Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
Data mining is a technology in data analysis with rising application in sports. Basketball is one of most popular sports. Due to its dynamics, a large number of events happen during a game. Basketball statisticians have task to note as many of these events as possible, in order to provide their analysis. In this paper, we used data from the First B basketball league for men in Serbia, for seasons...
It is very important to forecast the ice thickness of Transmission Line for the safe operation of transmission network. The author had introduced artificial neural network(ANN) to the prediction of the ice thickness of transmission line, and proposed a predictive model based on GA and BP addresses on the defects of BP network includes slow convergence and easiness of running to local minimum, and...
Gas filow-volume controlled by many factors, the trend is complex, the accurate mathematical model to predict, in view of this situation, the paper attempts to grey dynamic model based on artificial neural network, organic combination of intelligent analysis method, structural gray neural network combination forecast model, based on Visual Basic 6.0, meanwhile, corresponding calculation program is...
Based on the annual report data between 1995 and 2005 of all listed companies (LCs), the 25 initial financial indexes, widely used by experts and researchers aboard and at home, was deduced to 14 effective evaluation indicators using factor analysis and principal component analysis (PCA). The 14 evaluation indicators, covering five aspects for comprehensive evaluation of competitiveness of LC, retain...
Various attribute and relation information is used in social recommendation systems. However, previous approaches fail to use them in a unified way. In this paper, we propose a unified framework for social recommendation. Entities like users and items are described by their tags. We model each entity using topic models like Latent Dirichlet Allocation(LDA) and then connect these topic models to form...
With financial globalization, the rapid development of financial derivatives and the complexity of banks management, operational risk measurement and management in commercial bank management is becoming increasingly important. How to effectively predict, control and prevent operational risk in commercial banks have become an important issue. Using BP neural network model to predict the risk has its...
We consider here the task of multi-label classification for data organized in a multi-relational graph. We propose the IMMCA model - Iterative Multi-label Multi-Relational Classification Algorithm - a general algorithm for solving the inference and learning problems for this task. Inference is performed iteratively by propagating scores according to the multi-relational structure of the data. We detail...
Classification of network traffic is the essential step for many network researches. Machine learning based approach is one of the most important approaches in the field of network traffic classification. Many related algorithms have been issued by researchers while the whole process contains a series of steps except building the algorithm and few researchers perform description. In this paper, a...
A new adaptation method for local model networks with higher degree polynomials which are trained by the polynomial model tree (POLYMOT) algorithm is presented in this paper. Usually the local models are linearly parameterized and those parameters are typically adapted by a recursive least squares approach. For the utilization of higher degree polynomials a subset selection method, which is a part...
This paper describes dynamics analysis of a small training ship and a possibility of ship pitching stabilization by adjusting engine speed. First, statistical analysis through multi-variate auto regressive(MAR) model is carried out. After upgrading the navigational system of an actual small training ship, in order to identify the model of the ship, the real data collected by sea trials on the ship...
The paper aims to develop an efficient forecasting model using differential evolution (DE) based learning rule. The structure chosen is an adaptive linear combiner whose weights are trained using DE. The prediction performance of the resulting model is evaluated by feeding features of retail sales data for different months' ahead prediction. These results are compared with those obtained by GA based...
The aim of this paper is to describe an alternative analytical method in order to evaluate customer outage cost (COC) in Thailand. The information of electrical expense, outage frequency, outage duration, and process recovery time from industrial customers is gathered. They are used to be inputs of the proposed adaptive neuro fuzzy inference system (ANFIS). In the data training by neural network,...
The inherently hierarchical problem of evaluating the complexity of an image interpretation is of relevance in both computer science and cognitive psychology. In this paper a new method of rule generation for the hierarchical prioritized fuzzy system, HPFS, is proposed, which overcomes the problem of lack of interpretability of most of the traditional fuzzy systems in modelling image. A hierarchical...
This paper focuses on methods to discriminate a temporary fault from a permanent one, and accurately determine fault extinction time in an extra high voltage (EHV) transmission line in a bid to develop a self-adaptive automatic reclosing scheme. Consequently, improper reclosing of the line onto a fault is avoided. The fault identification prior to reclosing is based on optimized artificial neural...
Recently ensemble classification has attracted serious attention of machine learning community as a solution for improving classification accuracy. The effect of the strategies for generating the members, combining the predictions and the size of the ensemble on the accuracy of the ensemble are of utmost interest to the researchers. In this paper, we propose and empirically evaluate a novel method...
A simulation training platform aiming at the difficult problem of training is presented. Platform is built based on HLA and its framework is designed to hierarchical structure. Models of training equipment are created with software named GL Studio and Multigen Creator. Key technologies of modeling process are detailed. Equipment operations are layered and its rules are described with XML document...
The commercial banks risks come from all the uncertainty of the banking business, which have diffusibility and hidden features, if not timely controlled, will have a negative impact on the national economy. Therefore, it is necessary to design the corresponding index system according to the objectivity and relativity of the banking risks, and then control quantitatively the banks risk. Based on the...
Aimed at heart disease diagnose is an important issue and hybrid kernel functions have excellent learning ability and generalization performance, we propose SVM based on hybrid kernel function and apply the model to test the heart disease dataset. In this paper, K-type kernel function combine with linear kernel and polynomial kernel is firstly proposed, Linear combinations with different kernel functions...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.