A5045808844- Bayesian Methods and Mixture Models
- Advanced Clustering Algorithms Research
- Gene expression and cancer classification
- Statistical Methods and Bayesian Inference
- Advanced Statistical Methods and Models
- Statistical Methods and Inference
- Gaussian Processes and Bayesian Inference
- Neural Networks and Applications
- Data Management and Algorithms
- Sport and Mega-Event Impacts
- Bayesian Modeling and Causal Inference
- Target Tracking and Data Fusion in Sensor Networks
- Diverse Aspects of Tourism Research
- Simulation Techniques and Applications
- Guidance and Control Systems
- Time Series Analysis and Forecasting
- Spatial and Panel Data Analysis
- Fuzzy Logic and Control Systems
- Robotic Path Planning Algorithms
- Algorithms and Data Compression
- Metaheuristic Optimization Algorithms Research
- Mental Health Research Topics
- COVID-19 Pandemic Impacts
- COVID-19 epidemiological studies
- Ethics in Business and Education
University of Perugia
2015-2024
Finite mixture models are being used increasingly to model a wide variety of random phenomena for clustering, classification and density estimation. mclust is powerful popular package which allows modelling data as Gaussian finite with different covariance structures numbers components, purposes analysis. Recently, version 5 the has been made available on CRAN. This updated adds new structures, dimension reduction capabilities visualisation, selection criteria, initialisation strategies EM...
Genetic algorithms (GAs) are stochastic search inspired by the basic principles of biological evolution and natural selection. GAs simulate living organisms, where fittest individuals dominate over weaker ones, mimicking mechanisms evolution, such as selection, crossover mutation. have been successfully applied to solve optimization problems, both for continuous (whether differentiable or not) discrete functions. This paper describes R package <b>GA</b>, a collection general purpose...
Genetic algorithms are stochastic iterative in which a population of individuals evolve by emulating the process biological evolution and natural selection.The R package GA provides collection general purpose functions for optimisation using genetic algorithms.This paper describes some enhancements recently introduced version 3 package.In particular, hybrid GAs have been implemented including option to perform local searches during evolution.This allows combine power with speed...
Finite mixture modeling provides a framework for cluster analysis based on parsimonious Gaussian models. Variable or feature selection is of particular importance in situations where only subset the available variables provide clustering information. This enables more model, yielding efficient estimates, clearer interpretation and, often, improved partitions. paper describes R package clustvarsel which performs model-based clustering. An version Raftery and Dean (2006) methodology...
Genetic algorithms (GAs) are robust machine learning approaches for abbreviating a large set of variables into shorter subset that maximally captures the variance in original data. We employed GA-based method to shorten 62-item Multidimensional Experiential Avoidance Questionnaire (MEAQ) by half without much loss information. avoidance or tendency avoid negative internal experiences is key target many psychological interventions and its measurement an important issue psychology. The MEAQ has...
Genetic algorithms are stochastic iterative in which a population of individuals evolve by emulating the process biological evolution and natural selection. The R package GA provides collection general purpose functions for optimisation using genetic algorithms. This paper describes some enhancements recently introduced version 3 package. In particular, hybrid GAs have been implemented including option to perform local searches during evolution. allows combine power with speed optimiser....
In addition to positive externalities, hallmark events can generate negative social and environmental effects, giving rise significant sustainability issues. Thus, is often a necessary constraint containing damage. The aim of this article investigate the existence extent reciprocal influence between event sustainable transportation. On one hand, visitors using urban transportation enhance events' sustainability, while on other that urge attendees use public transit contribute economic green...