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A comprehensive comparison of different regression techniques and nature-inspired optimization algorithms

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

Abstract: Three types of regression techniques and meta-heuristic algorithms were employed to provide more alternative

Keywords： recycled aggregate concrete     carbonation depth     nature-inspired optimization algorithms     extreme gradient    

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foamed concrete compressive strength prediction using adaptive neuro-fuzzy inference system optimized by nature-inspiredalgorithms

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 1,   Pages 61-79 doi: 10.1007/s11709-020-0684-6

Abstract: ., ANFIS–particle swarm optimization (PSO), ANFIS–ant colony, ANFIS–differential evolution (DE), and

Keywords： foamed concrete     adaptive neuro fuzzy inference system     nature-inspired algorithms     prediction of compressive    

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Engineering punching shear strength of flat slabs predicted by nature-inspired metaheuristic optimized

Frontiers of Structural and Civil Engineering 2024, Volume 18, Issue 4,   Pages 551-567 doi: 10.1007/s11709-024-1091-1

Abstract: Reinforced concrete (RC) flat slabs, a popular choice in construction due to their flexibility, are susceptible to sudden and brittle punching shear failure. Existing design methods often exhibit significant bias and variability. Accurate estimation of punching shear strength in RC flat slabs is crucial for effective concrete structure design and management. This study introduces a novel computation method, the jellyfish-least square support vector machine (JS-LSSVR) hybrid model, to predict punching shear strength. By combining machine learning (LSSVR) with jellyfish swarm (JS) intelligence, this hybrid model ensures precise and reliable predictions. The model’s development utilizes a real-world experimental data set. Comparison with seven established optimizers, including artificial bee colony (ABC), differential evolution (DE), genetic algorithm (GA), and others, as well as existing machine learning (ML)-based models and design codes, validates the superiority of the JS-LSSVR hybrid model. This innovative approach significantly enhances prediction accuracy, providing valuable support for civil engineers in estimating RC flat slab punching shear strength.

Keywords： punching shear strength     reinforced concrete flat slabs     machine learning     jellyfish search     support vector machine    

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Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 3,   Pages 665-681 doi: 10.1007/s11709-021-0713-0

Abstract: neuro-fuzzy inference system is hybridized with several evolutionary approaches, including the ant colony optimization, genetic algorithm, teaching-learning-based optimization, biogeographical-based optimization, and invasiveweed optimization for estimating the long contraction scour depth.Based on the achieved modeling results, adaptive neuro-fuzzy inference system–biogeographic based optimization

Keywords： long contraction scour     prediction     uncertainty     ANFIS model     meta-heuristic algorithm    

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Thermo-fluidic devices and materials inspired from mass and energy transport phenomena in biological

Jian XIAO , Jing LIU ,

Frontiers in Energy 2009, Volume 3, Issue 1,   Pages 47-59 doi: 10.1007/s11708-008-0068-4

Abstract: Mass and energy transport consists of one of the most significant physiological processes in nature,dedicated to presenting a relatively complete review of the typical devices and materials in clinical use inspired

Keywords： bionics     mass transport     energy transport     artificial devices and materials     biology system     nature phenomena    

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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: performance and reduce the weight of the planet carrier in wind turbine gearbox, a multi-objective optimizationminimum mass of the studied part, is proposed by combining the response surface method and genetic algorithmsAnd a multi-objective genetic algorithm (MOGA) is applied to determine the direction of optimization.

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

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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:

Multi-objective optimization (MOO) and decision-making (DM) has become an important research areaThe researches on multi-objective evolutionary algorithms (MOEA) focus mainly on the Pareto-based comparisonThis paper presents an introduction to the history and classification of multi-objective optimizationand 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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Recent advances in system reliability optimization driven by importance measures

Shubin SI, Jiangbin ZHAO, Zhiqiang CAI, Hongyan DUI

Frontiers of Engineering Management 2020, Volume 7, Issue 3,   Pages 335-358 doi: 10.1007/s42524-020-0112-6

Abstract: System reliability optimization problems have been widely discussed to maximize system reliability withThe rules for simple optimization problems are summarized to enhance system reliability by using rankingThe importance-based optimization algorithms for complex or large-scale systems are generalized to obtainFurthermore, a general framework driven by IM is developed to solve optimization problems.Finally, some challenges in system reliability optimization that need to be solved in the future are

Keywords： importance measure     system performance     reliability optimization     optimization rules     optimization algorithms    

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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 algorithmsbased on Particle Swarm Optimization (PSO); these hybrids are Particle Swarm Optimization-Genetic Algorithm-FireflyAlgorithm (PSO-GA-FA), Particle Swarm Optimization-Grey Wolf Optimization-Firefly Algorithm (PSO-GWO-FA), and Particle Swarm Optimization-Genetic Algorithm-Grey Wolf Optimization (PSO-GA-GWO).The 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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Comparative seismic design optimization of spatial steel dome structures through three recent metaheuristicalgorithms

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 1,   Pages 57-74 doi: 10.1007/s11709-021-0784-y

Abstract: In this paper, the seismic design optimization of spatial steel dome structures is achieved through threerecent metaheuristic algorithms that are water strider (WS), grey wolf (GW), and brain storm optimizationThe metaheuristic algorithms are encoded in MATLAB interacting with SAP2000 for gathering structuralThe optimum spatial steel dome designs achieved by proposed WS, GW, and BSO algorithms are compared withand a gradient descent-based hyperband optimization (HBO) algorithm.

Keywords： steel dome optimization     water strider algorithm     grey wolf algorithm     brain storm optimization algorithm     hyperband optimization algorithm    

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The nature of cancer

Frontiers of Medicine 2023, Volume 17, Issue 4,   Pages 796-803 doi: 10.1007/s11684-022-0975-5

Abstract: The nature of cancer
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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 algorithmsto solve structural optimization problems.The algorithms considered in this step are the arithmetic optimization algorithm (AOA) and genetic algorithmResults show that both the OANN + GA + PS and OANN + AOA + PS algorithms perform well in solving structuraloptimization problems and achieve the same optimal design.

Keywords： optimization     surrogate models     artificial neural network     SAP2000     genetic algorithm    

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Dolphin swarm algorithm Article

Tian-qi WU,Min YAO,Jian-hua YANG

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 8,   Pages 717-729 doi: 10.1631/FITEE.1500287

Abstract: By adopting the distributed problem-solving strategy, swarm intelligence algorithms have been successfullyAt present, there are many well-implemented algorithms, such as particle swarm optimization, geneticalgorithm, artificial bee colony algorithm, and ant colony optimization.These algorithms have already shown favorable performances.The convergence rates and benchmark function results of these four algorithms are compared to testify

Keywords： Swarm intelligence     Bio-inspired algorithm     Dolphin     Optimization    

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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: group method of data handling (GMDH) network as a surrogate model during damage extent estimation by optimizationalgorithm; in this part of methodology, the performance of the three popular optimization algorithmsincluding particle swarm optimization (PSO), bat algorithm (BA), and colliding bodies optimization (

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

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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: Two different optimization operations were carried out: One used the harmony search (HS) algorithm, combining

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

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Title Author Date Type Operation

A comprehensive comparison of different regression techniques and nature-inspired optimization algorithms

Journal Article

foamed concrete compressive strength prediction using adaptive neuro-fuzzy inference system optimized by nature-inspiredalgorithms

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

Journal Article

Engineering punching shear strength of flat slabs predicted by nature-inspired metaheuristic optimized

Journal Article

Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related

Journal Article

Thermo-fluidic devices and materials inspired from mass and energy transport phenomena in biological

Jian XIAO , Jing LIU ,

Journal Article

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

Pengxing YI,Lijian DONG,Tielin SHI

Journal Article

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

Xie Tao Chen Huowang

Journal Article

Recent advances in system reliability optimization driven by importance measures

Shubin SI, Jiangbin ZHAO, Zhiqiang CAI, Hongyan DUI

Journal Article

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

Amin GHANNADIASL; Saeedeh GHAEMIFARD

Journal Article

Comparative seismic design optimization of spatial steel dome structures through three recent metaheuristicalgorithms

Journal Article

The nature of cancer

Journal Article

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

Journal Article

Dolphin swarm algorithm

Tian-qi WU,Min YAO,Jian-hua YANG

Journal Article

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

Hamed FATHNEJAT, Behrouz AHMADI-NEDUSHAN

Journal Article

Estimation of optimum design of structural systems via machine learning

Journal Article