The effect of canard’s optimum geometric design on wake control behind the car using Artificial Neural Network and Genetic Algorithm

Rostamzadeh‐Renani, Mohammad; Baghoolizadeh, Mohammadreza; Rostamzadeh‐Renani, Reza; Toghraie, Davood; Ahmadi, Basir

doi:10.1016/j.isatra.2022.05.038

Cited by 21 publications

(2 citation statements)

References 34 publications

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“…The objective function values for the solutions are the basis for making decisions about how to enhance the solutions. Researchers used evolutionary algorithms or other methods in several studies [ [34] , [35] , [36] , [37] ]. In this study, MOGOA, MALO, MOPSO, MOMFO, MOWOA and NSGA Ⅱ algorithms are used in the direction of coupling with GMDH ANN and optimization.…”

Section: Methodsmentioning

confidence: 99%

Using of artificial neural networks and different evolutionary algorithms to predict the viscosity and thermal conductivity of silica-alumina-MWCN/water nanofluid

Baghoolizadeh,

Jasim,

Sajadi

et al. 2024

Heliyon

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Section: Methodsmentioning

confidence: 99%

Using of artificial neural networks and different evolutionary algorithms to predict the viscosity and thermal conductivity of silica-alumina-MWCN/water nanofluid

Baghoolizadeh,

Jasim,

Sajadi

et al. 2024

Heliyon

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“…There are various regression algorithms that can make the connection between these inputs and outputs. Regression modeling is a proposed method for predicting specific behaviors learned from existing data and is applied in various fields of engineering 73,113‐115 …”

Section: Modeling Of Annual Electricity Consumption Functions and Ann...mentioning

confidence: 99%

Multi‐objective optimization of annual electricity consumption and annual electricity production of a residential building using photovoltaic shadings

Baghoolizadeh

Nadooshan

Dehkordi

et al. 2022

Intl J of Energy Research

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Summary Shading is one of the cases that has effectivity on the household energy consumption. Shadings can be used either in horizontal or vertical form adjacent to the building’s window in order to control the sunlight. In this paper, a multi‐objective optimization is conducted to simultaneously reduce the annual electricity consumption and augment the electricity production with the application of photovoltaic shadings installed over the building window. To initiate the multi‐objective optimization, four design variables based on the positioning and geometry of photovoltaic shading are selected and test samples are simulated through EnergyPlus software. The model is three‐floor building located in Tehran, Iran. Next, the Morris sensitivity analysis (MSA) is implemented to calculate the extent to which each design variable affects the objective functions. Afterwards, the relation between the design variables and objective functions is extracted through the regression modeling using GMDH type‐ANN and the equations extracted are then utilized as inputs for genetic algorithm to conduct a Pareto‐based optimization. The results demonstrate that the maximum sunlight reception is attributed to the PV shading in southern direction of the building and its optimal tilt angle is 19.6 considering an annual period. There are slight changes to the tilt angle while seasonal period is considered for the calculations. The results also show that the use of solar shadings can reduce electricity consumption by approximately 4 to 11, 1 to 4, and 10 to 22% for an annual period, winter and summer season, respectively. At the end, the numerical data for the city of Tehran is compared to the cities of Canberra and Macapa.

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Prediction of the thermal behavior of multi-walled carbon nanotubes-CuO-CeO2 (20-40-40)/water hybrid nanofluid using different types of regressors and evolutionary algorithms for designing the best artificial neural network modeling

Rostamzadeh-Renani,

Baghoolizadeh,

Mohammad Sajadi

et al. 2023

Alexandria Engineering Journal

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The effect of canard’s optimum geometric design on wake control behind the car using Artificial Neural Network and Genetic Algorithm

Cited by 21 publications

References 34 publications

Using of artificial neural networks and different evolutionary algorithms to predict the viscosity and thermal conductivity of silica-alumina-MWCN/water nanofluid

Using of artificial neural networks and different evolutionary algorithms to predict the viscosity and thermal conductivity of silica-alumina-MWCN/water nanofluid

Multi‐objective optimization of annual electricity consumption and annual electricity production of a residential building using photovoltaic shadings

Prediction of the thermal behavior of multi-walled carbon nanotubes-CuO-CeO2 (20-40-40)/water hybrid nanofluid using different types of regressors and evolutionary algorithms for designing the best artificial neural network modeling

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