Development of new hybrid model of discrete wavelet decomposition and autoregressive integrated moving average (ARIMA) models in application to one month …

S Singh, KS Parmar, J Kumar, SJS Makkhan - Chaos, solitons & fractals, 2020 - Elsevier
Everywhere around the globe, the hot topic of discussion today is the ongoing and fast-
spreading coronavirus disease (COVID-19), which is caused by the severe acute respiratory …

Application of least square support vector machine and multivariate adaptive regression spline models in long term prediction of river water pollution

O Kisi, KS Parmar - Journal of Hydrology, 2016 - Elsevier
This study investigates the accuracy of least square support vector machine (LSSVM),
multivariate adaptive regression splines (MARS) and M5 model tree (M5Tree) in modeling …

Study of ARIMA and least square support vector machine (LS-SVM) models for the prediction of SARS-CoV-2 confirmed cases in the most affected countries

S Singh, KS Parmar, SJS Makkhan, J Kaur… - Chaos, Solitons & …, 2020 - Elsevier
Discussions about the recently identified deadly coronavirus disease (COVID-19) which
originated in Wuhan, China in December 2019 are common around the globe now. This is …

Long-term aerosol climatology over Indo-Gangetic Plain: Trend, prediction and potential source fields

M Kumar, KS Parmar, DB Kumar, A Mhawish… - Atmospheric …, 2018 - Elsevier
Long-term aerosol climatology is derived using Terra MODIS (Collection 6) enhanced Deep
Blue (DB) AOD retrieval algorithm to investigate decadal trend (2006–2015) in columnar …

ARIMA analysis of the effect of land surface coverage on PM10 concentrations in a high-altitude megacity

C Zafra, Y Ángel, E Torres - Atmospheric Pollution Research, 2017 - Elsevier
This paper uses ARIMA models for daily temporal analysis of the effect of land surface
coverage (LSC) on PM 10 concentrations in a high-altitude megacity. Bogota, the capital of …

Application Study of Comprehensive Forecasting Model Based on Entropy Weighting Method on Trend of PM2.5 Concentration in Guangzhou, China

D Liu, L Li - International journal of environmental research and …, 2015 - mdpi.com
For the issue of haze-fog, PM2. 5 is the main influence factor of haze-fog pollution in China.
The trend of PM2. 5 concentration was analyzed from a qualitative point of view based on …

Time series analysis of aerosol optical depth over New Delhi using Box–Jenkins ARIMA modeling approach

K Taneja, S Ahmad, K Ahmad, SD Attri - Atmospheric Pollution Research, 2016 - Elsevier
The present study focuses on the application of stochastic modeling technique in analyzing
the future trends of aerosol optical properties. For this, the Box–Jenkins ARIMA …

Modeling of air pollutants using least square support vector regression, multivariate adaptive regression spline, and M5 model tree models

O Kisi, KS Parmar, K Soni, V Demir - Air Quality, Atmosphere & Health, 2017 - Springer
This study investigates the applicability of three different soft computing methods, least
square support vector regression (LSSVR), multivariate adaptive regression splines …

Soft computing model coupled with statistical models to estimate future of stock market

S Singh, KS Parmar, J Kumar - Neural Computing and Applications, 2021 - Springer
Almost every organization around the globe is working with uncertainty due to inevitable
changes and growth in every sphere of life. These changes affect directly or indirectly the …

Modeling and spatial characterization of aerosols at Middle East AERONET stations

CM Anoruo, SNH Bukhari, OK Nwofor - Theoretical and Applied …, 2023 - Springer
In this paper, we employed an autoregressive integrated moving average (ARIMA) model to
simulate aerosol optical depth time series from the ground-based AErosol RObotic NETwork …