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Application of machine learning algorithms for the evaluation of seismic soil liquefaction potential

Mahmood AHMAD, Xiao-Wei TANG, Jiang-Nan QIU, Feezan AHMAD, Wen-Jing GU

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 2,   Pages 490-505 doi: 10.1007/s11709-020-0669-5

Abstract: This study investigates the performance of four machine learning (ML) algorithms to evaluate the earthquake-inducedbased on the cone penetration test field case history records using the Bayesian belief network (BBN) learningThe BBN structures that were developed by ML algorithms-K2, hill climbing (HC), tree augmented naive(TAN) Bayes, and Tabu search were adopted to perform parameter learning in Netica, thereby fixing theThe results of this study can provide theoretical support for researchers in selecting appropriate ML algorithms

Keywords： seismic soil liquefaction     Bayesian belief network     cone penetration test     parameter learning     structurallearning    

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Estimation of optimum design of structural systems via machine learning

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 6,   Pages 1441-1452 doi: 10.1007/s11709-021-0774-0

Abstract: Three different structural engineering designs were investigated to determine optimum design variables, and then to estimate design parameters and the main objective function of designs directly, speedily, and effectively. Two different optimization operations were carried out: One used the harmony search (HS) algorithm, combining different ranges of both HS parameters and iteration with population numbers. The other used an estimation application that was done via artificial neural networks (ANN) to find out the estimated values of parameters. To explore the estimation success of ANN models, different test cases were proposed for the three structural designs. Outcomes of the study suggest that ANN estimation for structures is an effective, successful, and speedy tool to forecast and determine the real optimum results for any design model.

Keywords： optimization     metaheuristic algorithms     harmony search     structural designs     machine learning     artificial    

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Analytical algorithms of compressive bending capacity of bolted circumferential joint in metro shield

Frontiers of Structural and Civil Engineering   Pages 901-914 doi: 10.1007/s11709-023-0915-8

Abstract: Simplified analytical algorithms for four stress stages are established to describe the bearing behaviorsUsing the proposed simplified analytical algorithms, a parametric investigation is conducted to discuss

Keywords： shield tunnel     segment joint     joint structural model     failure mechanism    

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Runoff Modeling in Ungauged Catchments Using Machine Learning Algorithm-Based Model Parameters Regionalization Article

Houfa Wu,Jianyun Zhang,Zhenxin Bao,Guoqing Wang,Wensheng Wang,Yanqing Yang,Jie Wang

Engineering 2023, Volume 28, Issue 9,   Pages 93-104 doi: 10.1016/j.eng.2021.12.014

Abstract: LR-based approach, the accuracy of the runoff modeling in ungauged catchments was improved by the machine learningalgorithms because of the outstanding capability to deal with nonlinear relationships.performances of different approaches were similar in humid regions, while the advantages of the machine learning

Keywords： Parameters estimation     Ungauged catchments     Regionalization scheme     Machine learning algorithms     Soil and    

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Crack detection of the cantilever beam using new triple hybrid algorithms based on Particle Swarm Optimization

Amin GHANNADIASL; Saeedeh GHAEMIFARD

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 9,   Pages 1127-1140 doi: 10.1007/s11709-022-0838-9

Abstract: This paper deals with the inverse analysis of the crack detection problems using triple hybrid algorithmspaper, this is applied to identify crack location and depth in a cantilever beam using the new hybrid algorithmsThe results show that among the proposed triple hybrid algorithms, the PSO-GA-FA and PSO-GWO-FA algorithms

Keywords： crack     cantilever beam     triple hybrid algorithms     Particle Swarm Optimization    

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Artificial intelligence algorithms for cyberspace security applications: a technological and status review Review

Jie CHEN, Dandan WU, Ruiyun XIE,chenjie1900@mail.nwpu.edu.cn,wudd@cetcsc.com

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 8,   Pages 1117-1142 doi: 10.1631/FITEE.2200314

Abstract: algorithms have become the core means to increase the chance of security and improve the network attack

Keywords： Artificial intelligence (AI)     Machine learning (ML)     Deep learning (DL)     Optimization algorithm     Hybrid    

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Multi-objective genetic algorithms based structural optimization and experimental investigation of the

Pengxing YI,Lijian DONG,Tielin SHI

Frontiers of Mechanical Engineering 2014, Volume 9, Issue 4,   Pages 354-367 doi: 10.1007/s11465-014-0319-5

Abstract: minimum mass of the studied part, is proposed by combining the response surface method and genetic algorithms

Keywords： planet carrier     multi-objective optimization     genetic algorithms     wind turbine gearbox     modal experiment    

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Development of surface reconstruction algorithms for optical interferometric measurement

Dongxu WU, Fengzhou FANG

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 1,   Pages 1-31 doi: 10.1007/s11465-020-0602-6

Abstract: Theoretical background and recent advances of fringe analysis algorithms, including coherence peak sensingtechniques in image stitching, on-machine measurement, intelligent sampling, parallel computing, and deep learning

Keywords： surface topography     measurement     optical interferometry     coherence envelope     phase-shifting algorithm    

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Survey of the Algorithms on Association Rule Mining

Bi Jianxin,Zhang Qishan

Strategic Study of CAE 2005, Volume 7, Issue 4,   Pages 88-94

Abstract:

In this paper the principle of the algorithms on association rule mining is introduced firstly, andresearches of the algorithms on association rule mining are summarized in turn according to variableAt the same time some typical algorithms are analyzed and compared.

Keywords： data mining     association rule     algorithms     survey    

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Evolutionary Algorithms for Multi-objective Optimization and Decision-Making Problems

Xie Tao Chen Huowang

Strategic Study of CAE 2002, Volume 4, Issue 2,   Pages 59-68

Abstract: The researches on multi-objective evolutionary algorithms (MOEA) focus mainly on the Pareto-based comparisonoptimization and decision-making techniques, analyzes both the Pareto-based and non-Pareto-based evolutionary algorithms

Keywords： evolutionary algorithms     multi-objective optimization and decision-making     Pareto optimal    

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TIE algorithm: a layer over clustering-based taxonomy generation for handling evolving data None

Rabia IRFAN, Sharifullah KHAN, Kashif RAJPOOT, Ali Mustafa QAMAR

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 6,   Pages 763-782 doi: 10.1631/FITEE.1700517

Abstract: Taxonomy is generated to effectively organize and access large volume of data. A taxonomy is a way of representing concepts that exist in data. It needs to continuously evolve to reflect changes in data. Existing automatic taxonomy generation techniques do not handle the evolution of data; therefore, the generated taxonomies do not truly represent the data. The evolution of data can be handled by either regenerating taxonomy from scratch, or allowing taxonomy to incrementally evolve whenever changes occur in the data. The former approach is not economical in terms of time and resources. A taxonomy incremental evolution (TIE) algorithm, as proposed, is a novel attempt to handle the data that evolve in time. It serves as a layer over an existing clustering-based taxonomy generation technique and allows an existing taxonomy to incrementally evolve. The algorithm was evaluated in research articles selected from the computing domain. It was found that the taxonomy using the algorithm that evolved with data needed considerably shorter time, and had better quality per unit time as compared to the taxonomy regenerated from scratch.

Keywords： Taxonomy     Clustering algorithms     Information science     Knowledge management     Machine learning    

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An efficient two-stage approach for structural damage detection using meta-heuristic algorithms and group

Hamed FATHNEJAT, Behrouz AHMADI-NEDUSHAN

Frontiers of Structural and Civil Engineering 2020, Volume 14, Issue 4,   Pages 907-929 doi: 10.1007/s11709-020-0628-1

Abstract: optimization algorithm; in this part of methodology, the performance of the three popular optimization algorithms

Keywords： two-stage method     modal strain energy     surrogate model     GMDH     optimization damage detection    

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Optimal design of double-layer barrel vaults using genetic and pattern search algorithms and optimized

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 3,   Pages 378-395 doi: 10.1007/s11709-022-0899-9

Abstract: This paper presents a combined method based on optimized neural networks and optimization algorithmsThe algorithms considered in this step are the arithmetic optimization algorithm (AOA) and genetic algorithmIn the first example, the performance of two algorithms, OANN + AOA + PS and OANN + GA + PS, is investigatedResults show that both the OANN + GA + PS and OANN + AOA + PS algorithms perform well in solving structural

Keywords： optimization     surrogate models     artificial neural network     SAP2000     genetic algorithm    

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A Data and Knowledge Collaboration Strategy for Decision-Making on the Amount of Aluminum Fluoride Addition Based on Augmented Fuzzy Cognitive Maps Article

Weichao Yue、 Weihua Gui、 Xiaofang Chen、 Zhaohui Zeng、 Yongfang Xie

Engineering 2019, Volume 5, Issue 6,   Pages 1060-1076 doi: 10.1016/j.eng.2019.10.005

Abstract: region based on the STA using the proposed strategy is faster than when using the differential Hebbian learning

Keywords： AlF 3 addition     Fuzzy cognitive maps     Learning algorithms     State transition algorithm     Fuzzy    

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Evacuation Reliability Calculation in Case of Building Fire Based on Genetic Algorithms

Wang Jinhui,Lu Shouxiang

Strategic Study of CAE 2006, Volume 8, Issue 3,   Pages 58-61

Abstract:

The risk of people under building fire is expressed by genetic algorithms (GAs) reliability index

Keywords： genetic algorithms     fire     evacuation     reliability    

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Title Author Date Type Operation

Application of machine learning algorithms for the evaluation of seismic soil liquefaction potential

Mahmood AHMAD, Xiao-Wei TANG, Jiang-Nan QIU, Feezan AHMAD, Wen-Jing GU

Journal Article

Estimation of optimum design of structural systems via machine learning

Journal Article

Analytical algorithms of compressive bending capacity of bolted circumferential joint in metro shield

Journal Article

Runoff Modeling in Ungauged Catchments Using Machine Learning Algorithm-Based Model Parameters Regionalization

Houfa Wu,Jianyun Zhang,Zhenxin Bao,Guoqing Wang,Wensheng Wang,Yanqing Yang,Jie Wang

Journal Article

Crack detection of the cantilever beam using new triple hybrid algorithms based on Particle Swarm Optimization

Amin GHANNADIASL; Saeedeh GHAEMIFARD

Journal Article

Artificial intelligence algorithms for cyberspace security applications: a technological and status review

Jie CHEN, Dandan WU, Ruiyun XIE,chenjie1900@mail.nwpu.edu.cn,wudd@cetcsc.com

Journal Article

Multi-objective genetic algorithms based structural optimization and experimental investigation of the

Pengxing YI,Lijian DONG,Tielin SHI

Journal Article

Development of surface reconstruction algorithms for optical interferometric measurement

Dongxu WU, Fengzhou FANG

Journal Article

Survey of the Algorithms on Association Rule Mining

Bi Jianxin,Zhang Qishan

Journal Article

Evolutionary Algorithms for Multi-objective Optimization and Decision-Making Problems

Xie Tao Chen Huowang

Journal Article

TIE algorithm: a layer over clustering-based taxonomy generation for handling evolving data

Rabia IRFAN, Sharifullah KHAN, Kashif RAJPOOT, Ali Mustafa QAMAR

Journal Article

An efficient two-stage approach for structural damage detection using meta-heuristic algorithms and group

Hamed FATHNEJAT, Behrouz AHMADI-NEDUSHAN

Journal Article

Optimal design of double-layer barrel vaults using genetic and pattern search algorithms and optimized

Journal Article

A Data and Knowledge Collaboration Strategy for Decision-Making on the Amount of Aluminum Fluoride Addition Based on Augmented Fuzzy Cognitive Maps

Weichao Yue、 Weihua Gui、 Xiaofang Chen、 Zhaohui Zeng、 Yongfang Xie

Journal Article

Evacuation Reliability Calculation in Case of Building Fire Based on Genetic Algorithms

Wang Jinhui,Lu Shouxiang

Journal Article