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Load Forecasting Algorithms with Simulation & Coding
Amogha A.K.1
Section:Research Paper, Product Type: Journal
Vol.7 ,
Issue.2 , pp.15-20, Apr-2019
Online published on Apr 30, 2019
Copyright © Amogha A.K. . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: Amogha A.K., “Load Forecasting Algorithms with Simulation & Coding,” International Journal of Scientific Research in Network Security and Communication, Vol.7, Issue.2, pp.15-20, 2019.
MLA Style Citation: Amogha A.K. "Load Forecasting Algorithms with Simulation & Coding." International Journal of Scientific Research in Network Security and Communication 7.2 (2019): 15-20.
APA Style Citation: Amogha A.K., (2019). Load Forecasting Algorithms with Simulation & Coding. International Journal of Scientific Research in Network Security and Communication, 7(2), 15-20.
BibTex Style Citation:
@article{A.K._2019,
author = {Amogha A.K.},
title = {Load Forecasting Algorithms with Simulation & Coding},
journal = {International Journal of Scientific Research in Network Security and Communication},
issue_date = {4 2019},
volume = {7},
Issue = {2},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {15-20},
url = {https://www.isroset.org/journal/IJSRNSC/full_paper_view.php?paper_id=362},
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
UR - https://www.isroset.org/journal/IJSRNSC/full_paper_view.php?paper_id=362
TI - Load Forecasting Algorithms with Simulation & Coding
T2 - International Journal of Scientific Research in Network Security and Communication
AU - Amogha A.K.
PY - 2019
DA - 2019/04/30
PB - IJCSE, Indore, INDIA
SP - 15-20
IS - 2
VL - 7
SN - 2347-2693
ER -
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Abstract :
This paper provides simulations of load forecasting using GMDH Shell software, GNU Octave software and MATLAB software. The analysis made in this paper uses the algorithms like ANN and time- series. Such algorithms help in providing the good accuracy in finding the predictions of the load.
Key-Words / Index Term :
Load Forecasting, ANN, Time series Algorithm
References :
[1] Y. P. Wang, D.X. Huang , H.Q. Xiong, and Y. L. Niu, “Using relational analysis and multi-variable grey model for electricity demand forecasting in smart grid environment, ” Power System Protection and Control, vol.40, no.1, pp.96-100, 2012.
[2] Y. Yang and D. Xue ,“ Continuous fractional-order grey model and electricity prediction research based on the observation error feedback,” Energy, vol. 115, pp. 722-733, 2016.
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