Search Results - (( developing learning circular algorithm ) OR ( java adaptation optimization algorithm ))

Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Machine learning‐based approach for bandwidth and frequency prediction of circular SIW antenna by Alam, Md Mahabub, Nurhafizah, Abu Talip Yusof, Ahmad Afif, Mohd Faudzi, Tomal, Md Raihanul Islam, Haque, Md Ershadul, Rahman, Md. Suaibur

“…A predictive ML framework was developed using six regression algorithms trained on significant geometrical parameters, such as ring slot radius, via diameter, and feedline width. …”
Get full text
Get full text
Get full text

Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
Get full text
Get full text
Get full text
Get full text

Integration of grey analysis with artificial neural network for classification of slope failure by Deris A.M., Solemon B., Omar R.C.

“…This study employs an "artificial neural network" (ANN) to predict the slope failures based on historical circular slope cases. Using the feed-forward back-propagation algorithm with a multilayer perceptron network, ANN is a powerful ML method capable of predicting the complex model of slope cases. …”

Image Classification for Age-related Macular Degeneration Screening Using Hierarchical Image Decompositions and Graph Mining by Mohd Hanafi Ahmad Hijazi, Chuntao Jiang, Frans Coenen, Yalin Zheng

Get full text
Get full text
Get full text
Get full text

A comparative study of supervised machine learning approaches for slope failure production by Deris A.M., Solemon B., Omar R.C.

“…This study employs an "artificial neural network" (ANN) to predict the slope failures based on historical circular slope cases. Using the feed-forward back-propagation algorithm with a multilayer perceptron network, ANN is a powerful ML method capable of predicting the complex model of slope cases. …”

Effect of particle size on second law of thermodynamics analysis of Al2O3 nanofluid: Application of XGBoost and gradient boosting regression for prognostic analysis by Kumar K P., Alruqi M., Hanafi H.A., Sharma P., Wanatasanappan V.V.

“…Prognostic models were developed using two sophisticated machine learning algorithms, XGBoost and Gradient Boosting Regression (GBR). …”