Effective selection of climate predictors is a fundamental aspect of climate modeling
research. Predictor Screening (PS) plays a crucial role in identifying regional climate drivers …

Determination of ripeness represented by firmness measured during storage is important to
guide the supply chain management of avocados. A machine vision system devised with a …

Differential Credibility Assessment for Statistical Downscaling in: Journal of Applied
Meteorology and Climatology Volume 59 Issue 8 (2020) Jump to Content Jump to Main …

Statistical Downscaling (SD) is a model that uses satellite data from General Circulation
Models (GCM), which in climatology are very useful in predicting climate for the next few …

Background P300-based brain-computer interfaces provide communication pathways
without the need for muscle activity by recognizing electrical signals from the brain. The …

Problems of high correlated data in a linear regression can not be handled directly by
standard methods of parameter estimation such as the least squares (LS). Lasso technique …

Rainfall prediction is necessary since extreme rainfall has a big impact to the environment. A
method commonly used to predict rainfall is statistical downscaling. This technique develops …

Tuberculosis is the deadliest infectious disease in Indonesia, and West Java is a province
with the largest number of tuberculosis cases in Indonesia. This research was conducted to …

Rainfall data are more than or equal zero and can be represented using Gamma
distribution. In statistical downscaling the local scale rainfall data are used as the response …

Skillful long-lead climate forecast is of great importance in managing large water systems
and can be made possible using teleconnections between regional climate and large-scale …