Multiple Regression and Big Data Analysis for Predictive Emission Monitoring Systems
نویسندگان
چکیده
Predictive Emission Monitoring Systems (PEMS) offer a cost-effective and environmentally friendly alternative to Continuous (CEMS) for monitoring pollution from industrial sources. Multiple regression is one of the fundamental statistical techniques describe relationship between dependent independent variables. This model can be effectively used develop PEMS, estimate amount emitted by sources, where fuel composition other process-related parameters are available. It often makes them sufficient predict emission discharge with acceptable accuracy. In cases PEMS accepted as an method CEMS, which use gas analyzers, they provide cost savings substantial benefits ongoing system support maintenance. The described mathematical concept based on matrix algebra representation in multiple involving precision arithmetic techniques. Challenging numerical examples big data analysis, investigated. Numerical illustrate computational accuracy efficiency analysis due increasing level. programming language C++ implementation. research development, including NOx emissions data, were obtained CEMS software installed petrochemical plant.
منابع مشابه
A Divided Regression Analysis for Big Data
Statistics is an important part in big data because many statistical methods are used for big data analysis. The aim of statistics is to estimate population using the sample extracted from the population, so statistics is to analyze not the population but the sample. But in big data environment, we can get the big data set closed to the population by the advanced computing systems such as cloud...
متن کاملMultiple Fuzzy Regression Model for Fuzzy Input-Output Data
A novel approach to the problem of regression modeling for fuzzy input-output data is introduced.In order to estimate the parameters of the model, a distance on the space of interval-valued quantities is employed.By minimizing the sum of squared errors, a class of regression models is derived based on the interval-valued data obtained from the $alpha$-level sets of fuzzy input-output data.Then,...
متن کاملBig Data Analytics and Now-casting: A Comprehensive Model for Eventuality of Forecasting and Predictive Policies of Policy-making Institutions
The ability of now-casting and eventuality is the most crucial and vital achievement of big data analytics in the area of policy-making. To recognize the trends and to render a real image of the current condition and alarming immediate indicators, the significance and the specific positions of big data in policy-making are undeniable. Moreover, the requirement for policy-making institutions to ...
متن کاملPredictive factors for infertility of women: an univariate and multivariate logistic regression analysis
Background and aims: Infertility is a major problem during reproductive age. Physical and psychological effects of infertility in women are problematic. The aim of this study was to determine the potential predictive factors of infertility, among women referring both public and private health centers in Ilam province, western Iran, in 2013. Methods: In this cross-sectional study, 1013 women re...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Applied mathematics
سال: 2023
ISSN: ['2152-7393', '2152-7385']
DOI: https://doi.org/10.4236/am.2023.145023