Predicting of Solar Power Generation using Random Forest Regression (Record no. 86010)

MARC details
000 -LEADER
fixed length control field 01824nam a22002657a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251016094134.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250909b ||||| |||| 00| 0 eng d
043 ## - GEOGRAPHIC AREA CODE
Geographic area code URS
245 ## - TITLE STATEMENT
Title Predicting of Solar Power Generation using Random Forest Regression
Remainder of title / Mentoy, Jane J.... [et al.].
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Date of publication, distribution, etc. November 2024
300 ## - PHYSICAL DESCRIPTION
Extent 30 leaves :
Other physical details illustrations ;
Dimensions 28 cm.
336 ## - CONTENT TYPE
Source rdacontent
Content type term text
337 ## - MEDIA TYPE
Source rdamedia
Media type term unmediated
338 ## - CARRIER TYPE
Source rdacarrier
Carrier type term volume
502 ## - DISSERTATION NOTE
Dissertation note Thesis
Degree type Bachelor of Science in Mathematics
Name of granting institution University of Rizal System-Morong
Year degree granted 2024
520 ## - SUMMARY, ETC.
Summary, etc. This research explores predicting solar power consumption at Kasarinlan Ecopark in Baras, Rizal, using Random Forest Regression. Solar energy is increasingly used as a sustainable alternative to fossil fuels due to its environmental benefits and low maintenance requirements. However, accurately predicting the power output from solar panels remains a challenge because the voltage generated can vary greatly and is difficult to estimate. This study addresses this issue by applying four supervised machine-learning techniques to predict solar power consumption. The results show that Random Forest Regression provides the most accurate predictions with minimal errors. The findings highlight the effectiveness of using Random Forest for solar energy forecasting, helping to improve the efficient use of solar power in grid systems.
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Mentoy, Jane J.
Relator term author
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Bandong, Charisse Mae B.
Relator term author
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Estremos, Danilo Jr. J.
Relator term author
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Gonzales, Radnajelo S.
Relator term author
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Olinares, Gracelyn Y.
Relator term author
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Dela Cruz, Shiela Marie F.
Relator term degree supervisor
856 ## - ELECTRONIC LOCATION AND ACCESS
Materials specified Online Request for Student Unpublished Works
Uniform Resource Identifier <a href="https://forms.gle/iwQgJ2wFRviEt3BA8">https://forms.gle/iwQgJ2wFRviEt3BA8</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Theses and dissertations
Holdings
Withdrawn status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Date acquired Barcode Date last seen Price effective from Koha item type
  Library of Congress Classification     Reference Morong College Library Morong College Library 09/09/2025 URSMOR-CL-7023 09/09/2025 09/09/2025 Theses and dissertations

University of Rizal System
Email us at univlibservices@urs.edu.ph

Visit our Website www.urs.edu.ph/library