subthalamic Nucleus to Inform Next‐Generation Deep Brain Stimulation

Movement disorders, 2023-05, Vol.38 (5), p.818-830

2023

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Investigation on factors affecting early strength of high-performance concrete by Gaussian Process Regression

PloS one, 2022-01, Vol.17 (1), p.e0262930-e0262930

2022

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Deep Brain Stimulation for Chronic Cluster Headache: Meta‐Analysis of Individual Patient Data

Annals of neurology, 2020-11, Vol.88 (5), p.956-969

2020

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Optimization of Artificial Intelligence System by Evolutionary Algorithm for Prediction of Axial Capacity of Rectangular Concrete Filled Steel Tubes under Compression

Materials, 2020-03, Vol.13 (5), p.1205

2020

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Investigation of ANN architecture for predicting the compressive strength of concrete containing GGBFS

PloS one, 2021-12, Vol.16 (12), p.e0260847

2021

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Investigation of ANN architecture for predicting shear strength of fiber reinforcement bars concrete beams

PloS one, 2021-04, Vol.16 (4), p.e0247391-e0247391

2021

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Universal boosting ML approaches to predict the ultimate load capacity of CFST columns

The structural design of tall and special buildings, 2024-02, Vol.33 (2), p.n/a

2024

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A Novel Hybrid Model Based on a Feedforward Neural Network and One Step Secant Algorithm for Prediction of Load-Bearing Capacity of Rectangular Concrete-Filled Steel Tube Columns

Molecules (Basel, Switzerland), 2020-07, Vol.25 (15), p.3486

2020

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Interplay of spin-orbit coupling and superconducting correlations in germanium telluride thin films

Physica status solidi. PSS-RRL. Rapid research letters, 2016-03, Vol.10 (3), p.253-259

2016

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Accelerating fluid flow simulations through doubly porous media using a FEM-assisted machine learning approach

Results in physics, 2023-11, Vol.54, p.107036, Article 107036

2023

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Prediction Compressive Strength of Concrete Containing GGBFS using Random Forest Model

Advances in Civil Engineering, 2021, Vol.2021 (1)

2021

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Backpropagation Neural Network-Based Machine Learning Model for Prediction of Soil Friction Angle

Mathematical problems in engineering, 2020-12, Vol.2020, p.1-11

2020

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Beamforming-as-a-Service for Multicast and Broadcast Services in 5G systems and Beyond

IEEE access, 2023-01, Vol.11, p.1-1

2023

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Parametric Investigation of Particle Swarm Optimization to Improve the Performance of the Adaptive Neuro-Fuzzy Inference System in Determining the Buckling Capacity of Circular Opening Steel Beams

Materials, 2020-05, Vol.13 (10), p.2210

2020

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A hybrid machine learning model to estimate self-compacting concrete compressive strength

Frontiers of Structural and Civil Engineering, 2022-08, Vol.16 (8), p.990-1002

2022

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Estimation of Soil Cohesion Using Machine Learning Method: A Random Forest Approach

Advances in Civil Engineering, 2021, Vol.2021 (1)

2021

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Investigation of ANN Architecture for Predicting Load-Carrying Capacity of Castellated Steel Beams

Complexity (New York, N.Y.), 2021, Vol.2021 (1)

2021

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On the Training Algorithms for Artificial Neural Network in Predicting the Shear Strength of Deep Beams

Complexity (New York, N.Y.), 2021, Vol.2021 (1)

2021

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Investigation of ANN Model Containing One Hidden Layer for Predicting Compressive Strength of Concrete with Blast-Furnace Slag and Fly Ash

Advances in materials science and engineering, 2021, Vol.2021 (1)

2021

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Predicting shear strength of slender beams without reinforcement using hybrid gradient boosting trees and optimization algorithms

Frontiers of Structural and Civil Engineering, 2022-12, Vol.16 (10), p.1267-1286

2022

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Combining Multimodal Biomarkers to Guide Deep Brain Stimulation Programming in Parkinson Disease

Neuromodulation (Malden, Mass.), 2023-02, Vol.26 (2), p.320-332

2023

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Ensemble Tree-Based Approach to Predict the Rotation Capacity of Wide-Flange Beams

Advances in Civil Engineering, 2022, Vol.2022 (1)

2022

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Assessment of different machine learning techniques in predicting the compressive strength of self-compacting concrete

Frontiers of Structural and Civil Engineering, 2022-07, Vol.16 (7), p.928-945

2022

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Development of deep neural network model to predict the compressive strength of rubber concrete

Construction & building materials, 2021-09, Vol.301, p.124081, Article 124081

2021

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Awake craniotomy for gliomas in a high-field intraoperative magnetic resonance imaging suite: analysis of 42 cases

Journal of neurosurgery, 2014-10, Vol.121 (4), p.810-817

2014

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Spectral Topography of the Subthalamic Nucleus to Inform Next‐Generation Deep Brain Stimulation

Investigation on factors affecting early strength of high-performance concrete by Gaussian Process Regression

Deep Brain Stimulation for Chronic Cluster Headache: Meta‐Analysis of Individual Patient Data

Optimization of Artificial Intelligence System by Evolutionary Algorithm for Prediction of Axial Capacity of Rectangular Concrete Filled Steel Tubes under Compression

Investigation of ANN architecture for predicting the compressive strength of concrete containing GGBFS

Investigation of ANN architecture for predicting shear strength of fiber reinforcement bars concrete beams

Universal boosting ML approaches to predict the ultimate load capacity of CFST columns

A Novel Hybrid Model Based on a Feedforward Neural Network and One Step Secant Algorithm for Prediction of Load-Bearing Capacity of Rectangular Concrete-Filled Steel Tube Columns

Interplay of spin-orbit coupling and superconducting correlations in germanium telluride thin films

Accelerating fluid flow simulations through doubly porous media using a FEM-assisted machine learning approach

Prediction Compressive Strength of Concrete Containing GGBFS using Random Forest Model

Backpropagation Neural Network-Based Machine Learning Model for Prediction of Soil Friction Angle

Beamforming-as-a-Service for Multicast and Broadcast Services in 5G systems and Beyond

Parametric Investigation of Particle Swarm Optimization to Improve the Performance of the Adaptive Neuro-Fuzzy Inference System in Determining the Buckling Capacity of Circular Opening Steel Beams

A hybrid machine learning model to estimate self-compacting concrete compressive strength

Estimation of Soil Cohesion Using Machine Learning Method: A Random Forest Approach

Investigation of ANN Architecture for Predicting Load-Carrying Capacity of Castellated Steel Beams

On the Training Algorithms for Artificial Neural Network in Predicting the Shear Strength of Deep Beams

Investigation of ANN Model Containing One Hidden Layer for Predicting Compressive Strength of Concrete with Blast-Furnace Slag and Fly Ash

Predicting shear strength of slender beams without reinforcement using hybrid gradient boosting trees and optimization algorithms

Combining Multimodal Biomarkers to Guide Deep Brain Stimulation Programming in Parkinson Disease

Ensemble Tree-Based Approach to Predict the Rotation Capacity of Wide-Flange Beams

Assessment of different machine learning techniques in predicting the compressive strength of self-compacting concrete

Development of deep neural network model to predict the compressive strength of rubber concrete

Awake craniotomy for gliomas in a high-field intraoperative magnetic resonance imaging suite: analysis of 42 cases

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