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1.
Evaluation of Machine Learning Algorithms for Predicting the Processing Time of Order Picking in a Warehouse
Tilen Škrinjar, 2019, master's thesis

Abstract: Optimization of warehouse processes increases efficiency and lowers the cost of managing a warehouse. The most expensive and time-consuming activity is picking. Knowing picking process time is an important factor for proper organization of material and information flow. Orders delivered to a packing station too early or too late can cause delays in a warehouse. The purpose of this study is to evaluate machine learning pipeline for processing time prediction of order picking. This includes data gathering, data preprocessing and the evaluation of machine learning algorithms, which are the most important aspects of this research.
Keywords: warehouse, order picking, machine learning, regression analysis
Published: 25.02.2019; Views: 698; Downloads: 0

2.
Statistical analysis of the development indicators' impacts on e-commerce of individuals in selected European countries
Ksenija Dumičić, Ivana Skoko Bonić, Berislav Žmuk, 2018, original scientific article

Abstract: The aim of this paper is to analyse the influence of the development level indicators on the e-commerce, i.e. on the online purchase by individuals, in selected European countries in 2013. In the analysis, the main variable under study and all the independent variables are included as standardised. Based on nine variables, the principal component analysis with varimax rotation was performed and the two extracted factors were used as the regressors in the multiple regression analysis. In the regression model both components, Factor 1, which includes seven variables, called Prosperity, Investing in Education and IT Infrastructure, and Awareness, and Factor 2, comprised of two variables, called IT Skills, are statistically significant at the significance level of 1%. Both factors show a positive correlation with the online purchase of individuals. Inclusion and analysis of distributions and impacts of even nine independent variables, which make up two distinct factors affecting the e-commerce, make a new contribution of this work.
Keywords: e-commerce, broadband access to the Internet, factor analysis, multiple regression analysis
Published: 10.10.2018; Views: 629; Downloads: 291
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3.
Prediction of California Bearing Ratio (CBR) and Compaction Characteristics of granular soil
Attique ul Rehman, Khalid Farooq, Hassan Mujtaba, 2017, original scientific article

Abstract: This research is an effort to correlate the index properties of granular soils with the California Bearing Ratio (CBR) and the compaction characteristics. Soil classification, modified proctor and CBR tests conforming to the relevant ASTM methods were performed on natural as well as composite sand samples. The laboratory test results indicated that samples used in this research lie in SW, SP and SP-SM categories based on Unified Soil Classification System and in groups A-1-b and A-3 based on the AASHTO classification system. Multiple linear regression analysis was performed on experimental data and correlations were developed to predict the CBR, maximum dry density (MDD) and optimum moisture content (OMC) in terms of the index properties of the samples. Among the various parameters, the coefficient of uniformity (Cu), the grain size corresponding to 30% passing (D30) and the mean grain size (D50) were found to be the most effective predictors. The proposed prediction models were duly validated using an independent dataset of CBR tests on sandy soils. The comparative results showed that the variation between the experimental and predicted results for CBR falls within ±4% confidence interval and that of the maximum dry density and the optimum moisture content are within ±2%. Based on the correlations developed for CBR, MDD and OMC, predictive curves are proposed for a quick estimation based on Cu , D30 and D50. The proposed models and the predictive curves for the estimation of the CBR value and the compaction characteristics would be very useful in geotechnical & pavement engineering without performing the laboratory compaction and CBR tests.
Keywords: CBR, regression, model, prediction, compaction characteristics
Published: 18.06.2018; Views: 562; Downloads: 156
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4.
Evolutionary-based prediction of ε50 for the lateral load-displacement behavior of piles in clay
Babak Ebrahimian, Aida Nazari, 2013, original scientific article

Abstract: Analyzing piles that are subjected to lateral loads reveals that their behavior depends on the soil’s resistance at any point along the pile as a function of the pile’s deflection, known as the p-y curve. On the other hand, the deformation characteristics of soil defined as “the soil strain at 50% of maximum deviatoric stress (ε50)” have a considerable effect on the generated p-y curve. In this research, several models are proposed to predict ε50 specifically for designing the very long pile foundations of offshore oil and gas platforms in the South Pars field, Persian Gulf, Iran. Herein, ε50 is evaluated using extensive soil data, including in-situ and laboratory test results using evolutionary polynomial regression (EPR). The effects of the undrained shear strength, the normalized tip resistance of the cone penetration test, the over-burden pressure, the plasticity index and the over-consolidation ratio on ε50 are investigated in marine clays. It is demonstrated that the normalized cone tip resistance, which is an indication of the soil’s undrained shear strength, leads to more realistic ε50 values compared with the laboratory-derived undrained shear strength parameter. In addition, the application of the soil-index properties and the over-burden pressure in the models, improves their estimation quality. Furthermore, the results of full-scale lateral pile load tests at different sites are used in order to validate the performance of the proposed models when it comes to predicting the behavior of the lateral piles.
Keywords: p-y curve, laterally loaded pile, piezocone penetration test, PCPT, marine clay, evolutionary polynomial regression, EPR, South Pars field
Published: 14.06.2018; Views: 452; Downloads: 50
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5.
Radon anomalies in soil gas caused by seismic activity
Boris Zmazek, Mladen Živčić, Ljupčo Todorovski, Sašo Džeroski, Janja Vaupotič, Ivan Kobal, 2004, original scientific article

Abstract: At the Orlica fault in the Krško basin, combined barasol detectors were buried in six boreholes, two along the fault itself and four on either side of it, to measure and record radon activity, temperature and pressure in soil gas every 60 minutes for four years. Data collected have been analysed in a manner aimed at distinguishing radon anomalies resulting from environmental parameters (air and soil temperature, barometric pressure, rainfall) from those caused solely by seismic events. The following approaches have been used to identify anomalies: (i) ± 2σ deviation of radon concentration from the seasonal average, (ii) correlation between time gradients of radon concentration and barometric pressure, and (iii) prediction with regression trees within a machine learning program. In this paper results obtained with regression trees are presented. A model has been built in which the program was taught to predict radon concentration from the data collected during the seismically inactive periods when radon is presumably influenced only by environmental parameters. A correlation coefficient of 0.83 between measured and predicted values was obtained. Then, the whole data time series was included and a significantly lowered correlation was observed during the seismically active periods. This reduced correlation is thus an indicator of seismic effect.
Keywords: radon in soil gas, environmental parameters, earthquakes, correlation, regression trees, forecasting
Published: 15.05.2018; Views: 815; Downloads: 55
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6.
Financial system and agricultural growth in Ukraine
Olena Oliynyk, 2017, original scientific article

Abstract: Background/Purpose: An effective financial system should increase the efficiency of economic activities. This study provides evidence regarding the importance of financial development for agricultural growth in Ukraine. Methodology: We used non-integrated and integral indicators, time series and regression analysis to investigate the link between the financial development and agricultural growth. Results: The results based on integral indicators shows that the financial development does not affect agricultural growth in Ukraine. The study based on non-integrated indicators, which characterizes various aspects of the financial system’s banking component and agricultural growth, provided a significant link between the financial system and agriculture growth. The regression models revealed if bank deposits to GDP (%) increases the value added per worker in agriculture increases exponentially. The results of the study indicate that, agriculture is more sensitive to lending changes than the vast majority of other sectors of the economy. The increasing lending of one UAH (Ukrainian hryvnia) resulted in retail turnover growth of 1.62 UAH, while agricultural gross output, growth was UAH 5.06. Conclusion: Our results reveal a positive relationship between financial system’s banking component and agriculture growth in Ukraine. The results indicate the necessity for continued research into further developing universal methodological approaches of appraising the nexus of the financial system’s banking component on agriculture growth in general as well separate farm groups. The results of our study has important implications on policy making authorities efforts to stimulate agricultural growth by improving the efficiency of the financial system’s banking component.
Keywords: agricultural growth, the integral indicator of the agricultural growth, the integral indicator of the financial development, time series analysis, regression analysis, financial system
Published: 04.05.2018; Views: 711; Downloads: 276
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7.
Historic train stations in Małopolskie Province during the railroad industry regression
Tomasz Chaberko, 2008, original scientific article

Abstract: Train stations tend to be the most representative constructions of the railroad industry. In many cases they are considered as interesting transportation and architectural monuments. In Poland, where the rail network was developed mostly before World War I, they constitute the most numerous group of monuments of Poland’s industrial era. The main goal of this paper is to indicate the historic train station buildings (those dating back to the period 1847-1918) in Małopolskie Province and determine their role in the modern railroad transportation system. As a backdrop for the discussion, a few background elements are included. They are: chosen architectural hallmarks of train stations in the Austro-Hungarian Empire, selected issues concerning the railroad history of Galicia and contemporary aspects of the railroad industry’s current regression. It is in this context that the state and prospective utilization of historic rail stations are portrayed.
Keywords: railroad industry, cultural heritage, industrial landmarks, railroad industry regression, Małopolskie Province, Poland
Published: 15.03.2018; Views: 487; Downloads: 59
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8.
Organization in finance prepared by stohastic differential equations with additive and nonlinear models and continuous optimization
Pakize Taylan, Gerhard-Wilhelm Weber, 2008, original scientific article

Abstract: A central element in organization of financal means by a person, a company or societal group consists in the constitution, analysis and optimization of portfolios. This requests the time-depending modeling of processes. Likewise many processes in nature, technology and economy, financial processes suffer from stochastic fluctuations. Therefore, we consider stochastic differential equations (Kloeden, Platen and Schurz, 1994) since in reality, especially, in the financial sector, many processes are affected with noise. As a drawback, these equations are hard to represent by a computer and hard to resolve. In our paper, we express them in simplified manner of approximation by both a discretization and additive models based on splines. Our parameter estimation refers to the linearly involved spline coefficients as prepared in (Taylan and Weber, 2007) and the partially nonlinearly involved probabilistic parameters. We construct a penalized residual sum of square for this model and face occuring nonlinearities by Gauss-Newton's and Levenberg-Marquardt's method on determining the iteration step. We also investigate when the related minimization program can be written as a Tikhonov regularization problem (sometimes called ridge regression), and we treat it using continuous optimization techniques. In particular, we prepare access to the elegant framework of conic quadratic programming. These convex optimation problems are very well-structured, herewith resembling linear programs and, hence, permitting the use of interior point methods (Nesterov and Nemirovskii, 1993).
Keywords: stochastic differential equations, regression, statistical learning, parameter estimation, splines, Gauss-Newton method, Levenberg-Marquardt's method, smoothing, stability, penalty methods, Tikhonov regularization, continuous optimization, conic quadratic programming
Published: 10.01.2018; Views: 570; Downloads: 60
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9.
Impact of ICTs on innovation activities
Jovana Zoroja, 2016, original scientific article

Abstract: The development and usage of information and communication technologies (ICTs) has particularly increased in the last two decades, while at the same time showing great potential to improve the efficacy of business processes, facilitate and drive innovations, and therefore increase competitiveness. Innovation activities represent an important factor for social and economic change as well as for increasing competitive advantages at both the national and firm levels. This paper focuses on the role that ICTs play in the innovation performance of selected European countries. Using data drawn from the Eurostat and Global Competitiveness Index (2007–2011) and panel regression analysis, research results indicate that ICTs have a significant impact on business innovation activities.
Keywords: information and communication technology, innovation, business sophistication, competitiveness, European countries, regression analysis
Published: 13.11.2017; Views: 609; Downloads: 94
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10.
Obvladovanje tveganj pri »peer to peer« posojilih
Andrej Blagotinšek, 2017, master's thesis

Abstract: Nove digitalne tehnologije botrujejo procesu preoblikovanja obstoječih vrednostih verig finančnih produktov oz. storitev. »P2P« posojila so nov in inovativen način tako investiranja presežkov finančnih sredstev kot tudi prejemanja finančnega kapitala. Število tovrstnih posojil konstantno raste, vendar posojilodajalci niso profesionalni investitorji. Posojilodajalci prevzemajo veliko tveganje, saj so »P2P« posojila izdana brez zavarovanja. V ta namen »P2P« platforme izdajajo historične podatke o posojilojemalcih. V delu se osredotočamo na identifikacijo tveganj, ki so prisotna pri tovrstnem investiranju in na napovedovanje možnosti neplačil posojil. Empirična študija analizira podatke pridobljene iz platforme Bondora (N=1823) od leta 2009 do 2015. Opravili smo statistično analizo spremenljivk. Razvili smo Logit model za napovedovanje neplačil. Kakovost modela smo preverjali z ROC krivuljo, optimizacijo modela pa na osnovi uravnoteženja klasifikacijske natančnosti, kjer smo dololčili optimalno presečno vrednost. Rezultati so pokazali, da kreditni model za napovedovanje neplačil zmanjšuje verjetnost finančne izgube pri »P2P« investiranju.
Keywords: kreditno tveganje, verjetnost neplačila, »P2P« posojila, LOGIT model, obvladovanje tveganj, C25 Discrete Regression and Qualitative Choice Models, G21 Banks, G17, Financial Forecasting and Simulation
Published: 27.10.2017; Views: 1487; Downloads: 268
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