An ArcGIS Tool for Modeling the Climate Envelope with Feed-Forward ANN

This paper is about the development and the application of an ESRI ArcGIS tool which implements multi-layer, feed-forward artificial neural network (ANN) to study the climate envelope of species. The supervised learning is achieved by backpropagation algorithm. Based on the distribution and the grids of the climate (and edaphic data) of the reference and future periods the tool predicts the future potential distribution of the studied species. The trained network can be saved and loaded. A modeling result based on the distribution of European larch (Larix decidua Mill.) is presented as a case study.

Project finance in Hungarian electricity sector. Effect of feed-in tariff system’s change onto power plant investments

The research analyses the former and the current status of the small gas-motor power plant investments in the Hungarian energy sector. It discusses the development of project financing in the segment and the major changes and effects of new regulations and subsidy-policy implemented in 2010. The objective of this paper is to present the results of an empirical research of the so called GCHP projects, and to draw conclusion concerning how classic project financing conditions were present and changed during the last decade, and how regulation affected the current and future financial status of these projects.