Homogeneous graphene oxide production with the variance reduction techniques: Taguchi method with the principal component analysis

Korucu, Haluk; Şimşek, Barış; Guvenc, Ali Bilge; Küçük, Vedat Arda

doi:10.1016/j.vibspec.2019.102967

Cited by 20 publications

(2 citation statements)

References 60 publications

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“…This is because the PCs are generated from the orthogonal directions that have the maximum variance in the original dataset. The reduction in dimension assists greatly in visualization and interpretation of the original dataset [34][35][36]. The beneficial and alluring feature of the PCA is the reduction in dimension of a set of multidimensional data.…”

Section: Principal Component Analysismentioning

confidence: 99%

Statistical analysis and prediction of spatial resilient modulus of coarse-grained soils for pavement subbase and base layers using MLR, ANN and Ensemble techniques

Ikeagwuani

Nwonu

2022

Innov. Infrastruct. Solut.

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Prediction methods for the estimation of the resilient modulus( ) of unbound granular materials continues to be fraught with challenges associated with the in situ dependency of the existing methods, which makes them unreliable when considering the spatial variability of soil properties. Moreover, the artificial intelligence methods, which prove to be superior for prediction, indicate that more recent and hybrid machine learning methods are more apt. Consequently, a comparative analysis was executed in the present study using advanced statistical approaches and a simple routine method for the prediction of the of coarse-grained soils used as unbound granular materials in highway pavements. This study considered also the spatial variability of the routine soil properties based on the long-term pavement performance database. The result of the descriptive analysis conducted using principal component analysis revealed that the variation in is due to three principal factors, which include the effect of moisture on the fines content, effect of coarse particles on the compaction characteristics and the effect of the soil stress state. Subsequently, prediction of the using multiple linear regression was unreliable based on residual analysis and multi-collinearity problems. Thus, predictive modeling of was then executed using artificial neural network (ANN) and ensemble techniques (random forest and gradient boosting machine), which resulted in very high R 2 values above 0.9, considered apt for MEPD. The ANN model was found to provide a superior prediction performance than the ensemble techniques.

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Section: Principal Component Analysismentioning

confidence: 99%

Statistical analysis and prediction of spatial resilient modulus of coarse-grained soils for pavement subbase and base layers using MLR, ANN and Ensemble techniques

Ikeagwuani

Nwonu

2022

Innov. Infrastruct. Solut.

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“…Taguchi developed the experimental design method known as the Taguchi method, which is based on experimental design to improve quality. This method was created by combining partial factorial experimental design with concepts such as robust design and orthogonal arrays [10,11]. In Taguchi's experimental design, the factors affecting the product's performance are divided into controllable and uncontrollable factors.…”

Section: Introductionmentioning

confidence: 99%

Silica nanoparticle synthesis by experimental design for drug and gene delivery applications

ULTAV¹,

TONBUL²,

SAHIN³

et al. 2023

jrp

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Silica nanoparticles (SNPs) are one of the most researched drug/gene delivery platforms due to their easy and cheap production. Their toxicity depends on the nanoparticle characteristics like particle size or shape. It is well known that the smaller nanoparticles have a better cellular uptake potential. For this reason, in this study, we synthesized SNPs with a particle size of around 100 nm via an experimental design method that combines Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) with Taguchi design to optimize more than one response. After the optimization, average particle size, particle size distribution, zeta potential, and particle morphology of validated SNPs were analyzed. The cytotoxicity studies were performed on fibroblast cells (L929) for 48 and 72 hours. Results show that obtained nanoparticles were spherical-shaped with a size of around 100 nm and had good biocompatibility.

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Optimization of Graphene-Related Materials Synthesis: Influence of Controlling Critical Factors in Different Methods

Tolentino-Hernández,

Ruiz-Perez,

Caballero-Briones

2024

Advanced Structured Materials

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Homogeneous graphene oxide production with the variance reduction techniques: Taguchi method with the principal component analysis

Cited by 20 publications

References 60 publications

Statistical analysis and prediction of spatial resilient modulus of coarse-grained soils for pavement subbase and base layers using MLR, ANN and Ensemble techniques

Statistical analysis and prediction of spatial resilient modulus of coarse-grained soils for pavement subbase and base layers using MLR, ANN and Ensemble techniques

Silica nanoparticle synthesis by experimental design for drug and gene delivery applications

Optimization of Graphene-Related Materials Synthesis: Influence of Controlling Critical Factors in Different Methods

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