0000000000225964
AUTHOR
Danial Jahed Armaghani
Convolution-based ensemble learning algorithms to estimate the bond strength of the corroded reinforced concrete
Reinforced concrete bond strength deterioration is one of the most serious problems in the construction industry. It is one of the most common factors impacting structural deterioration and the major cause of premature decadence of reinforced concrete structures. Therefore, developing an accurate model with the lowest variance and high reliability for the bond strength of corroded reinforced concrete is very important. The current work evaluates the efficiency of convolution-based ensemble learning algorithms. To address these issues, convolution-based ensemble learning models are developed using a database collected from the previous experimental studies of relative bond strength for corro…
Novel fuzzy-based optimization approaches for the prediction of ultimate axial load of circular concrete-filled steel tubes
An accurate estimation of the axial compression capacity of the concrete-filled steel tubular (CFST) column is crucial for ensuring the safety of structures containing them and preventing related failures. In this article, two novel hybrid fuzzy systems (FS) were used to create a new framework for estimating the axial compression capacity of circular CCFST columns. In the hybrid models, differential evolution (DE) and firefly algorithm (FFA) techniques are employed in order to obtain the optimal membership functions of the base FS model. To train the models with the new hybrid techniques, i.e., FS-DE and FS-FFA, a substantial library of 410 experimental tests was compiled from openly availa…
Mapping and holistic design of natural hydraulic lime mortars
Supplementary data to this article can be found online at https://doi.org/10.1016/j.cemconres.2020.106167.
Genetic justification of severe COVID-19 using a rigorous algorithm
Recent studies suggest excessive complement activation in severe coronavirus disease-19 (COVID-19). The latter shares common characteristics with complement-mediated thrombotic microangiopathy (TMA). We hypothesized that genetic susceptibility would be evident in patients with severe COVID-19 (similar to TMA) and associated with disease severity. We analyzed genetic and clinical data from 97 patients hospitalized for COVID-19. Through targeted next-generation-sequencing we found an ADAMTS13 variant in 49 patients, along with two risk factor variants (C3, 21 patients; CFH,34 patients). 31 (32%) patients had a combination of these, which was independently associated with ICU hospitalization (…
A novel heuristic algorithm for the modeling and risk assessment of the COVID-19 pandemic phenomenon
This article belongs to the special issue: Soft computing techniques in materials science and engineering Summarization: The modeling and risk assessment of a pandemic phenomenon such as COVID-19 is an important and complicated issue in epidemiology, and such an attempt is of great interest for public health decision-making. To this end, in the present study, based on a recent heuristic algorithm proposed by the authors, the time evolution of COVID-19 is investigated for six different countries/states, namely New York, California, USA, Iran, Sweden and UK. The number of COVID-19-related deaths is used to develop the proposed heuristic model as it is believed that the predicted number of dai…
A Novel Heuristic Global Algorithm to Predict the COVID-19 Pandemic Trend
SummaryMathematical models are useful tools to predict the course of an epidemic. A heuristic global Gaussian-function-based algorithm for predicting the COVID-19 pandemic trend is proposed for estimating how the temporal evolution of the pandemic develops by predicting daily COVID-19 deaths, for up to 10 days, starting with the day the prediction is made. The validity of the proposed heuristic global algorithm was tested in the case of China (at different temporal stages of the pandemic). The algorithm was used to obtain predictions in six different locations: California, New York, Iran, Sweden, the United Kingdom, and the entire United States, and in all cases the prediction was confirmed…