The paper presents experiments with application of Radial Basis Function (RBF) network to Short Term Load Forecasting (STLF) problems. The proposed regression model is used to forecast forty-eight hours ahead electric load. The model has been implemented on real data: inputs to the RBF are past loads, weekday and special-day coding and the output is the load forecast for the given hour. Ordinary RBF was applied in the experiments. The centers of the Gaussian basis functions were selected on the base of the quasi-Newton algorithm. Mean absolute percentage error of about 4% is derived from the data from the Power System in Crete. The performance of the proposed model has been compared with simulations performed by the MLP network, and former models developed for the distribution company in Poland.Index Terms-Neural network, radial basis function network, short-term load forecasting.

The concept of Smart City is concerned primarily with integration ICT with processes performed in the city. The paper identifies applications and requirements of Smart Cities grouped into two topics: Smart Grid and Smart Tourism and reviews selected projects implemented in these areas in Poland.

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Cross-border innovation clusters are some of the essential concepts of reinforcing regional innovation capacities. In accordance with the concept of Industrie 4.0, introduced in 2011 in the Hannower Messe as the next industrial revolution, there appear new opportunities to build innovation clusters, combining innovation with a networked manufacturing system. Its core property will be new network technology on which they would create new products and services. This new type of cross-border innovation clusters will be the result from innovation policies carried out in regions. The main advantage of this type of clusters is that they allow the re-industrialization of regions, the end of mass production monopoly, and, thus, a successful competition with corporations, and also prosumerbased production. To achieve these objectives, the cluster has to deal with economically efficient technology. One of the key instruments of innovation policy will be the evaluation of the economic potential of the cluster before its appointment.The aim of the article is twofold. Firstly, it is to introduce the idea of a cross border innovation cluster and a network that combines innovation with a network manufacturing system. Secondly, the goal is to provide the method for assessing the economic potential of a prospective cross border innovation cluster. The assessment of cluster's economic potential, based on the evaluation of the technology used in its development and the future products and services, developed in the prospect cluster, will be among the most important tools of innovation policy in regions. This issue is important because the methodology of such an economic potential assessment of prospect cross-border innovation clusters has never been developed.In this study, the authors have collected representative examples of the implemented Industrie 4.0 solutions. Using a QuickLook assessment methodology, developed at the University of Texas, USA, and transferred to the University of Lodz, Poland, as a part of the offset program established in 2003, the authors have found that it could be applied to both Cyber-Physical System based Industrie 4.0 initiatives and other network manufacturing initiatives, based on the new technology. On the basis of a case study, concerning Polish cluster initiative Green Cars, the article concludes that there are many potential applications of the presented methodology to the Lithuanian-Polish prospect manufacturing system.