An evolutionary fuzzy modelling approach and comparison of different methods for shear strength prediction of high-strength concrete beams without stirrups

Mohammadhassani, Mohammad; Nezamabadi‐pour, Hossein; Suhatril, Meldi; Shariati, Mahdi

doi:10.12989/sss.2014.14.5.785

Cited by 143 publications

(26 citation statements)

References 21 publications

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“…FIS is based on expertise expressed in terms of "IF-THEN" rules and can thus be employed to predict the behavior of many uncertain systems like shear strength prediction of high-strength concrete beams, 18,19 wind turbine and wind farms efficiency. [19][20][21] FIS advantage is that it does not require knowledge of the underlying physical process as a precondition for its application. Thus ANFIS integrates the fuzzy inference system with a back-propagation learning algorithm of neural network.…”

Section: Anfis Methodologymentioning

confidence: 99%

Retracted: Estimation of important variables for strength of concrete with high performance based on neuro fuzzy logic approach

2019

Structural Concrete

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Concrete is the most important material in civil engineering. Development of concrete strength could be determined by ratio of water and cement. However recent studies suggested that the concrete strength is influences also by other ingredients. Concrete with high performances is very complex material therefore the analyzing of the materials could be rather difficult and challenging task. The concrete compressive strength is a highly nonlinear function of age and ingredients. These ingredients include cement, blast furnace slag, fly ash, water, superplasticizer, coarse aggregate, and fine aggregate. In order to decrease the complexity the main goal of the study was to determine which variable are important and which variable are not important for the concrete strength analyzing. As the output variable compressive strength of the concrete with high performance was used. Since the concrete compressive strength is a highly nonlinear function in this article computational intelligence was used. Results suggested that the age has the highest impact on the compressive strength of the concrete with high performance.

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Section: Anfis Methodologymentioning

confidence: 99%

Retracted: Estimation of important variables for strength of concrete with high performance based on neuro fuzzy logic approach

2019

Structural Concrete

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“…Machine learning is a bionics-based problem solution scheme which mimics the functionality of human brain [1][2][3][4][5][6][7][8][9][10][11][12][13]. It is usually constituted by a series of mathematic operations and transformations which are implemented by computer programs coupled with modern electronic computers.…”

Section: Introductionmentioning

confidence: 99%

Hybrid machine learning hydrological model for flood forecast purpose

Kan¹,

Liang²,

Yu³

et al. 2020

Open Geosciences

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Machine learning-based data-driven models have achieved great success since their invention. Nowadays, the artificial neural network (ANN)-based machine learning methods have made great progress than ever before, such as the deep learning and reinforcement learning, etc. In this study, we coupled the ANN with the K-nearest neighbor method to propose a novel hybrid machine learning (HML) hydrological model for flood forecast purpose. The advantage of the proposed model over traditional neural network models is that it can predict discharge continuously without accuracy loss owed to its specially designed model structure. In order to overcome the local minimum issue of the traditional neural network training, a genetic algorithm and Levenberg–Marquardt-based multi-objective training method was also proposed. Real-world applications of the HML hydrological model indicated its satisfactory performance and reliable stability, which enlightened the possibility of further applications of the HML hydrological model in flood forecast problems.

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“…A growing demand on the structure and infrastructure adapted to an ever-changing social landscape has mainly raised the novelty of engineering materials (Mohammadhassani et al 2013, 2014b, Mansouri et al 2016, Hosseinpour et al 2018, Nasrollahi et al 2018, Sadeghipour Chahnasir et al 2018, Shahnazar et al 2018, Toghroli et al 2018b, Zhao et al 2018a. It also bring solutions to guarantee the optimum exploitation of resources, and foster more sustainable use of assets (Gerami et al 2008, Gholhaki et al 2008, Haddad 2008, Kheyroddin et al 2008, Sharbatdar et al 2008, Andalib et al 2018, Paknahad et al 2018, therefore, majority of studies have been conducted to determine the preference for familiarity or preference for novelty of structures (Ardalan et al 2009, Mohammadhassani et al 2013, 2014a, b, Mola-Abasi et al 2013, Eslami et al 2014, Toghroli et al 2014, Shahabi et al 2016, Toghroli et al 2018a. Accordingly, few studies are on the cold-form beamto-column connections (Mohammadhassani et al 2012, Sohel et al 2012, Talaiekhozani et al 2014, Zhao et al 2014, El Kadi and Kiymaz 2015, Shah et al 2015, Bao et al 2016, Shah et al 2016a, b, c, Bertocci et al 2017, El Kadi et al 2017 Corresponding author, Ph.D., E-mail: BuiTienDieu@gmail.com 2017a,…”

Section: Introductionmentioning

confidence: 99%

Behavior of steel storage pallet racking connection - A review

Chen¹,

Shi²,

Shariati³

et al. 2019

Preprint

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Steel pallet racking industry has globally used from the industrial revolution and has deeply evolved from hot-rolled profile into cold-formed profile to raise the optimization in engineering field. Nowadays, some studies regarding cold-formed steel profile have been performed, but fewer studies in terms of cold-formed pallet racking specifically in connection due to the semi-rigid behavior by lug-hooked into the upright have been conducted. The objective of this study is to review the related literature on steel storage racking connection behavior.

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An evolutionary fuzzy modelling approach and comparison of different methods for shear strength prediction of high-strength concrete beams without stirrups

Cited by 143 publications

References 21 publications

Retracted: Estimation of important variables for strength of concrete with high performance based on neuro fuzzy logic approach

Retracted: Estimation of important variables for strength of concrete with high performance based on neuro fuzzy logic approach

Hybrid machine learning hydrological model for flood forecast purpose

Behavior of steel storage pallet racking connection - A review

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