Prediction of traffic noise induced annoyance: A two-staged SEM-Artificial Neural Network approach

Das, Chidananda Prasad; Swain, Bijay Kumar; Goswami, Shreerup; Das, Mira

doi:10.1016/j.trd.2021.103055

Cited by 23 publications

(18 citation statements)

References 100 publications

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“…Table 12 reveals that both gender (p = 0.001) and marital status (p = 0.001) has an association with anxiety of the noise pollution (Table 12). Gender is not a significant element in the influence of noise concern, according to certain studies [5,85]. Similar results also depicted in the present study.…”

Section: Community Responsessupporting

confidence: 92%

“…There was also a link between the individuals' age and sleep problems (p = 0.046). It was also said that age is not a significant factor when it comes to the effects of noise exposure [5,80]. Increased parent-reported sleep issues were identified in the few studies that looked at the link between noise and child/adolescent sleep [23,82].…”

Section: Community Responsesmentioning

confidence: 99%

“…Many studies also reported that there is a corelation between noise and health problems like headache, irritability etc. [5][6][7]. The main source of noise pollution is vehicular traffic noise or road traffic noise, as reported by many studies [3,[8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

“…The main source of noise pollution is vehicular traffic noise or road traffic noise, as reported by many studies [3,[8][9][10][11][12]. Increased noise exposure is known to produce annoyance [5,13,14], headaches [15][16][17][18], diabetes [19], irritability [20], sleep disturbances [21][22][23][24][25][26], hypertension [27][28][29][30], and problem in blood pressure [31]. Presently, it is a global problem [32].…”

Section: Introductionmentioning

confidence: 99%

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Impact of Noise Pollution during Covid-19: A Case Study of Balasore, Odisha

Swain¹,

Das²,

Goswami³

2023

Noise Control

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Activities such as development of industrialisation, urbanisation is a part of our life in the present scenario. During this phase we face a lot of health issues due to noise pollution. Growing of vehicle traffic is one of the major causes towards noise pollution and it affects significantly on the environment. The impact of such pollution had been assessed in 20 major squares (Commercial, residential and silence area) of the Balasore town during and after lockdown imposition of Covid-19. During lockdown period, the noise level of the town was within the permissible limit set by CPCB while before and after lockdown period it was beyond the permissible limit. The demographics and psychophysiological (annoyance, sleeping problem, tiredness, headache, and depression) responses of the participants were collected using standard questionnaires. It was also observed that there were better health conditions among the public (150 participated in the questionnaire) during the lockdown period, then before and after the lockdown phase. It was revealed that socio-demographic factors have no effects on the annoyance level.

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Section: Community Responsessupporting

confidence: 92%

Section: Community Responsesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Impact of Noise Pollution during Covid-19: A Case Study of Balasore, Odisha

Swain¹,

Das²,

Goswami³

2023

Noise Control

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“…III. RMSE: RMSE is the standard deviation of the predicted errors as its function is as follows (Das et al, 2021):…”

Section: Data Validationmentioning

confidence: 99%

Modeling of COVID‐19 death rate using various air pollutants: A multiple linear regression approach

Teja

Laskar

Mozumder

2023

Environmental Quality Mgmt

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Air pollution is a significant health risk, especially for vulnerable populations such as children, people with chronic illnesses, the elderly, and the economically and socially disadvantaged. Furthermore, air pollution has enormous social costs that we all bear in the form of premature deaths, low productivity, sick leave, and other strains on the healthcare system. The primary sources of air pollution are traffic, home fires, and industry. Measuring NO2 levels in air pollution reveals the extent of pollution caused by traffic, particularly diesel vehicles, which are the primary source of NO2. COVID‐19 rates are rising in areas with high levels of air pollution, according to mounting evidence. Toxic contaminants can make people more susceptible to COVID‐19. The causal relationship between air pollution and COVID‐19 cases has yet to be established, but experts warn that long‐term exposure will undoubtedly make people more susceptible to lung infections. Air pollution has been linked to an increase in cancer, heart disease, stroke, diabetes, asthma, and other comorbidities by inducing cellular damage and inflammation throughout the body. All of these factors increase the risk of death in COVID‐19 patients. As a result, air quality parameters must be predicted and monitored. To predict results, this study proposes a statistical‐based machine learning approach. Using multiple linear regression (MLR), Decision Tree (D.T.), and Random Forest (R.F.), the experimental results achieved 80%, 73%, and 65% accuracy on the dataset, respectively.

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Prediction of traffic noise induced annoyance of vendors through noise indices using structural equation modeling: Artificial neural network model

Das

Goswami

Das

2022

Environmental Quality Mgmt

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Urbanization and population growth, as well as the movement of diverse vehicles on urban roadways, all contribute to excessive noise in the urban acoustic environment.Annoyance, cardiovascular disease, dementia, hypertension, stress, sleeping problem, irritation, hair-fall, headache, are the most common reported problems due to traffic noise exposure. The "Structural Equation Modeling-Artificial Neural Network Model" was used in the current study to predict traffic noise induced annoyance among 100 vendors whose shops are located from Khandagiri to Baramunda along the National Highway 16 of the smart city Bhubaneswar Odisha. Due to the movement of large number of heavy vehicles as well as medium and light weight vehicles, these roadways remain noisy throughout the day. Moreover, the annoyance questionnaire was developed in compliance with ISO/TS 15666 criteria for assessing annoyance level.The combination of SEM and ANN is rarely seen in acoustics, especially in noise studies. However, in this study, both SEM and ANN are used to predict annoyance using various noise indices. Moreover, the SEM model revealed a significant association between "Equivalent Noise Level" (Leq) and annoyance (p-value = 0.031), "Minimum Noise Level" (LMin) and annoyance (p-value = 0.049), "Background Noise Level" (L 90 ) and annoyance (p-value = 0.047), "Noise Pollution Level" (NPL) and annoyance

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Prediction of traffic noise induced annoyance: A two-staged SEM-Artificial Neural Network approach

Cited by 23 publications

References 100 publications

Impact of Noise Pollution during Covid-19: A Case Study of Balasore, Odisha

Impact of Noise Pollution during Covid-19: A Case Study of Balasore, Odisha

Modeling of COVID‐19 death rate using various air pollutants: A multiple linear regression approach

Prediction of traffic noise induced annoyance of vendors through noise indices using structural equation modeling: Artificial neural network model

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