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

机译:通过比较数据挖掘方法的战略投资规划太阳能验证:土耳其城市内的一个扩展榜样

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摘要

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.
机译:能源供应与数据管理是我世纪的关键挑战之一。具体而言,为了减少气候变化效应,随着能源需求的日期增加,造成严重的困境。它可以充分和解(可再生)能源技术的创新数据管理。研究人员,政府,非政府组织和公司讨论的新的环保规划方法和投资将为塑造未来提供基本和最重要的变量。我们使用现代数据挖掘方法(SOM和K-Means)和官方政府统计,根据其消费相似之处,福利水平和增长率,并在快速迈尔5.1的帮助下将它们与可再生资源的潜力进行比较和matlab软件。选择数据挖掘以使可能在第一眼中可能无法预测的变量内可见的可能秘密关系。在这里,我们的目标是在与利用软件中同时看到验证过程中所选算法的成功水平。此外,我们旨在提高决策者和利益攸关方的创新方法,通过同时照顾不同的变量,可再生资源是最适合确切的区域。

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