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Compressive 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: compressive strength test, this study combines five novel metaheuristic algorithms with extreme gradient boostingThe results indicated that the squirrel search algorithm-extreme gradient boosting (SSA-XGB) yielded

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

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The influence of social media on stock volatility

Xianjiao WU, Xiaolin WANG, Shudong MA, Qiang YE

Frontiers of Engineering Management 2017, Volume 4, Issue 2,   Pages 201-211 doi: 10.15302/J-FEM-2017018

Abstract: explores the influence of social media on stock volatility and builds a feature model with an intelligence algorithm

Keywords： stock volatility     social data     sentiment analysis     boosting algorithm    

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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    

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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 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    

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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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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    

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Transparency: The Missing Link to Boosting AI Transformations in Chemical Engineering

Yue Yuan,Donovan Chaffart,Tao Wu,Jesse Zhu,

Engineering doi: 10.1016/j.eng.2023.11.024

Abstract: The issue of opacity within data-driven artificial intelligence (AI) algorithms has become an impediment to these algorithms’ extensive utilization, especially within sensitive domains concerning health, safety, and high profitability, such as chemical engineering (CE). In order to promote reliable AI utilization in CE, this review discusses the concept of transparency within AI utilizations, which is defined based on both explainable AI (XAI) concepts and key features from within the CE field. This review also highlights the requirements of reliable AI from the aspects of causality (i.e., the correlations between the predictions and inputs of an AI), explainability (i.e., the operational rationales of the workflows), and informativeness (i.e., the mechanistic insights of the investigating systems). Related techniques are evaluated together with state-of-the-art applications to highlight the significance of establishing reliable AI applications in CE. Furthermore, a comprehensive transparency analysis case study is provided as an example to enhance understanding. Overall, this work provides a thorough discussion of this subject matter in a way that—for the first time—is particularly geared toward chemical engineers in order to raise awareness of responsible AI utilization. With this vital missing link, AI is anticipated to serve as a novel and powerful tool that can tremendously aid chemical engineers in solving bottleneck challenges in CE.

Keywords： Transparency     Explainable AI     Reliability     Causality     Explainability     Informativeness     Hybrid modeling     Physics-informed    

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Periodically varied initial offset boosting behaviors in a memristive system with cosine memductance Regular Papers

Mo CHEN, Xue REN, Hua-gan WU, Quan XU, Bo-cheng BAO

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 12,   Pages 1706-1716 doi: 10.1631/FITEE.1900360

Abstract: Nonlinear and one-dimensional initial offset boosting behaviors, which are triggered by not only theof coexisting attractors with different positions and topological structures are revealed along the boosting

Keywords： Initial offset boosting     Memristive system     Memductance     Line equilibrium set    

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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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Floret-like Fe–N nanoparticle-embedded porous carbon superstructures from a Fe-covalent triazine polymer boosting

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 5,   Pages 525-535 doi: 10.1007/s11705-022-2232-5

Abstract: Fe–Nx nanoparticles-embedded porous carbons with a desirable superstructure have attracted immense attention as promising catalysts for electrochemical oxygen reduction reaction. Herein, we employed Fe-coordinated covalent triazine polymer for the fabrication of Fe–Nx nanoparticle-embedded porous carbon nanoflorets (Fe/N@CNFs) employing a hypersaline-confinement-conversion strategy. Presence of tailored N types within the covalent triazine polymer interwork in high proportions contributes to the generation of Fe/N coordination and subsequent Fe–Nx nanoparticles. Owing to the utilization of NaCl crystals, the resultant Fe/N@CNF-800 which was generated by pyrolysis at 800 °C showed nanoflower structure and large specific surface area, which remarkably suppressed the agglomeration of high catalytic active sites. As expect, the Fe/N@CNF-800 exhibited unexpected oxygen reduction reaction catalytic performance with an ultrahigh half-wave potential (0.89 V vs. reversible hydrogen electrode), a dominant 4e– transfer approach and great cycle stability (> 92% after 100000 s). As a demonstration, the Fe/N-PCNF-800-assembled zinc–air battery delivered a high open circuit voltage of 1.51 V, a maximum peak power density of 164 mW·cm–2, as well as eminent rate performance, surpassing those of commercial Pt/C. This contribution offers a valuable avenue to exploit efficient metal nanoparticles-based carbon catalysts towards energy-related electrocatalytic reactions and beyond.

Keywords： Fe–Nx nanoparticles     hypersaline-confinement conversion     floret-like carbon     covalent triazine polymers     oxygen reduction reaction    

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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: simple and multiple linear regression models, three machine learning algorithms, random forest, gradient boosting

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

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Boosting the direct conversion of NHHCO electrolyte to syngas on Ag/Zn zeolitic imidazolate framework

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 9,   Pages 1196-1207 doi: 10.1007/s11705-022-2289-1

Abstract: zeolitic imidazolate framework derived nitrogen carbon catalysts, which were used for the first time for boosting

Keywords： Ag catalyst     zeolitic imidazolate framework     CO2 electroreduction     ammonium bicarbonate electrolyte     syngas    

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Optimization and its realization of anneal-genetic algorithm

Wang Ying

Strategic Study of CAE 2008, Volume 10, Issue 7,   Pages 57-59

Abstract:

A method that uses annealing algorithm to improve the inefficient localsearch of genetic algorithm is proposed.The algorithm optimization is more rapidly in precision after annealing algorithm integration with thegenetic algorithm.By examples of cement ratio works, compared with results of the simple algorithm, it is effectively.

Keywords： genetic algorithm     simulated annealing algorithm     genetic algorithm improvement    

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Framework, model and algorithm for the global control of urban automated driving traffic

Frontiers of Engineering Management doi: 10.1007/s42524-023-0294-9

Abstract: vehicle global scheduling problem, for which a mathematical model is formulated and a modified A-star algorithmThe experimental findings reveal that (i) the algorithm consistently delivers high-quality solutions

Keywords： automated driving     urban traffic control     global scheduling mode     autonomous vehicle route planning     A-star algorithm    

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Title Author Date Type Operation

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

Journal Article

The influence of social media on stock volatility

Xianjiao WU, Xiaolin WANG, Shudong MA, Qiang YE

Journal Article

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

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 extreme gradient boosting in predicting the viscoelastic characteristics of graphene oxide

Journal Article

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

Journal Article

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

Journal Article

Transparency: The Missing Link to Boosting AI Transformations in Chemical Engineering

Yue Yuan,Donovan Chaffart,Tao Wu,Jesse Zhu,

Journal Article

Periodically varied initial offset boosting behaviors in a memristive system with cosine memductance

Mo CHEN, Xue REN, Hua-gan WU, Quan XU, Bo-cheng BAO

Journal Article

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

Journal Article

Floret-like Fe–N nanoparticle-embedded porous carbon superstructures from a Fe-covalent triazine polymer boosting

Journal Article

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

Walid Khalid MBARAK, Esma Nur CINICIOGLU, Ozer CINICIOGLU

Journal Article

Boosting the direct conversion of NHHCO electrolyte to syngas on Ag/Zn zeolitic imidazolate framework

Journal Article

Optimization and its realization of anneal-genetic algorithm

Wang Ying

Journal Article

Framework, model and algorithm for the global control of urban automated driving traffic

Journal Article