Resource Type

Journal Article 246

Year

2024 14

2023 19

2022 15

2021 11

2020 12

2019 12

2018 12

2017 12

2016 3

2015 13

2014 4

2013 6

2012 6

2011 11

2010 13

2009 20

2008 15

2007 10

2006 6

2005 8

open ︾

Keywords

technique 4

CO2 capture 2

Extreme learning machine 2

Machine learning 2

blast load 2

engineering 2

extreme gradient boosting technique 2

gradient boosting 2

gradient method 2

key technique 2

mining technique 2

numerical simulation 2

parametric analysis 2

temperature gradient 2

trans-oceanic bridge 2

3D pore volume distribution 1

3D shape factor 1

Cynoglossus semilaevis 1

Iris lactea Pall. var. chinensis (Fisch.) Koidz 1

open ︾

Search scope:

排序： Display mode:

strength prediction and optimization design of sustainable concrete based on squirrel search algorithm-extremegradient boosting technique

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 9,   Pages 1310-1325 doi: 10.1007/s11709-023-0997-3

Abstract: traditional compressive strength test, this study combines five novel metaheuristic algorithms with extremegradient boosting (XGB) to predict the compressive strength of green concrete based on fly ash and blastThe results indicated that the squirrel search algorithm-extreme gradient boosting (SSA-XGB) yieldedTherefore, the developed hybrid XGB model can be introduced as an accurate and fast technique for the

Keywords： sustainable concrete     fly ash     slay     extreme gradient boosting technique     squirrel search algorithm    

HTML PDF Collect

Application of extreme gradient boosting in predicting the viscoelastic characteristics of graphene oxide

Frontiers of Structural and Civil Engineering 2024, Volume 18, Issue 6,   Pages 899-917 doi: 10.1007/s11709-024-1025-y

Abstract: The purpose of this investigation is to construct an extreme gradient boosting (XGB) model to predict

Keywords： complex modulus     phase angle     graphene oxide     asphalt     extreme gradient boosting     machine learning    

HTML PDF Collect

A comprehensive comparison of different regression techniques and nature-inspired optimization algorithms to predict carbonation depth of recycled aggregate concrete

Frontiers of Structural and Civil Engineering 2023, Volume 18, Issue 1,   Pages 30-50 doi: 10.1007/s11709-024-1041-y

Abstract: It was found that the best prediction performance was obtained from extreme gradient boosting-multi-universe

Keywords： recycled aggregate concrete     carbonation depth     nature-inspired optimization algorithms     extreme gradientboosting technique     parametric analysis    

HTML PDF Collect

Gradient boosting dendritic network for ultra-short-term PV power prediction

Frontiers in Energy doi: 10.1007/s11708-024-0915-y

Abstract: Based on a gradient boosting strategy and a dendritic network, this paper proposes a novel ensemble predictionmodel, named gradient boosting dendritic network (GBDD) model which can reduce the forecast error by

Keywords： photovoltaic (PV) power prediction     dendrite network     gradient boosting strategy    

HTML PDF Collect

Machine learning enabled prediction and process optimization of VFA production from riboflavin-mediated sludge fermentation

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 11, doi: 10.1007/s11783-023-1735-8

Abstract:

● Data-driven approach was used to simulate VFA production from WAS fermentation.

Keywords： Machine learning     Volatile fatty acids     Riboflavin     Waste activated sludge     eXtreme Gradient Boosting    

HTML PDF Collect

An efficient improved Gradient Boosting for strain prediction in Near-Surface Mounted fiber-reinforced

Frontiers of Structural and Civil Engineering 2024, Volume 18, Issue 8,   Pages 1148-1168 doi: 10.1007/s11709-024-1079-x

Abstract: The Near-Surface Mounted (NSM) strengthening technique has emerged as a promising alternative to traditionalapplication of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is proposed to optimize GradientBoosting (GB) training performance for concrete strain prediction in NSM-FRP RC.

Keywords： NSM technique     fiber-reinforced polymer rods     static and dynamic analysis     GB     PSO     GA     finite element    

HTML PDF Collect

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

Thuy-Anh NGUYEN; Hai-Bang LY; Van Quan TRAN

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 10,   Pages 1267-1286 doi: 10.1007/s11709-022-0842-0

Abstract: Gradient Boosting (GB) technique was developed and evaluated in combination with three different optimization

Keywords： slender beam     shear strength     gradient boosting     optimization algorithms    

HTML PDF Collect

Application of machine learning technique for predicting and evaluating chloride ingress in concrete

Van Quan TRAN; Van Loi GIAP; Dinh Phien VU; Riya Catherine GEORGE; Lanh Si HO

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 9,   Pages 1153-1169 doi: 10.1007/s11709-022-0830-4

Abstract: This research aims at predicting the chloride content in concrete using three hybrid models of gradientboosting (GB), artificial neural network (ANN), and random forest (RF) in combination with particle

Keywords： gradient boosting     random forest     chloride content     concrete     sensitivity analysis.    

HTML PDF Collect

Development of gradient boosting-assisted machine learning data-driven model for free chlorine residual

Frontiers of Environmental Science & Engineering 2024, Volume 18, Issue 2, doi: 10.1007/s11783-024-1777-6

Abstract:

● A machine learning approach was applied to predict free chlorine residuals.

Keywords： Machine learning     Data-driven modeling     Drinking water treatment     Disinfection     Chlorination    

HTML PDF Collect

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

Van Quan TRAN; Hai-Van Thi MAI; Thuy-Anh NGUYEN; Hai-Bang LY

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 7,   Pages 928-945 doi: 10.1007/s11709-022-0837-x

Abstract: (CS of SCC) can be successfully predicted from mix design and curing age by a machine learning (ML) techniquenamed the Extreme Gradient Boosting (XGB) algorithm, including non-hybrid and hybrid models.K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Trees (DTR), Random Forest (RF), GradientBoosting (GB), and Artificial Neural Network using two training algorithms LBFGS and SGD (denoted as

Keywords： compressive strength     self-compacting concrete     machine learning techniques     particle swarm optimization     extremegradient boosting    

HTML PDF Collect

New technique of precision necking for long tubes with variable wall thickness

Yongqiang GUO, Chunguo XU, Jingtao HAN, Zhengyu WANG

Frontiers of Mechanical Engineering 2020, Volume 15, Issue 4,   Pages 622-630 doi: 10.1007/s11465-019-0565-7

Abstract: ultimate limit deformation with a necking coefficient of 0.68 could be achieved using the temperature gradient

Keywords： extrusion     rear axle     necking coefficient     temperature gradient    

HTML PDF Collect

SPT based determination of undrained shear strength: Regression models and machine learning

Walid Khalid MBARAK, Esma Nur CINICIOGLU, Ozer CINICIOGLU

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 1,   Pages 185-198 doi: 10.1007/s11709-019-0591-x

Abstract: of simple and multiple linear regression models, three machine learning algorithms, random forest, gradientboosting and stacked models, are developed for prediction of undrained shear strength.

Keywords： undrained shear strength     linear regression     random forest     gradient boosting     machine learning     standard    

HTML PDF Collect

Initial-condition-switched boosting extreme multistability and mechanism analysis in a memcapacitive Research Articles

Bei Chen, Quan Xu, Mo Chen, Huagan Wu, Bocheng Bao,mervinbao@126.com

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 11,   Pages 1517-1531 doi: 10.1631/FITEE.2000622

Abstract: has seized scientists’ attention due to its rich diversity of dynamical behaviors and great flexibility in engineering applications. In this paper, a four-dimensional (4D) is built using four linear circuit elements and one nonlinear charge-controlled memcapacitor with a cosine inverse memcapacitance. The 4D possesses a line equilibrium set, and its stability periodically evolves with the initial condition of the memcapacitor. The 4D exhibits due to the periodically evolving stability. Complex dynamical behaviors of period doubling/halving bifurcations, chaos crisis, and initial-condition-switched coexisting attractors are revealed by bifurcation diagrams, Lyapunov exponents, and phase portraits. Thereafter, a reconstructed system is derived via integral transformation to reveal the forming mechanism of the in the . Finally, an implementation circuit is designed for the reconstructed system, and Power SIMulation (PSIM) simulations are executed to confirm the validity of the numerical analysis.

Keywords： 超级多稳定性；初值切换调控；忆容振荡器；机理分析    

HTML PDF Collect

Current molecular biologic techniques for characterizing environmental microbial community

Dawen GAO, Yu TAO

Frontiers of Environmental Science & Engineering 2012, Volume 6, Issue 1,   Pages 82-97 doi: 10.1007/s11783-011-0306-6

Abstract: Microbes are vital to the earth because of their enormous numbers and instinct function maintaining the natural balance. Since the microbiology was applied in environmental science and engineering more than a century ago, researchers desire for more and more information concerning the microbial spatio-temporal variations in almost every fields from contaminated soil to wastewater treatment plant (WWTP). For the past 30 years, molecular biologic techniques explored for environmental microbial community (EMC) have spanned a broad range of approaches to facilitate the researches with the assistance of computer science: faster, more accurate and more sensitive. In this feature article, we outlined several current and emerging molecular biologic techniques applied in detection of EMC, and presented and assessed in detail the application of three promising tools.

Keywords： molecular biological technique     microbial community     denaturing gradient gel electrophoresis (DGGE)     terminal    

HTML PDF Collect

Extreme weather/climate events and disaster prevention and mitigation under global warming background

Zhai Panmao,Liu Jing

Strategic Study of CAE 2012, Volume 14, Issue 9,   Pages 55-63

Abstract:

The definitions of extreme weather/climate events and "climate extremeOn the basis of classifying the extreme events into four categories (namely extremes caused by variationssingle variable, events related to weather phenomena,compound events and climate extremes), the related extremeMeanwhile, it is also necessary to strengthen engineering defense measures based on changes in extreme

Keywords： extreme climate indices     high impacts     meteorological disasters     engineering    

HTML PDF Collect

Title Author Date Type Operation

strength prediction and optimization design of sustainable concrete based on squirrel search algorithm-extremegradient boosting technique

Journal Article

Application of extreme gradient boosting in predicting the viscoelastic characteristics of graphene oxide

Journal Article

A comprehensive comparison of different regression techniques and nature-inspired optimization algorithms to predict carbonation depth of recycled aggregate concrete

Journal Article

Gradient boosting dendritic network for ultra-short-term PV power prediction

Journal Article

Machine learning enabled prediction and process optimization of VFA production from riboflavin-mediated sludge fermentation

Journal Article

An efficient improved Gradient Boosting for strain prediction in Near-Surface Mounted fiber-reinforced

Journal Article

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

Thuy-Anh NGUYEN; Hai-Bang LY; Van Quan TRAN

Journal Article

Application of machine learning technique for predicting and evaluating chloride ingress in concrete

Van Quan TRAN; Van Loi GIAP; Dinh Phien VU; Riya Catherine GEORGE; Lanh Si HO

Journal Article

Development of gradient boosting-assisted machine learning data-driven model for free chlorine residual

Journal Article

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

Van Quan TRAN; Hai-Van Thi MAI; Thuy-Anh NGUYEN; Hai-Bang LY

Journal Article

New technique of precision necking for long tubes with variable wall thickness

Yongqiang GUO, Chunguo XU, Jingtao HAN, Zhengyu WANG

Journal Article

SPT based determination of undrained shear strength: Regression models and machine learning

Walid Khalid MBARAK, Esma Nur CINICIOGLU, Ozer CINICIOGLU

Journal Article

Initial-condition-switched boosting extreme multistability and mechanism analysis in a memcapacitive

Bei Chen, Quan Xu, Mo Chen, Huagan Wu, Bocheng Bao,mervinbao@126.com

Journal Article

Current molecular biologic techniques for characterizing environmental microbial community

Dawen GAO, Yu TAO

Journal Article

Extreme weather/climate events and disaster prevention and mitigation under global warming background

Zhai Panmao,Liu Jing

Journal Article