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Moncef L Nehdi on Muck Rack

Moncef L Nehdi

As seen in: MDPI, ACI Materials Journal, Concrete International
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Articles

Performance of Statistical and Intelligent Methods in Estimating Rock Compressive Strength

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By Xuesong Zhang, Moncef L Nehdi, Amin Iraji, Farag M. A
| MDPI
Abstract : This research was conducted to forecast the uniaxial compressive strength (UCS) of rocks via the random forest, artificial neural network, Gaussian process regression, support vector machine, K-nearest neighbor, adaptive neuro-fuzzy inference system, simple regression, and multiple linear regression approaches. For this purpose, geo-mechanical and petrographic characteristics of sedimentary rocks in southern Iran were measured.
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Optimization of Fly Ash—Slag One-Part Geopolymers with Improved Properties

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By Iman Faridmehr, Mohammad Sahraei, Moncef L Nehdi, Kiyanets A. Valerievich
| MDPI
5.4. Informational Models Predictive 5.4.1. Multiple Linear Regression Model (MLR) The following Equation (8) expresses the most appropriate coefficients for the MLR model for estimating the compressive strength of the studied geopolymer pastes. 28-day Compressive Strength = 1.12 * (fly ash) + 1.93 * (GGBS) + 8.02 * (Na2O content) − 76.03 * (water/binder ratio) − 0.38 * (curing temperature) − 99.23 (8) Concerning the above equation, the value of R2 was calculated as 0.61.
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Parameters Identification of Solar PV Using Hybrid Chaotic Northern Goshawk and Pattern Search

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By Habib Satria, Moncef L Nehdi, Monjee K. Almustafa, Rahmad B. Y
| MDPI
This is an early access version, the complete PDF, HTML, and XML versions will be available soon. Open AccessArticle by Habib Satria 1, Rahmad B. Y. Syah 1,*, Moncef L. Nehdi 2,*, Monjee K.
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