English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Open

Presents the pdf analysis as premium feature

PDF Analysis

Insights

Presents the summarisation as premium feature

Summarisation

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Energy supply together with the data management is one of the key challenges of our century. Specifically, to decrease the climate change effects as energy requirement increases day by day poses a serious dilemma. It can be adequately reconciled with innovative data management in (renewable) energy technologies. The new environmental-friendly planning methods and investments that are discussed by researchers, governments, NGOs, and companies will give the basic and most important variables in shaping the future. We use modern data mining methods (SOM and K -Means) and official governmental statistics for clustering cities according to their consumption similarities, the level of welfare, and growth rate and compare them with their potential of renewable resources with the help of Rapid Miner 5.1 and MATLAB software. The data mining was chosen to make the possible secret relations visible within the variables that can be unpredictable at first sight. Here, we aim to see the success level of the chosen algorithms in validation process simultaneously with the utilized software. Additionally, we aim to improve innovative approach for decision-makers and stakeholders about which renewable resource is the most suitable for an exact region by taking care of different variables at the same time.

Solar Energy Validation for Strategic Investment Planning via Comparative Data Mining Methods: An Expanded Example within the Cities of Turkey