Tomasz Pełech-Pilichowski

Advances in Fuzzy Decision Making

This book shows how common operation management methods and algorithms can be extended to deal with vague or imprecise information in decision-making problems. It describes how to combine decision trees, clustering, multi-attribute decision-making algorithms and Monte Carlo Simulation with the mathematical description of imprecise or vague information, and how to visualize such information. Moreover, it discusses a broad spectrum of real-life management problems including forecasting the apparent consumption of steel products, planning and scheduling of production processes, project portfolio selection and economic-risk estimation. It is a concise, yet comprehensive, reference source for researchers in decision-making and decision-makers in business organizations alike.

Enhancements of Moving Trend Based Filters Aimed at Time Series Prediction

One of the techniques recommended for calculating the nonparametric trend (nonstationary, low-frequency time series component) is the moving trend based smoothing [10], [3], [4] typically based on linear Least Square (LS) approximates of the series in a moving window. Such algorithm splits input time series into three sections, starting, central, final ones. The procedures used in each section may be viewed as Moving Trend based Filters (MTF). In the paper MTFs properties in frequency domain are considered, from seasonal time series decomposition, smoothing and prediction efficiency perspectives. A number of MTFs enhancements is proposed, involving different approximating polynomials and final section signal corrections. In particular, a compression of the final section MTF output signal is proposed to reduce the filter delay, and then reconstruction of the missing signal by a special multiple LS approximation. It improves significantly the final section signal shape evaluation, which are essential for further prediction purposes.

Advances in Business ICT

Futurists and scientists alike profess the coming of a new era in the history the knowledge era. The notion of knowledge is as old as humans self-consciousness, but new challenges appear. The meaning of the word knowledge is changing from cognitive notion to a technical term denoting a structured economic resource to be actively managed. This contributed volume is a result of vivid and extremely valuable discussions held at 3rd International Workshop on Advances in Business ICT (ABICT) in Wrocaw, Poland, September 9-12, 2012. The workshop focused on Advances in Business ICT approached from a multidisciplinary perspective. It provided an international forum for scientists/experts from academia and industry to discuss and exchange current results, applications, new ideas of ongoing research and experience on all aspects of Business Intelligence. ABICT has also been an opportunity to demonstrate different ideas and tools for developing and supporting organizational creativity, as well as advances in decision support systems. This book is of interest to researchers, widely understood business, public sector and IT professionals.

A two-level algorithm of time series change detection based on a unique changes similarity method

In the paper, a novel two level algorithm of time series change detection is presented. In the first level, to identify non-stationary sequences in processed signals preliminary detection of events is performed with short-term prediction comparison. In the second stage, to confirm changes detected in first level a unique changes similarity method is employed. Detection of changes in non-stationary time series is discussed, implemented algorithms are described and results produced on exemplary four financial time series are showed.

Advances in ICT for Business, Industry and Public sector

Thats it, a book to wait for in this month. Even you have wanted for long time for releasing this book advances in ict for business industry and public sector; you may not be able to get in some stress. Should you go around and seek fro the book until you really get it? Are you sure? Are you that free? This condition will force you to always end up to get a book. But now, we are coming to give you excellent solution.

A two-level detector of short-term unique changes in time series based on a similarity method

In the paper, a novel two-level algorithm of time-series change detection is presented. In the first level, to identify non-stationary sequences in a processed signal, preliminary detection of events is performed with a short-term prediction comparison. In the second stage, to confirm the changes detected in the first level, a similarity method aimed at identification of unique changes is employed. The detection of changes in a non-stationary time series is discussed, implemented algorithms are described and the results produced on a sample four financial time series are shown. General conditions for implementing the proposed algorithm as an immune-like event detector are discussed.

Low-Frequency Signal Reconstruction and Abrupt Change Detection in Non-stationary Time Series by Enhanced Moving Trend Based Filters

An original approach to digital moving trend based filters (MTF) design, based on Bode plots analysis is proposed, aimed at seasonal time series decomposition and prediction [5]. A number of polynomials of different range are discussed to be used in the MTF as the LS approximation formula. The Bode plots of the MTF are shown, and the best filter is selected. Results of a seasonal time series decomposition and prediction with the best MTF is presented and compared to the classical MTF calculations (involving the linear LS approximation). The MTF enhancementsareintroduced aimed at better change detection. Efficiency of low-frequency periodic signals reconstruction and step-wise changes is illustrated.

On Problems of Automatic Legal Texts Processing and Information Acquiring from Normative Acts

In the paper, problems of legal information digitalization are investigat- ed. Conditions for extraction information from legal texts (i.a. normative acts) related to the common ones processing (non-legal terms, in English) are outlined. Problems of dimensionality reduction and application of similarity measures are discussed. Sample results of similarity analysis is presented. Further research aimed at semantic analysis of legal texts are outlined.

Remarks on visualization of fuzziness of cardiac data

In contemporary health science sophisticated apparatus delivers a lot of data on vital processes in patients. All of them are processed as a bulk of numbers not suitable directly for diagnosing or research purposes. Moreover, which is common in biomedical sciences, measured data are intrinsically inaccurate, i.e., fuzzy. In order to overcome these deficiencies a set of visualization methods has been developed as well as dedicated file formats. In the paper authors discuss selected formats and imaging techniques useful for cardiologists. Problems of medical data processing is outlined. Strengthens and weaknesses of raw STL file format are analyzed. Visualization styles of data fuzziness using experimental package ScPovPlot3D based on POVRay are proposed and discussed.

On a Property of Phase Correlation and Possibilities to Reduce the Walsh Function System

Data processing algorithms are used for business, industry and public sector to filter input data, calculate values, detect abrupt changes, acquire information from data or to ensure signal consistency. It is an important research area for Big Data processing and processing of data received from Internet of Things. Typically, classical algorithms are exploited, i.e. statistical procedures, data mining techniques and computational intelligence algorithms. Referring to the area of signal processing, applications of mathematical transformation (e.g. Fourier Transform, Walsh–Fourier Transform) of input signals from either domain to the other are promising. They enable to perform complementary analyses and to consider additional signal components, in particular cyclic (periodic) ones (sin- and cos-components). The Walsh function system is a multiplicative group of Rademacher and Gray functions. In its structure, it contains discrete-harmonic, sin-components of the Rademacher functions, and cos-components of the Gray function, as well as discrete-irregular components of the Walsh function. In the paper, the phase interdependence property has been defined, in pairs of a complete Walsh function system. Odd (sin-components) and even (cos-components) Walsh function subsystems were extracted as theoretical and numerical processing databases. A perspective concerning the processing efficiency and digital signal processing is outlined.