Considering the problem of diabetes prediction for the use case of PIMA Indian Data Set and Diabetes Dataset 2019, the present paper compares the efficiency of two automatic machine learning tools without code offered by Microsoft and Matlab: Automated ML from Azure Machine Learning Studio, and the Classification Learner Application from Matlab. Also, the results obtained for the best model obtained using the automatic machine tools without code, are compared with those obtained for an implementation with code, made on-premise.

The paper approaches the problem of modeling the microwave heating process using Neural Networks. The Neural Network was trained using Matlab and Comsol Multiphysics software. Numerical simulations were made in Comsol Multiphysics, obtaining the necessary input and output data to train the Neural Network. The training was made using Adaptive Neural Network tool from Matlab software.

In the present study a design of experiments method was used to obtain the most suitable responses. The variables that occur in the optimization are the movement of a dielectric material on Oy and Oz axis of a waveguide and the microwave power. The responses refer to the thermal field distribution, the reflected power, dielectric's temperature and the absorbed power.

The main objective of our research was to develop a model using the numerical simulation software - Comsol Multiphysics for the drying process of wheat seeds. A number of simulations were made in order to analyze the increase of temperature calculated in the dielectric material, the electric field intensity and total absorbed power.

The present paper describes the optimization process of heating a dielectric material, inside a microwave applicator, using design of experiments. Based on the results achieved through optimization, experimental data were done using a microwave installation. The dielectric material used within the optimization process and experimental data is Fir wood, with initial humidity of 62%.

The paper presents the optimization of the dielectric position inside a microwave installation created for processing dielectric materials - seeds/granular products - using design of experiments (DOE) with the main purpose of making the power transfer towards the dielectric more effective. Running simulations for various input data with the commercial Comsol Multiphysics software and using the experimental methods available in the statistical and data analysis software Minitab, we intend to obtain the optimal position of the dielectric inside the applicator for certain specified conditions.

The position of a dielectric material inside the applicator of a microwave installation is analyzed and optimized using the Box Behnken type of experiment; this type of experiment can be found inside the optimization software known as “Minitab”. An experiment having three factors and three levels was carried out. ANOVA - Analysis of Variance was used to study the influence that the factors have on responses. The objective of optimization was to process corn seeds in microwave field for obtaining a humidity that is well-suited for good storage; another objective was to meet the quality requirements for the treated material. The numerical modeling software called Comsol Multiphysics was used for studying the influence that the factors have on the optimization response.

The aim of the present study was the optimization of the factors that interfere in the heating process of a dielectric material inside a microwave applicator. Because in the process of optimization choosing the factors and responses is very important, in order to make the best decision when establishing the input data, Analysis of Variance was used. The article includes design of experiments using Design Expertsoftware and numerical modeling made with Comsol Multiphysics software.

The paper presents a design of experiments technique for the optimization of a waveguide position. General full factorial design with 2 factors and 3 levels was used during the process of optimization, results of the numerical simulations made with ComsolMultiphysics being the input data for the experimental design. The results obtained revealed a uniform distribution of the thermal and electrical field, in conditions of imposed temperature values.