• Corpus ID: 67769671

A Novel Universal Solar Energy Predictor

@article{Bidikar2019ANU,
  title={A Novel Universal Solar Energy Predictor},
  author={Nirupam Bidikar and Kotoju Rajitha and P. Usha Supriya},
  journal={ArXiv},
  year={2019},
  volume={abs/1902.06660}
}
Solar energy is one of the most economical and clean sustainable energy sources on the planet. However, the solar energy throughput is highly unpredictable due to its dependency on a plethora of conditions including weather, seasons, and other ecological/environmental conditions. Thus, the solar energy prediction is an inevitable necessity to optimize solar energy and also to improve the efficiency of solar energy systems. Conventionally, the optimization of the solar energy is undertaken by… 

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References

SHOWING 1-10 OF 18 REFERENCES

A Novel Application of Naive Bayes Classifier in Photovoltaic Energy Prediction

By means of the Naïve Bayes application, the accuracy measures are improved and the effects of other solar attributes on the photovoltaic energy generation are evaluated.

Pvlib Python: a Python Package for Modeling Solar Energy Systems

pvlib python is a community-supported open source tool that provides a set of functions and classes for simulating the performance of photovoltaic energy systems. pvlib python aims to provide

k-Means Partition of Monthly Average Insolation Period Data for Turkey

The most productive and the most unfavorable places among all provinces are mined on the basis of monthly average insolation period for the 75 provinces in Turkey.

Predictive Analytics and Data Mining: Concepts and Practice with RapidMiner

This book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions, and implement a simple step-by-step process for predicting an outcome or discovering hidden relationships using RapidMiner, an open source GUI based data mining tool.

Top 10 algorithms in data mining

This paper presents the top 10 data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM) in December 2006: C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN,

Scikit-learn: Machine Learning in Python

Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing

“A and B”:

Direct fabrication of large micropatterned single crystals. p1205 21 Feb 2003. (news): Academy plucks best biophysicists from a sea of mediocrity. p994 14 Feb 2003.