Bibliographic citations
Romero, M., (2023). Modelo de regresión lineal del comportamiento de ruido influenciado por el tránsito vehicular en el barrio de Calvario, Moyobamba [Universidad Nacional de San Martín. Fondo Editorial]. http://hdl.handle.net/11458/5249
Romero, M., Modelo de regresión lineal del comportamiento de ruido influenciado por el tránsito vehicular en el barrio de Calvario, Moyobamba []. PE: Universidad Nacional de San Martín. Fondo Editorial; 2023. http://hdl.handle.net/11458/5249
@misc{renati/1058674,
title = "Modelo de regresión lineal del comportamiento de ruido influenciado por el tránsito vehicular en el barrio de Calvario, Moyobamba",
author = "Romero Marina, Marco Vinicio",
publisher = "Universidad Nacional de San Martín. Fondo Editorial",
year = "2023"
}
Linear regression model of noise behavior influenced by vehicular traffic in the neighborhood of Calvario, Moyobamba Vehicular traffic represents one of the main sources of noise pollution that generates high noise levels, according to the number, speed and type of vehicles, which can affect human health. The general objective was "To determine the linear regression model of noise behavior influenced by vehicular traffic in the Calvario neighborhood, Moyobamba". The project was carried out in the Calvario neighborhood of the city of Moyobamba, belonging to the district and province of the same name, in the department of San Martin. The execution period was 8 months from 4/29/2022. The sample consisted of 22 sampling points distributed in the urban area of the Calvario neighborhood. The quantification of vehicular traffic and the measurement of noise levels were carried out through direct observation using data collection cards as an instrument, the measurement time was 8 weeks over a period of 4 months and for the measurement of noise levels a sound level meter was also used as an instrument. In addition, the results of noise levels were compared with the standards established in Supreme Decree N° 085-2003-PCM and the simple linear regression statistic was used to determine the linear regression model of noise behavior influenced by vehicular traffic; descriptive statistics were also used to process and analyze the data with programs such as Excel and SPSS Statisstics. It was determined that the highest average vehicle flow is 1168.25 veh/hour in the morning and the lowest average vehicle flow is 5.58 veh/hour at night, where, in addition, the largest number of vehicles circulate on the main streets and avenues of the neighborhood. Likewise, the highest noise levels (82.18 and 81.13 dBA) are generated during daytime hours and the lowest noise levels (21.54 dBA) during nighttime hours. During daytime hours, 16, 11 and 2 sampling points exceed the EQSs for the residential, commercial and special protection zones, respectively, and during nighttime hours, 13 and 2 sampling points exceed the EQSs for the residential and special protection zones, respectively. Finally, in the two zones and times studied, high correlation coefficients were determined between the variables, with the linear regression model of noise behavior for the residential zone in daytime and nighttime hours LAeqT hour = 10.63 + 20.21 Log Qt and LAeqT hour = 27.08 + 13.37 Log Qt, respectively; and, in the mixed zone during daytime and nighttime hours LAeqT hour = -198.84 + 92.57 Log Qt and LAeqT hour = 27.08 + 13.37 * Log Qt, respectively. It is concluded with a confidence level of 95% that the linear regression models of the behavior of noise influenced by vehicular traffic in the Calvario neighborhood were adequate.
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