Against the background of global urban knowledge economy, this paper discusses some of the challenges that sustainable urban life is facing in the global knowledge economy of the 21st century. The paper makes an overview of the fundamental change in urban-rural relations, urban and rural...

UK, along with many other developed countries, is now considered to be primarily a knowledge economy. According to this model, future prosperity will depend on the development of knowledge-intensive, high value-added economic activities, and on a highly skilled workforce. At the same time, the...

Global economic crisis has shown that only countries with high rate of innovation can preserve high levels of economic growth in an unsta- ble environment. Furthermore, it has been proven that nation's and the world's future economic growth will stem from industries that rely on knowledge, new...

The labour content, its structures and the finality of the social action were always in a permanent relation with the historical type of society and with the manner of producing goods and services. The humanity passing to the global economy, to a new manner of economic growth places in front of...

We study model selection strategies based on penalized empirical loss minimization. We point out a tight relationship between error estimation and data-based complexity penalization: any good error estimate may be converted into a data-based penalty function and the performance of the estimate...

Purpose – The purpose of this paper is to perform a comparative study of prediction performances of an artificial neutral network (ANN) model against a linear prediction model like a linear discriminant analysis (LDA) with regards to forecasting corporate credit ratings from financial...

Tech Report

The huge popularity of Hidden Markov models in pattern recognition is due to the ability to 'learn' model parameters from an observation sequence through Baum-Welch and other re-estimation procedures. In the case of HMM parameter estimation from an ensemble of observation sequences, rather than...

This thesis is based on research on financial time series analysis using pattern recognition methods. The first part of this research focuses on univariate time series analysis using different pattern recognition methods. First, probabilities of basic patterns are used to represent the features...

Cycle-theory-based market analysis is the main focus of this thesis, in which I try to find systematic methods to recognize and utilize market patterns, especially cyclic ones, to obtain a correct understanding of market movements. The KNN algorithm, a pattern recognition method extensively used...