Abstract
This paper presents an integrated and novel service environment for real-time interactions between users, as well as enhanced visualization and decision support services over extremely large volumes of heterogeneous Renewable data sources. The integrated visual analytics methods, allow energy analysts to incorporate their expert knowledge into the analysis, so as to dynamically investigate the observed events and locations, and accurately identify the preferable results. The goal of visual analytics research is to turn the information overload into an opportunity by enabling decision-makers to examine this massive amount of information to make effective decisions.
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Konstantinos, V., Karras, Y., Kohlhammer, J., Steiger, M., Tzovaras, D., Gounopoulos, E. (2014). Enhanced Visual Analytics Services for the Optimal Planning of Renewable Energy Resources Installations. In: Iliadis, L., Maglogiannis, I., Papadopoulos, H., Sioutas, S., Makris, C. (eds) Artificial Intelligence Applications and Innovations. AIAI 2014. IFIP Advances in Information and Communication Technology, vol 437. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44722-2_35
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DOI: https://doi.org/10.1007/978-3-662-44722-2_35
Publisher Name: Springer, Berlin, Heidelberg
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