ABSTRACT - Traditional statistical models as tools for summarizing patterns and regularities in observed data can be used for making predictions. However, statistical prediction models contain small number of important predictors, which means limited informative capability. Also, predictive statistical models that provide some type of pseudo-correct regular statistical patterns, are used without previous understanding of the used data causality. Machine Learning (ML) algorithms as area in Artificial Intelligence (AI) provide the ability to interpret and understand data in more sophisticated way. Artificial Neural Networks as kind of ML methods use non-linear algorithms, considering links and associations between parameters, while statistica...
This book gathers the most current research from across the globe in the study of artificial neural ...
Machine Learning has become 'commodity' in engineering and experimental sciences, as calculus and st...
Two articles, Edelsbrunner and, Schneider (2013), and Nokelainen and Silander (2014) comment on Muss...
Title: Methods of artificial intelligence and their use in prediction Author: Lubomír Šerý Departmen...
Intelligent modeling techniques have evolved from the application field, where prior knowledge and c...
Neural networks are being used in areas of prediction and classification, the areas where statistica...
The field of neural networks is a wide and diverse field which spans a variety of interests, modelli...
The analysis of a time series is a problem well known to statisticians. Neural networks form the bas...
In this paper, Artificial Neural Networks (ANN) and Regression Analysis models were considered to de...
We present an overview of current research on artificial neural networks, emphasizing a statistica...
In this paper, Artificial Neural Networks (ANN) and Regression Analysis models were considered to de...
Artificial Neural Networks (ANN) approach is an alternate way to classical methods. As a computation...
Machine learning is a branch of artificial intelligence in which the system is made to learn from da...
Introduction: Artificial neural networks mimic brains behavior. They are able to predict and feature...
summary:Artificial neural networks (ANN) have received a great deal of attention in many fields of e...
This book gathers the most current research from across the globe in the study of artificial neural ...
Machine Learning has become 'commodity' in engineering and experimental sciences, as calculus and st...
Two articles, Edelsbrunner and, Schneider (2013), and Nokelainen and Silander (2014) comment on Muss...
Title: Methods of artificial intelligence and their use in prediction Author: Lubomír Šerý Departmen...
Intelligent modeling techniques have evolved from the application field, where prior knowledge and c...
Neural networks are being used in areas of prediction and classification, the areas where statistica...
The field of neural networks is a wide and diverse field which spans a variety of interests, modelli...
The analysis of a time series is a problem well known to statisticians. Neural networks form the bas...
In this paper, Artificial Neural Networks (ANN) and Regression Analysis models were considered to de...
We present an overview of current research on artificial neural networks, emphasizing a statistica...
In this paper, Artificial Neural Networks (ANN) and Regression Analysis models were considered to de...
Artificial Neural Networks (ANN) approach is an alternate way to classical methods. As a computation...
Machine learning is a branch of artificial intelligence in which the system is made to learn from da...
Introduction: Artificial neural networks mimic brains behavior. They are able to predict and feature...
summary:Artificial neural networks (ANN) have received a great deal of attention in many fields of e...
This book gathers the most current research from across the globe in the study of artificial neural ...
Machine Learning has become 'commodity' in engineering and experimental sciences, as calculus and st...
Two articles, Edelsbrunner and, Schneider (2013), and Nokelainen and Silander (2014) comment on Muss...