Author:Gergő Pintér

Publications
EasyChair Preprint no. 3310
EasyChair Preprint no. 3057
EasyChair Preprint no. 2994
EasyChair Preprint no. 2781
EasyChair Preprint no. 1824
EasyChair Preprint no. 394

Keyphrases

AHP, analysis, Analytic Hierarchy Process, Analytical Network Process, ANN model, ann pso model, ANN-PSO, Artificial Neural Network, Artificial Neural Networks (ANN), breast cancer, breast cancer dataset, Breast Cancer Detection, cancer mass, combine harvester, comparative analysis, Confusion Matrix, Coronavirus, COVID-19, cross validation technique, Data Mining, Data Mining Technique, developed country, electrical engineering obuda university, ELM model, elm rbf model, epithelial cell size, evaluation criterion, expert system, Extreme Learning Machine, Extreme Learning Machine (ELM), Fan speed, first module, fold cross, Fuzzy Linguistic Variable, fuzzy rule, fuzzy system, Health, hidden layer, hybrid machine learning2, int agric eng, Large Social Event, linguistic variable, machine learning3, machine learning method, Malignant breast cancer, mobility patterns, model number, multilayer fuzzy expert system, negative rate, neural network2, Particle Swarm Optimization, Particle Swarm Optimization (PSO), performance analysis, Physical activities, prediction model, public health, public space, Radial Basis Function, Radial Basis Function (RBF), rmse r2 mape model, SARS-CoV-2, Smart Cities, Support Vector Machine, Support Vector Machine (SVM), Sustainability2, Sustainable banking, Sustainable business model, swarm size, target value, urban health, urban morphology, urban planning, Urbanization, Wisconsin Dataset.