Beware of r2 even for test datasets: Using the latest measured y‐values (r2LM) in time series data analysis
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Chemometrics"
DOI: 10.1002/cem.3093
Abstract: The determination coefficient of a test dataset, r2, is calculated and used to compare the performance of adaptive soft sensors and discuss the possibility of their practical use. However, soft sensors that give very high… read more here.
Keywords: time series; values r2lm; latest measured; soft sensors ... See more keywords
Simple statistical models can be sufficient for testing hypotheses with population time‐series data
Sign Up to like & getrecommendations! Published in 2022 at "Ecology and Evolution"
DOI: 10.1002/ece3.9339
Abstract: Abstract Time‐series data offer wide‐ranging opportunities to test hypotheses about the physical and biological factors that influence species abundances. Although sophisticated models have been developed and applied to analyze abundance time series, they require information… read more here.
Keywords: time; time series; testing hypotheses; model ... See more keywords
Evaluating consumptive and nonconsumptive predator effects on prey density using field time-series data.
Sign Up to like & getrecommendations! Published in 2019 at "Ecology"
DOI: 10.1002/ecy.2583
Abstract: Determining the degree to which predation affects prey abundance in natural communities constitutes a key goal of ecological research. Predators can affect prey through both consumptive effects (CEs) and nonconsumptive effects (NCEs), although the contributions… read more here.
Keywords: series data; predator effects; time series; density ... See more keywords
Multihorizons transfer strategy for continuous online prediction of time‐series data in complex systems
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22900
Abstract: The sustainability online prediction is of great significance for higher horizon time‐series prediction in the future, and it embodies higher application value in equipment fault prediction and health management. However, compared with one‐step time‐series prediction,… read more here.
Keywords: online prediction; time; time series; prediction ... See more keywords
Variational Approach for Learning Markov Processes from Time Series Data
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Nonlinear Science"
DOI: 10.1007/s00332-019-09567-y
Abstract: Inference, prediction, and control of complex dynamical systems from time series is important in many areas, including financial markets, power grid management, climate and weather modeling, or molecular dynamics. The analysis of such highly nonlinear… read more here.
Keywords: series data; time; time series; markov processes ... See more keywords
Classification for Time Series Data. An Unsupervised Approach Based on Reduction of Dimensionality
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Classification"
DOI: 10.1007/s00357-019-9308-z
Abstract: In this work we use a novel methodology for the classification of time series data, through a natural, unsupervised data learning process. This strategy is based on the sequential use of Multiple Factor Analysis and… read more here.
Keywords: series data; time; time series; classification time ... See more keywords
The Swiss army knife of time series data mining: ten useful things you can do with the matrix profile and ten lines of code
Sign Up to like & getrecommendations! Published in 2020 at "Data Mining and Knowledge Discovery"
DOI: 10.1007/s10618-019-00668-6
Abstract: The recently introduced data structure, the Matrix Profile, annotates a time series by recording the location of and distance to the nearest neighbor of every subsequence. This information trivially provides answers to queries for both… read more here.
Keywords: data mining; matrix profile; time series; time ... See more keywords
Building FAIR Functionality: Annotating Events in Time Series Data Using Hierarchical Event Descriptors (HED).
Sign Up to like & getrecommendations! Published in 2021 at "Neuroinformatics"
DOI: 10.1007/s12021-021-09537-4
Abstract: Human electrophysiological and related time series data are often acquired in complex, event-rich environments. However, the resulting recorded brain or other dynamics are often interpreted in relation to more sparsely recorded or subsequently-noted events. Currently… read more here.
Keywords: time series; hierarchical event; event; series data ... See more keywords
BiLSTM model based on multivariate time series data in multiple field for forecasting trading area
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Ambient Intelligence and Humanized Computing"
DOI: 10.1007/s12652-019-01398-9
Abstract: An artificial neural network-based model is widely used for analyzing and predicting multivariate time series data. However, the study on the analysis and prediction of multivariate time series data in multiple fields has limitations in… read more here.
Keywords: series data; time; time series; model ... See more keywords
A Novel Moving Average Forecasting Approach Using Fuzzy Time Series Data Set
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Control, Automation and Electrical Systems"
DOI: 10.1007/s40313-019-00467-w
Abstract: In this study, we develop a novel moving average forecasting approach based on fuzzy time series data set. The main objective of applying this moving average approach in develop method is to provide better results… read more here.
Keywords: fuzzy time; moving average; series data; time series ... See more keywords
Robust qualitative estimation of time-varying contact rates in uncertain epidemics.
Sign Up to like & getrecommendations! Published in 2018 at "Epidemics"
DOI: 10.1016/j.epidem.2018.03.001
Abstract: We will inevitably face new epidemics where the lack of long time-series data and the uncertainty about the outbreak dynamics make difficult to obtain quantitative predictions. Here we present an algorithm to qualitatively infer time-varying… read more here.
Keywords: time series; time varying; time; varying contact ... See more keywords