For the optimal design and selection of solar energy conversion systems, as well as for other fields of interest, such as architecture, agriculture, hydrology and ecology, the knowledge of accurate ...global solar radiation data is extremely important. However, due to the cost and difficulty in solar radiation measurements these data are not easily available for many countries. Therefore many empirical models have been developed by various researchers to predict global solar radiation from readily available data. The number of developed models is relatively high, which makes it difficult to choose the most appropriate one for a particular purpose and site. There are several studies in which authors evaluate different models for specific location. However, there is no comprehensive study in which these models are evaluated in case of global use. The main objective of this study is to evaluate different solar radiation models on global scale, which might be helpful in the selection of the most appropriate and accurate model based on the available sunshine data. Using the radiation data corresponding to 924 sites throughout the world we conducted a detailed statistical analysis of 101 different solar radiation models that are available in literature. Ten statistical indicators were used to assess models performance. In addition, we introduced specific global performance indicator (GPI), by means of which all analyzed models are depicted with a single parameter and easily ranked.
In many solar applications knowing diffuse solar radiation on horizontal surface represents an important requirement. The measurement of diffuse radiation is quite expensive, and because of that ...solar radiation measurements are not easily available in many locations around the world. Therefore many empirical correlations have been developed by various researchers to predict diffuse radiation from available meteorological data. The main objective of this study is to assess and compare different diffuse solar models available in the literature. These empirical models have been derived for specific location using long term measurements for that location. There is no general formula to calculate the diffuse solar radiation at any location in the world. While there are several studies in which authors compare different diffuse models for specific location, there is no comprehensive study in which these models are compared on a global scale. In this study we used statistical analysis to evaluate performance of analyzed models using long term measurements at 267 different sites around the world. Ten statistical quantitative indicators are used to evaluate different diffuse solar radiation models. The results are also visually presented by means of Taylor diagrams, which give a clear picture of how close a particular model is to measured data and how it is relatively compared to other models.
Traffic is the main source of noise in urban environments and significantly affects human mental and physical health and labor productivity. Therefore it is very important to model the noise produced ...by various vehicles. Techniques for traffic noise prediction are mainly based on regression analysis, which generally is not good enough to describe the trends of noise. In this paper the application of artificial neural networks (ANNs) for the prediction of traffic noise is presented. As input variables of the neural network, the proposed structure of the traffic flow and the average speed of the traffic flow are chosen. The output variable of the network is the equivalent noise level in the given time period Leq . Based on these parameters, the network is modeled, trained and tested through a comparative analysis of the calculated values and measured levels of traffic noise using the originally developed user friendly software package. It is shown that the artificial neural networks can be a useful tool for the prediction of noise with sufficient accuracy. In addition, the measured values were also used to calculate equivalent noise level by means of classical methods, and comparative analysis is given. The results clearly show that ANN approach is superior in traffic noise level prediction to any other statistical method.
•Optimum yearly, biannual, seasonal, monthly, and daily tilt angles were found.•Energy collected per square meter is compared for ten different scenarios.•Four seasonal scenarios and two biannual ...scenarios were considered.•It is sufficient to adjust tilt angles only twice per year.
The amount of energy that is transformed in solar collector depends on its tilt angle with respect to horizontal plane and orientation of the collector. In this article the optimum tilt angle of solar collectors for Belgrade, which is located at the latitude of 44°47′N is determined. The optimum tilt angle was found by searching for the values for which the solar radiation on the collector surface is maximum for a particular day or a specific period. In that manner the yearly, biannual, seasonal, monthly, fortnightly, and daily optimum tilt angles are determined. Annually collected energy per square meter of tilted surface is compared for ten different scenarios. In addition, these optimum tilt angles are used to calculate the amount of energy on the surface of PV panels that could be installed at the roof of the building. The results show that for observed case study placing the panels at yearly, seasonal and monthly optimum tilt angles, would yield increasing yearly amount of collected energy by factor of 5.98%, 13.55%, and 15.42% respectively compared to energy that could be collected by putting the panels at current roofs’ surface angles.
Studies of small and medium-sized enterprise (SMEs) development around the world show that the most significant factor for increasing their numbers and improving business success is the free ...enterprise, as exogenous, and innovation as an endogenous variable. At the same time, the dominant view in economic theory is that innovation is a key generator of changes for which the SMEs can be considered as a kind of metaphors for a successful business over the last twenty years in a number of economies. Arguing that cooperation between SMEs is increasingly common generic strategy of their development, the paper first explains the importance of collaboration to increase innovation and competitiveness, and then provides possible models using information technology such as Workflow Management Systems (WfMS), Service Oriented Architecture (SOA) and Service-Oriented Cloud Computing Architecture (SOCCA) to support the collaboration of these business entities. Solutions provided are aimed at improving the innovativeness of SMEs and fully follow the requirements of the so-called fifth-generation innovation process whose key attributes are integration and flexibility.
Starting from the premise that the phenomenon of innovation is at the heart of modern economic policies, the focus of the paper is on the most innovative and least innovative European countries, ...based on the values of the 12th pillar of the Global Competitiveness Index (GCI) - Innovation. The research centres on the analysis of the selected countries, observing them as 10 innovation leaders and 10 innovation learners of Europe in 2013. Cluster analysis of the selected countries shows the depth of the gap between the formed clusters of innovation leaders and innovation learners. By applying the method of visualisation, the paper examines the components of the pillar Innovation in respect of these countries. With regard to the clusters formed and a big difference between them, the further course of the research includes the time dimension and analyses the trend of innovativeness in the studied groups of countries for the period 2006 - 2015. The time series graphs for each of the clusters, according to indicators of Innovation, with average values per cluster have been constructed, showing also the trend lines for each of the clusters. Bearing in mind that the majority of macroeconomic time series exhibits time dependence, dynamic relations between them are analysed using the VAR model. Statistically significant interdependence is established between the observed series. Furthermore, through simple linear regression, the impact of innovativeness on GDP per capita of the observed group of countries is examined. It can be concluded that, in addition to the pronounced gap between the achieved levels of innovativeness of the observed groups of countries, there is a positive impact of innovativeness on the achieved level of GDP per capita, expressed in the purchasing power of the domestic currency on the part of the group of innovation 'learners' in the reporting time period.
The paper considers the level of competitiveness of two groups of Balkan countries. The first group consists of neighboring countries of the Republic of Serbia that are not members of the EU ...(Albania, Bosnia and Herzegovina, Macedonia, Montenegro, Serbia), while the second group consists of five member states of the EU (Bulgaria, Croatia, Greece, Hungary and Romania). Research refers to a time period from 2006 to 2015. The level of competitiveness of countries is analyzed through the value of the Global Competitiveness Index of the World Economic Forum. Special focus is on Basic & Efficiency factors based competitiveness, on the one hand, and Innovation & Sophistication factors based competitiveness, on the other. The conclusion is that Serbia and the selected non-EU countries are lagging behind the group of EU countries, by all indicators. However, data for the observed period reveal trend of convergence of these groups' competitiveness.
Over the last decade, promotion of competitiveness represents one of the central goals of economic policy of most of the countries. Moreover, in recent years, the promotion of competitiveness has ...been seen as a way of achieving desirable changes in economy and society. While there is no unity of views in the theory regarding the conceptual definition of the phenomenon of competitiveness, it is becoming less arguable that in strictly economic terms, competitiveness is a synonym for productivity. However, it should be noted that productivity growth that is accompanied by increasing social imbalance (for example, inequality in income distribution), on the one hand, and environmental pollution, on the other hand, cannot be a guarantee of improving the competitiveness of countries in the long run. Acknowledging precisely this fact and using the data from World Economic Forum on Global Competitiveness 2013, this paper elaborates on the phenomenon of sustainable competitiveness and tests the hypothesis about the positive impact of its social and environmental dimension on the economic dimension of sustainable competitiveness that is represented by the value of the Global Competitiveness Index. The survey of 34 countries confirmed the indisputable positive impact of the social dimension of sustainability, but also variable direction of the impact of the environmental dimension of sustainability (depending on the level of GDP per capita) on the economic dimension of sustainable competitiveness of European countries in 2013.
The paper presents an empirical analysis of the impact of institutional reform policies and institutional quality on the economic growth of five Western Balkan countries (WB countries: Serbia, ...Montenegro, Bosnia and Herzegovina, Northern Macedonia and Albania) in the period 2006-2016. It was developed its own model of quantification concerning the impact of the most important indicators of the quality of institutions on the economic growth of these countries, which are in a delayed phase of transition and at some stage in the EU accession process. Achieving high and stable rates of economic growth for WB countries becomes the ultimate prerequisite for completing the EU transition and accession process. In order to improve growth dynamics, among other things, it is necessary to identify key drivers of growth and to model appropriate growth and development policies based on the results obtained. In the paper, WB countries were viewed as a whole. By empirically testing the impact of individual quality indicators of institutions on economic growth, according to the World Bank Governance Indicators methodology by using panel data multiple linear regression analysis, the largest statistically significant and positive impact came from the Government Effectiveness and Regulatory Quality variable. The intensity of the impact of the Control of Corruption and Rule of Law variable on GDP per capita is slightly weaker, but it is also very pronounced. In this respect, the empirical results obtained can be a useful framework for modeling the development policies of WB countries. They represent an important guide for policy makers to implement measures aimed at improving the quality of institutions and at the same time modeling economic growth policies.
The paper examines the impact of the social dimension of sustainable competitiveness on the economic dimension, where the social dimension is represented by Indicators of social sustainability, and ...economic dimension by the Global competitiveness index, GCI. This allows for the identification of various Indicators of social sustainability and their individual and aggregate impact on GCI, which allows for identifying strengths and weaknesses in building competitiveness (from social aspect) and gives recommendations for strengthening and improving competitiveness of the observed group of countries. In this regard, impact model of indicators of social sustainability on GCI is defined, and examined based on a sample of 30 European countries. Data in WEF Global Competitiveness Report for for 2012, 2013, 2014, 2015, 2016 and 2017 was used. Analysis included two sets of countries with data on: 17 old free market economy countries in Europe (Austria, Belgium, Cyprus, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, UK) and 13 post transition free market economy countries in Europe on the basis of the economic historical background (Bulgaria, Croatia, Czech Rep., Estonia, Hungary, Latvia, Lithuania, Macedonia, Poland, Romania, Serbia, Slovak Rep., Slovenia).
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