Industrial time-series modeling via adapted receptive field temporal convolution networks integrating regularly updated multi-region operations based on PCA
Sign Up to like & getrecommendations! Published in 2020 at "Chemical Engineering Science"
DOI: 10.1016/j.ces.2020.115956
Abstract: Abstract Deep learning methods, especially the RNN based approaches, have been applied to the industrial time-series modeling these years successfully. However, the RNN based methods cannot overcome the enormous amount of iterative calculation. Traditional CNN… read more here.
Keywords: time series; regularly updated; method; series modeling ... See more keywords
SEM Based CARMA Time Series Modeling for Arbitrary N
Sign Up to like & getrecommendations! Published in 2018 at "Multivariate Behavioral Research"
DOI: 10.1080/00273171.2017.1383224
Abstract: ABSTRACT This article explains in detail the state space specification and estimation of first and higher-order autoregressive moving-average models in continuous time (CARMA) in an extended structural equation modeling (SEM) context for N = 1… read more here.
Keywords: time series; carma time; time; based carma ... See more keywords
Seasonal time-series modeling and forecasting of monthly mean temperature for decision making in the Kurdistan Region of Iraq
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Statistical Theory and Practice"
DOI: 10.1080/15598608.2017.1292484
Abstract: A generalized structural time-series modeling framework was used to analyze the monthly records of mean temperature, one of the most important environmental parameters, using classical stochastic processes. In this article we are using the SARIMA… read more here.
Keywords: temperature; time series; monthly mean; mean temperature ... See more keywords
Time Series Modeling for Dynamic Thermal Rating of Overhead Lines
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Power Systems"
DOI: 10.1109/tpwrs.2016.2596285
Abstract: Dynamic thermal rating (DTR) is more accurate and can better utilize the transmission/distribution capacity of an electric power system compared to static thermal rating. It is beneficial to integrate DTR into power system planning problems… read more here.
Keywords: time series; dtr; dynamic thermal; series modeling ... See more keywords
Time series modeling of pathogen-specific disease probabilities with subsampled data.
Sign Up to like & getrecommendations! Published in 2017 at "Biometrics"
DOI: 10.1111/biom.12560
Abstract: Many diseases arise due to exposure to one of multiple possible pathogens. We consider the situation in which disease counts are available over time from a study region, along with a measure of clinical disease… read more here.
Keywords: time series; time; disease; modeling pathogen ... See more keywords
Applying time series modeling to assess the dynamics and forecast monthly reports of abuse, neglect and/or exploitation involving a vulnerable adult
Sign Up to like & getrecommendations! Published in 2020 at "Archives of Public Health"
DOI: 10.1186/s13690-020-00431-0
Abstract: Background Application of time series modeling to predict reports related to maltreatment of vulnerable adults can be helpful for efficient early planning and resource allocation to handle a high volume of investigations. The goal of… read more here.
Keywords: adult; time series; time; series modeling ... See more keywords
Pooled Time Series Modeling Reveals Smoking Habit Memory Pattern
Sign Up to like & getrecommendations! Published in 2020 at "Frontiers in Psychiatry"
DOI: 10.3389/fpsyt.2020.00049
Abstract: Smoking is a habit that is hard to break because nicotine is highly addictive and smoking behavior is strongly linked to multiple daily activities and routines. Here, we explored the effect of gender, age, day… read more here.
Keywords: time series; smoking habit; series modeling; pooled time ... See more keywords