Decision support system for construction works based on precipitation data analysis/ (Record no. 394)

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003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250321162802.0
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040 ## - CATALOGING SOURCE
Transcribing agency NVSU
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Sumagpao, Argie S.
245 ## - TITLE STATEMENT
Title Decision support system for construction works based on precipitation data analysis/
Statement of responsibility, etc. Argie S. Sumagpao
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Bayombong:
Name of publisher, distributor, etc. Nueva Vizcaya State University,
Date of publication, distribution, etc. 2023
300 ## - PHYSICAL DESCRIPTION
Extent xi, 96 leaves :
Other physical details illustrations (some colored) ;
Dimensions 28 cm.
500 ## - GENERAL NOTE
General note The main aim of the study was to establish online interface of Civil Engineering project using the forecasted data from CY 2003 to 2022 in Nueva Vizcaya and determine the acceptability level of the online interface using the engineering project. Descriptive exploratory type of research was used in this study. The study was conducted mid-year of 2023 in the province of Nueva Vizcaya however the available data on precipitation used for the analysis were that from January 2003 to December 2022 Precipitation data from January 2003 to December 2022 were collected from the Agromet Station of Nueva Vizcaya State University Bayombong (NVSU-PAGASA) These data were used to forecast the precipitation of Nueva Vizcaya Province for CY 2024.<br/><br/> The month of April, May June, July, August, September, and October 2024 respectively, the seasonal adjustment factor (SAF) of precipitation was more than 200 min, it was in these months the precipitation was above the typical months. Among these months, September 2024 had the highest SAF of 315.118 mm followed by May 2024 which had SAF of 244.370 mm. Expert modeler of SPSS ver. 25 was used to find the best fit model for forecasting precipitation using mean rainfall all lagged at 12 months as covariates. It suggests the seasonal autoregressive integrated moving average model, SARIMA (1,0,1) (1,0,1)12 as the best fit statistical model for this time series data. It was found that twelve months climatic factors, mean rainfall (P value 0.043) lagged at 12 months were significant predictors of precipitation in the study area. Strong precipitations were found to occur between the months of April until October with a peak in the month of September. Since the entire year, or 12 months were notable for precipitation there is a high correlation that there are chances of rainfall in one month and the succeeding months in Nueva Vizcaya. It is also noted that the maximum precipitations during the months of September and decreases of precipitation thereafter. The level of acceptability had an overall average of 3.72 classified as strongly accepted.<br/><br/>Keywords: Precipitation, Time Series, SARIMA, Acceptability, Online Interface
500 ## - GENERAL NOTE
General note Thesis (Master of Arts in Teaching - Mathematics)
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes appendices and bibliographical references
942 ## - ADDED ENTRY ELEMENTS (KOHA)
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    Dewey Decimal Classification     Nueva Vizcaya State University - Bayombong Campus Nueva Vizcaya State University - Bayombong Campus Graduate School Section 03/21/2025 Donation   T Su955d 2023 T1045 03/21/2025 03/21/2025 Thesis

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