Wyniki wyszukiwania - Biblioteka Nauki

1

Forecast for the Development of the International Freight Transport Market in Poland Until 2030

100%

Dorosiewicz S. , Waśkiewicz J.

Logistics and Transport

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2018

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tom Vol. 40, No. 4

103--110

EN

This paper includes the forecasts of the volume of transport performance (in tonne-kilometres) of Polish international truck transport up to 2030.

2

Prognozowanie przychodów całkowitych w JIT na rok 2020

80%

Kozicki B. , Ćwiekowski Ł. , Koszarek A.

Systemy Logistyczne Wojsk

|

2020

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tom Vol. 52, no. 1

59--78

PL

W artykule został sformułowany problem badawczy dotyczący analizy, oceny i prognozowania przychodów całkowitych przedsiębiorstw JIT (Logistic Just in Time) w ujęciu miesięcznym na rok 2020. Przeprowadzono analizę literatury przedmiotu badań dotyczącą przychodów oraz prognozowania. Badania rozpoczęto od nakreślenia wykresu liniowego danych pierwotnych. Oceną obserwacji wzrokowej było zaobserwowanie tendencji w postaci trendu i sezonowości. Użytymi w artykule narzędziami badawczymi potwierdzono istnienie prawidłowości w rozpatrywanych danych retrospektywnych. Krytyczna analiza literatura dotycząca prognozowania, pozwoliła na wybór metody wygładzania wykładniczego Holta-Wintersa do prognozowania danych pierwotnych na przyszłość. Uzyskane prognozy zostały poddane analizie i ocenie.

EN

The article presents a research problem concerning the analysis, evaluation and forecasting of total revenues of JIT (Logistic Just in Time) enterprises in monthly terms for 2020. An analysis of the literature on the subject of revenues and forecasting was conducted. The study began with creating a line graph of primary data. Regularities in the form of trends and seasonality were the evaluation of visual observation. The research tools used in the article confirmed the existence of regularities in the retrospective data under consideration. Critical analysis of the literature related to forecasting has enabled the selection of the Holt-Winter’s exponential smoothing method for the forecasting of primary data for the future. The obtained forecasts were analyzed and evaluated.

3

Consideration in diagnostics of the grey system theory

80%

Żółtowski B.

Journal of Polish CIMAC

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2011

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tom Vol. 6, no 2

191-200

EN

The publication describes Grey System Theory (GST) and takes into account the Grey differential model (GM) and Grey Generating Space (GS). Grey System Theory shows to which extent the vibration signals (deriving from tested objects) influence the evaluation and analysis of condition of the machine. The above-mentioned theory applies under the existence of fix, non-negative and monotonic data correlated with insufficient and uncertain data’ sources. In relation to these circumstances, the Forecasting (rolling window) method seems to be appropriate solution, which remains the main subject of this paper. The present research use vibration methods to recognize the technical state of the machines and SVD method (Singular Value Decomposition) as well as GST (Grey System Theory) was used for results validation.

4

Predictive modeling and analysis of changes migrations in Poland

80%

Nawrocka M.

World Scientific News

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2017

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tom 72

329-343

EN

The development of the research in economy has shown that conducting mathematical modeling and statistics is an effective instrument for diagnosing the progress phenomenon of socio-economic. It provides the information about the dynamics of result changeability in different periods of time. Additionally statistical analysis allows determining the prediction for periods of future and past years. Migrations is characterized by the quality of being measurable because it includes quantitative data. In recent years, demonstrate high dynamics. Conducting the analyses and calculations based on methods and statistical instruments will result in the opportunity to compare, group, analysis variables, specify trends and designate the diagnoses of achieved sports results with the implementation of the optimum vector of variables of independent variable of migrations. An analysis of the dynamics migration variability was carried out on the basis of data from the website of the main statistical office, in this article. Used the statistical methods and the testing of interdependencies. Additionally, the models of time series have been used for the sake of the analysis. The most significant aim of the analysis of the dynamics is the designation of predictions. The use of the model of time series has the task of the specification of the change of the phenomenon level in time.

5

Forecasting on the long-term sustainability of the employees provident fund in Malaysia via the Box-Jenkins’ ARIMA model

80%

Hassan S. , Othman Z.

Business and Economic Horizons

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2018

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tom Volume 14

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nr Issue 1

43-53

EN

This study employs the use of Box-Jenkins’ ARIMA (1,1,0) model for the estimation and forecasts based on the annual data of EPF balances, which serve as a proxy to EPF sustainability, together with the yearly data of possible determinants namely investment earnings, nominal income, elderly population, life expectancy and mortality rate in Malaysia for the 1960 – 2010 and 2010 - 2014 periods, respectively. Amid a negative sentiment and conceivably bleak outlook on the long term EPF inadequacy to provide adequate incomes to elderly persons, the prognosis of this study instead reveals otherwise and is found to be in support for the long term prospect and sustainability of the EPF. With necessary improvements are underway to strengthen the performance of the administered EPF system, it is likely to believe that the EPF organization is committed to promoting its product as a more inclusive and equitable scheme in Malaysia.

6

Prognozowanie szeregów czasowych ze składową periodyczną z wykorzystaniem pakietu TSprediction programu R

80%

Bartłomowicz T.

Econometrics. Ekonometria. Advances in Applied Data Analytics

|

2014

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nr 4(46)

199-210

EN

The main aim of the paper is to present selected features of TSprediction package developed for R environment, which now is one of the most important commercial computing platforms (offered under the GNU GPL license). The article presents the features of the TSprediction package enabling the prediction of time series where there is a periodic component in the form of seasonal fluctuations. The package includes an implementation of the most popular time series methods of forecasting with a periodic component in the additive and multiplicative variety of ratio and Winters and Klein methods. The effects of selected forecasting functions and ex-post forecasting errors of TSprediction R package are presented in the examples.

7

Analysis and Modeling of Domain Registration Process

80%

Arabas P. , Jaskóła P. , Kamola M. , Karpowicz M.

Journal of Telecommunications and Information Technology

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2012

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tom nr 2

63-73

EN

The paper presents analysis of the domain name reservation process for the polish .pl domain. Two models of various time scale are constructed and finally combined to build long range high resolution model. The results of prediction are verified using real data.

8

Solutions for estimating the range of delay in time – area analogy method

80%

Gondek A.

Management

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2010

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tom Vol. 14, no 2

161-170

EN

This article presents the difficulties which a forecaster has when very high results of the measure of similarity are achieved in time – area analogy method, but in fact it is very difficult to choose the best range of delay in time between similar objects. The author shows this decision problem and possibility of solving it based on the example of the research about GDP per capita in Poland and any UE countries. Moreover, the time – area analogy method was described in details.

PL

Artykuł prezentuje trudności, na jakie napotyka prognosta w sytuacji, gdy osiąga wysokie miary podobieństwa podczas stosowania metody analogii przestrzenno – czasowych, a w rzeczywistości rodzi to problemy z określeniem rzędu przesunięcia w czasie przedziałów podobieństwa między obiektami. Autorka ukazuje problem decyzyjny, jak i podaje możliwości jego rozwiązania na przykładzie badania analogii w kształtowaniu się PKB per capita w Polsce i pozostałych krajach unijnych. Ponadto, metoda analogii przestrzenno – czasowych została szczegółowo opisana.

9

Zastosowanie modelu ARIMA do prognozy importu towarów do Polski na 2019 rok

80%

Kozicki B.

Systemy Logistyczne Wojsk

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2019

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tom Vol. 50, no. 1

127--141

PL

W artykule poruszony został problem z zakresu analizy i oceny danych dotyczących importu towarów do Polski w latach 2011-2018 w milionach ton oraz próba przeprowadzenia prognozowania eksportu w Polsce na czternaście przyszłych okresów modelem ARIMA. Badania rozpoczęto od analizy i oceny danych dotyczących importu towarów w milionach ton w Polsce w ujęciu dynamicznym. Następnie na podstawie uzyskanych ocen wybrano model prognostyczny ARIMA, a następnie zbudowano dwa modele uczące typu ARIMA. Zbudowane modele ARIMA zostały poddane analizie i ocenie. Wybrano najlepszy. Na jego podstawie wykonano prognozowanie szeregu pierwotnego. Uzyskane rezultaty badań przedstawiono w podsumowaniu.

EN

In the article the author raises the issue related to the analysis and evaluation of data concerning the importation of goods to Poland between 2011-2018 in millions of tons and the attempt to conduct the forecasting of exportation in Poland for fourteen future periods with the application of ARIMA model. The research was initiated with the analysis and evaluation of data concerning the importation of goods in millions of tons in Poland dynamically. Then, based on the evaluation obtained, the ARIMA prognostic model was applied, and, after that, two study models of ARIMA type were constructed. These ARIMA models were analyzed and evaluated. The best one was chosen. Based on it, the original time series was forecast. The results, which were gathered, were presented in the summary.

10

How do individual forecasters change their views? An analysis with micro panel data

80%

Paloviita M. , Viren M. , Bank of Finland , University of Turku

Acta Universitatis Lodziensis. Folia Oeconomica

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2013

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tom 295

EN

This paper scrutinizes the behavior of individual forecasters included in the Consensus Forecast inflation data for the US. More precisely, we try to determine whether individual forecasters deviate systematically from each other. We examine whether the ranking of forecasters is the same over time. The full micro data set includes 74 forecasters over the period 1989M10-2011M3. The results clearly indicate that the forecasters behave quite persistently so that, for instance, the ranking of forecasters does not change over time. Even so, we also find that the survey values imply reasonable values for the hybrid form of the New Keynesian Phillips curve and that forecaster’s disagreement is positively related to the size of forecast errors.

PL

Przeanalizowano zachowanie się poszczególnych ośrodków prognostycznych ujętych w prognozach Consensus Forecast dla inflacji w USA. Starano się określić, czy poszczególne prognozy systematycznie odbiegają od siebie. W szczególności zbadano, czy ranking ośrodków jest taki sam w czasie. Pełny zestaw danych obejmuje 74 prognostyków w okresie 1989M10– 2011M3. Wyniki wyraźnie wskazują, że prognostycy zachowują się bardzo konsekwentnie tak, że na przykład, ranking ośrodków nie zmienia się w czasie. Ponadto pokazano, że prognostycy są zgodni co do hybrydowej postaci neokeynesowskiej krzywej Phillipsa oraz że różnice pomiędzy nimi są dodatnio skorelowane z wielkością błędów prognozy.

11

Forecasting industrial production in Poland – a comparison of different methods

80%

Acedański J.

Econometrics. Ekonometria. Advances in Applied Data Analytics

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2013

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nr 1(39)

40-51

EN

In this paper we compared the accuracy of a few forecasting methods of the industrial production index in Poland. Naïve forecasts, simple autoregressive models, leading indicator models, factor models as well as joint models were included in the considerations. We used the out-of-sample RMSE and CPA tests as the main measures of the predictions accuracy. We found that three models provided the best predictions in most cases – the models with the PMI index and with the PMI and German IFO indexes as leading indicators as well as joint forecasts.

12

Prognozowanie przyjęć do pracy jako element budowy strategii personalnej

80%

Tomaszewski J.

Systemy Logistyczne Wojsk

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2018

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tom Vol. 49, no. 2

206--218

EN

The article presents an issue from the field of forecasting job recruitment in the year 2018/2019 based upon primary information acquired from the examined subjects. Examinations consist of firstly, data analysis and evaluation of the time series concerning job recruitment in the year 2011-2017. A forecast was produced, based on the obtained evaluations, using two forecasting methods. The results were analyzed and assessed. According to the data, the best forecast method was selected.

PL

W artykule poruszony został problem z zakresu prognozowania przyjęć do pracy na lata 2018/2019 na podstawie informacji pierwotnych uzyskanych z badanego podmiotu. Badania rozpoczęto od analizy i oceny szeregu czasowego dotyczącego przyjęć do pracy w latach 2011-2017. Na podstawie uzyskanych ocen, wykonano prognozowanie dwiema metodami prognostycznymi, które poddano analizie i ocenie. Uzyskane wyniki ocen pozwoliły wybrać najlepszą metodę prognostyczną.

13

Application of Markov Model in Crude Oil Price Forecasting

80%

Isah N. , Abdul Talib B.

Path of Science

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2017

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tom 3

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nr 8

1007-1012

EN

Crude oil is an important energy commodity to mankind. Several causes have made crude oil prices to be volatile. The fluctuation of crude oil prices has affected many related sectors and stock market indices. Hence, forecasting the crude oil prices is essential to avoid the future prices of the non-renewable natural resources to rise. In this study, daily crude oil prices data was obtained from WTI dated 2 January to 29 May 2015. We used Markov Model (MM) approach in forecasting the crude oil prices. In this study, the analyses were done using EViews and Maple software where the potential of this software in forecasting daily crude oil prices time series data was explored. Based on the study, we concluded that MM model is able to produce accurate forecast based on a description of history patterns in crude oil prices.

14

Influence of the Expected Wind Speed Fluctuation on the Number of Batteries of the Balancing System

80%

Yaremenko M. , Klen K.

Power Electronics and Drives

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2022

|

tom Vol. 7 (42)

187--196

EN

The article discusses a method of assessing the of dependence of the number of batteries that would be needed to achieve energy balance in distributed generation systems with wind turbines on ambient temperature and on the error involved in predicting the parameters of wind flow (wind speed). To describe the relationship between current rate and capacity in a given current range, Peukert’s law is used. Dependence of the Peukert's constant on ambient temperature for the lead-acid battery HZB12-180FA is calculated. Taking the lead-acid battery and wind turbine VE-2 as a reference, dependence of area of controlled operation of the battery on the wind speed forecasting error is calculated. The technique of considering ambient temperature, depth of discharge, and wind speed forecasting error when deciding the size of energy storage of the balancing system (the number of batteries and their capacity) is provided. A family of curves representing the dependence of the number of batteries constituting the balancing system on the ambient temperature and the wind speed forecasting error are presented. It is shown that as the wind speed forecasting error increases from 0% to 15% and the ambient temperature decreases from 20 °C to 20 °C, the number of batteries should be increased by approximately 2.81 times in order to maintain the same area of controlled operation of a battery.

15

Creating Trade Plans of Strategy Development with Foresight Methodology

80%

Markusik S. , Cieśla M.

Logistics and Transport

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2012

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tom 14

17-24

EN

Because structural innovation projects are burdened with high risk, there is a need for prior planning for rational investment decisions making, which can ensure the sustainable development of the industry. Finding the most probable development vision is one of the reasons why more and more successful and appreciable are studies connected with prediction of the future (known as: future studies), among which a method of foresight is also classified. The paper presents the problems associated with strategic planning based on foresight methodology, applied to searching for rational visions and scenarios for the development of transport systems.

16

Assessment of Composite Leading Indicators Usefulness in Forecasting Loans and Deposits Cyclical Fluctuations

80%

Garczarczyk J. , Skikiewicz R.

Prace i Materiały Instytutu Rozwoju Gospodarczego SGH

|

2011

|

tom 86:Business Surveys, Business Cycles. Polish Contribution to the 30th CIRET Conference

135-160

EN

The article has been focused on the application of the business cycle barometers for predicting the cyclical fluctuations of the two main categories in the banking market in Poland - PLN loans and PLN deposits. The barometers built for the first time for the Polish banking sector are based on sets of indicators, including both quantitative variables (official statistics data) and qualitative (among others derived from the business tendency survey conducted in the banking sector). Among the components of barometers both macro-economic indicators for the whole economy, as well as the variables from the financial sector and other sectors (including industry and trade) were used. The main aim of the article has been an evaluation of the characteristics of various types of composite leading indicators constructed on the basis of differentiated sets of variables. Then an attempt to construct three types of barometers: with the short, medium and long lead was made. In addition, the best composite leading indicators for each reference variable - PLN loans and PLN deposits were chosen.

17

Prognozowanie jedną metodą trzydziestu dwóch grup zmiennych

80%

Kozicki B. , Tomaszewski J. , Koszarek A.

Systemy Logistyczne Wojsk

|

2019

|

tom Vol. 51, no. 2

93--116

PL

W artykule poruszono problem badawczy dotyczący prognozowania jedną metodą trzydziestu dwóch grup zmiennych. Badania rozpoczęto od pozyskania danych pierwotnych w formie macierzy z strony internetowej Eurostatu. Dane pierwotne dotyczyły liczby lotnisk w trzydziestu dwóch państwach Europy w latach 2008-2017. Dalszym etapem było przeprowadzenie transformacji danych zawartych w macierzy w jeden szereg czasowy (badawczy). Szereg badawczy został poddany analizie i ocenie. Uzyskane oceny przeprowadzonych analiz pozwoliły wykryć tendencję, które stały się przesłanką do wyboru metod prognozowania. Wybrano dwie metody. Szereg badawczy został podzielony na dwie części na bazie których, zostały poddane analizie i ocenie dwie wybrane metody do prognozowania poprzez zastosowanie średniego bezwzględnego błędu prognozy. Najlepszą metodą wykonano prognozowanie szeregu badawczego na trzydzieści dwa przyszłe okresy.

EN

In this article, the author raises the research problem related to the forecasting of thirty-two groups of variables with one method. The research was initiated by gathering original data as a matrix from the Eurostat website. Original data concerned the number of airports in thirty-two European countries between 2008-2017. The next stage was the transformation of data included in the matrix into a time (research) series. The research series was analyzed and evaluated. The obtained results of analyses enabled the detection of a trend which became a premise for the choice of forecasting methods. Two methods were chosen. The research series was divided into two parts based on which these two forecasting methods were analyzed and evaluated with the application of a mean absolute forecasting error. The forecasting of the research series for thirty-two future periods was conducted with the best method.

18

Artificial Intelligence Methods in Spare Parts Demand Forecasting

80%

Rosienkiewicz M.

Logistics and Transport

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2013

|

tom 18

41-50

EN

The paper discusses the problem of forecasting lumpy demand which is typical for spare parts. Several prediction methods are presented in the article – traditional techniques based on time series and advanced methods that use Artificial Intelligence tools. The research conducted in the paper focuses on comparison of eight forecasting methods, including classical, hybrid and based on artificial neural networks. The aim of the paper is to assess the efficiency of lumpy demand forecasting methods that apply AI tools. The assessment is conducted by a comparison with traditional methods and it is based on Root Mean Square Errors (RMSE) and relative forecast errors (ex post) values. The article presents also a new approach to the lumpy demand forecasting issue – a method which combines regression modelling, information criteria and artificial neural networks.

19

Application of adaptive methods in demographic variables forecasting

80%

Sojka E.

Econometrics. Ekonometria. Advances in Applied Data Analytics

|

2015

|

nr 3 (49)

55-65

EN

The research paper is focused on the assessment of the usefulness of adaptive methods in forecasting demographic variables. The goal of the paper is to conduct the retro and prospective analysis of selected demographic values in the sphere of changes in time, and also to indicate an efficient method for the forecasting of the studied values in subsequent periods. The time series for Poland for the period between 2000 and 2013 are the basis for the development of the forecast. Mean squared errors of ex post forecasts are used as forecast quality measures. The results of the study show that among the applied methods of forecasting, the method of creeping trend with harmonic weights is the most suitable as it gives the smallest forecast errors.

20

Forecasting the electricity generation of photovoltaic plants

80%

Kuievda I. , Baliuta S. , Zinkevich P. , Stoliarov O.

Journal of New Technologies in Environmental Science

|

2021

|

tom Vol. 5, nr 1

40--45

EN

Due to the need in accordance with Ukrainian legislation to submit a day-ahead hourly forecast of electricity generation of solar power plants, the problem of forecasting model quality becomes very important. In the study it is proposed a method of choosing the optimal structure and sensitivity assessment of ANFIS-based forecasting model. In the model the input is solar irradiance, the output is solar panel generation power. The method is based on computational procedures using MATLAB software. For the data set, used in the study, the results, optimal for normalized mean absolute error (NMAE), were achieved on 5 triangular input member functions (trimf), while the error varied within 0.23% depending on number and shape of input member functions. According to the calculations of input error sensitivity of the forecasting model with 5 input trimf membership functions, the increasing of input error up to 8.19% NMAE leads to the raising of the output error in the testing sample up to 5.78%, NMAE. The rather low sensitivity of the model to the input data error allows us to conclude that forecasted meteorological data with a pre-known fixed forecast error can be used as input data.