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

Frontiers of Structural and Civil Engineering   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    

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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    

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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    

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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.    

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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    

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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    

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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    

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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    

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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    

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Vibration analysis of nano-structure multilayered graphene sheets using modified strain gradient theory

Amir ALLAHBAKHSHI,Masih ALLAHBAKHSHI

Frontiers of Mechanical Engineering 2015, Volume 10, Issue 2,   Pages 187-197 doi: 10.1007/s11465-015-0339-9

Abstract:

In this paper, for the first time, the modified strain gradient theory is used as a new size-dependentAfter obtaining the governing equations based on modified strain gradient theory via principle of minimum

Keywords： graphene     van der Waals (vdW) force     modi- fied strain gradient elasticity theory     size effect parameter    

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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    

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Concrete corrosion in wastewater systems: Prediction and sensitivity analysis using advanced extreme

Mohammad ZOUNEMAT-KERMANI, Meysam ALIZAMIR, Zaher Mundher YASEEN, Reinhard HINKELMANN

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 2,   Pages 444-460 doi: 10.1007/s11709-021-0697-9

Abstract: The models include three different types of extreme learning machines, including the standard, onlinesequential, and kernel extreme learning machines, in addition to the artificial neural network, classificationthe second assessment was conducted based on the gamma test approach, which is a sensitivity analysis techniqueThe online sequential extreme learning machine model demonstrated superior performance over the other

Keywords： sewer systems     environmental engineering     data-driven methods     sensitivity analysis    

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Velocity gradient elasticity for nonlinear vibration of carbon nanotube resonators

Hamid M. SEDIGHI, Hassen M. OUAKAD

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 6,   Pages 1520-1530 doi: 10.1007/s11709-020-0672-x

Abstract: undertake two models to capture the nanostructure nonlocal size effects: the strain and the velocity gradientThe structural nonlinear behavior of the system assuming both strain and velocity gradient theories is

Keywords： velocity gradient elasticity theory     nanotube resonators     differential-quadrature method     nonlinear vibration    

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Photoreduction adjusted surface oxygen vacancy of BiMoO for boosting photocatalytic redox performance

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 12,   Pages 1937-1948 doi: 10.1007/s11705-023-2353-5

Abstract: In this study, Bi2MoO6 with adjustable rich oxygen vacancies was prepared by a novel and simple solvothermal-photoreduction method which might be suitable for a large-scale production. The experiment results show that Bi2MoO6 with rich oxygen vacancies is an excellent photocatalyst. The photocatalytic ability of BMO-10 is 0.3 and 3.5 times higher than that of the pristine Bi2MoO6 for Rhodamine B degradation and Cr(VI) reduction, respectively. The results display that the band energy of the samples with oxygen vacancies was narrowed and the light absorption was broadened. Meanwhile, the efficiency of photogenerated electron-holes was increased and the separation and transfer speed of photogenerated carriers were improved. Therefore, this work provides a convenient and efficient method to prepare potential adjustable oxygen vacancy based photocatalysts to eliminate the pollution of dyes and Cr(VI) in water.

Keywords： Bi2MoO6     oxygen vacancies     photoreduction     Cr(VI)     RhB    

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Gradient-based compressive image fusion

Yang CHEN,Zheng QIN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 3,   Pages 227-237 doi: 10.1631/FITEE.1400217

Abstract: We present a novel image fusion scheme based on gradient and scrambled block Hadamard ensemble (SBHE)In the fusion phase, the image gradient is calculated to reflect the abundance of its contour informationBy compositing the gradient of each image, gradient-based weights are obtained, with which compressiveSimulation results demonstrate that the gradient-based scheme has the best performance, in terms of bothFurthermore, the gradient-based fusion scheme proposed in this paper can be applied in different fusion

Keywords： Compressive sensing (CS)     Image fusion     Gradient-based image fusion     CS-based image fusion    

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Title Author Date Type Operation

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

Journal Article

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

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

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

Vibration analysis of nano-structure multilayered graphene sheets using modified strain gradient theory

Amir ALLAHBAKHSHI,Masih ALLAHBAKHSHI

Journal Article

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

Zhai Panmao,Liu Jing

Journal Article

Concrete corrosion in wastewater systems: Prediction and sensitivity analysis using advanced extreme

Mohammad ZOUNEMAT-KERMANI, Meysam ALIZAMIR, Zaher Mundher YASEEN, Reinhard HINKELMANN

Journal Article

Velocity gradient elasticity for nonlinear vibration of carbon nanotube resonators

Hamid M. SEDIGHI, Hassen M. OUAKAD

Journal Article

Photoreduction adjusted surface oxygen vacancy of BiMoO for boosting photocatalytic redox performance

Journal Article

Gradient-based compressive image fusion

Yang CHEN,Zheng QIN

Journal Article