Predicting THM concentration in treated water with highly correlated data
نویسندگان
چکیده
منابع مشابه
Predicting Urban Water Quality with Ubiquitous Data
Urban water quality is of great importance to our daily lives. Prediction of urban water quality help control water pollution and protect human health. However, predicting the urban water quality is a challenging task since the water quality varies in urban spaces non-linearly and depends on multiple factors, such as meteorology, water usage patterns, and land uses. In this work, we forecast th...
متن کاملPredicting ground water nitrate concentration from land use.
Ground water nitrate concentrations on Nantucket Island, Massachusetts, were analyzed to assess the effects of land use on ground water quality. Exploratory data analysis was applied to historic ground water nitrate concentrations to determine spatial and temporal trends. Maximum likelihood Tobit and logistic regression analyses of explanatory variables that characterize land use within a 1000-...
متن کاملBayesian forecasting with highly correlated predictors
This paper considers Bayesian variable selection in regressions with a large number of possibly highly correlated macroeconomic predictors. I show that by acknowledging the correlation structure in the predictors can improve forecasts over existing popular Bayesian variable selection algorithms.
متن کاملSparse regression with highly correlated predictors
We consider a linear regression y = Xβ + u where X ∈ Rn×p, p n, and β is s−sparse. Motivated by examples in financial and economic data, we consider the situation where X has highly correlated and clustered columns. To perform sparse recovery in this setting, we introduce the clustering removal algorithm (CRA), that seeks to decrease the correlation in X by removing the cluster structure withou...
متن کاملNoise Power Spectral Density Estimation on Highly Correlated Data
In this contribution the Minimum Statistics noise power spectral density estimator [1] is revised for the particular case of highly correlated data which is observed for example when framewise processing with considerable frame overlap is performed. For this special case the noise power estimator tends to underestimate the noise power. We identify the variance estimator in the Minimum Statistic...
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: Mathematical and Computer Modelling
سال: 1988
ISSN: 0895-7177
DOI: 10.1016/0895-7177(88)90658-9