Now showing 1 - 4 of 4
  • Publication
    DATA PREPROCESSING METHODS FOR INTERVAL BASED NEURAL NETWORK PREDICTION
    The paper examines a task of forecasting stock prices of Riga Stock exchange by the use of interval value prediction approach, which is carried out by modified Kohonen neural network learning algorithm. The data preprocessing methods are analyzed and implemented here to solve stock prices prediction task. The proposed data preprocessing methods has been experimentally tested with two types of artificial neural networks.
  • Publication
    APPROACHES AND SOLUTIONS FOR SIGN LANGUAGE RECOGNITION PROBLEM
    The goal of the paper is reviewing several aspects of Sign Language Recognition problems focusing on Artificial Neural Network approach. The lack of automated Latvian Sign Language has identified and proposals of how to develop such a system have made. Tha authors use analytical, statistical methods as well as practical experiments with neural network software. The main results of the paper are description of main Sign Language Recognition problem solving methods with Artificial Neural Networks and directions of future work based on authors’ previous expertise.
  • Publication
    LATVIAN SIGN LANGUAGE RECOGNITION CLASSIFICATION POSSIBILITIES
    There is a lack of automated sign language recognition system in Latvia while many other countries have been already equipped with such a system. Latvian deaf society requires support of such a system which would allow people with special needs to enhance their communication in governmental and public places. The aim of this paper is to recognize Latvian sign language alphabet using classification approach with artificial neural networks, which is a first step in developing integral system of Latvian Sign Language recognition. Communication in our daily life is generally vocal, but body language has its own significance. It has many areas of application like sign languages are used for various purposes and in case of people who are deaf and dumb, sign language plays an important role. Gestures are the very first form of communication. The paper presents Sign Language Recognition possibilities with centre of gravity method. So this area influenced us very much to carry on the further work related to hand gesture classification and sign’s clustering.
  • Publication
    RETAIL TURNOVER PREDICTION USING MODULAR ARTIFICIAL NEURAL NETWORKS
    The paper focuses on the retail turnover prediction with artificial neural networks. The artificial neural networks have the potential to learn complex, non-linear relationships within data. The main disadvantage is that neural networks are “black boxes”, so the user cannot explain the obtained results and relationships between data. The modular neural networks allow obtaining more appropriate results by splitting the task into subtasks, thus giving the user more information in the output. In many cases an additional advantage of modular neural network is more precise prediction results, which will be shown in the experimental part of this paper.
    Scopus© Citations 1