Results 31 to 40 of about 517,907 (286)
Recent Advances in Energy Time Series Forecasting
Energies, 2017 This editorial summarizes the performance of the special issue entitled Energy Time Series Forecasting, which was published in MDPI’s Energies journal. The special issue took place in 2016 and accepted a total of 21 papers from twelve different countries.
Francisco Martínez-Álvarez +2 more
doaj +1 more source
Significance, 2005 Abstract As we go through life, everyone makes forecasts all the time, often without realising it. Sadly these forecasts are often (very) inaccurate. Chris Chatfield looks at the chequered history of forecasting and asks how we might do it better using time-series data, and what statistical techniques and models might help us.
openaire +1 more source
By dawn or dusk—how circadian timing rewrites bacterial infection outcomes
FEBS Letters, EarlyView.The circadian clock shapes immune function, yet its influence on infection outcomes is only beginning to be understood. This review highlights how circadian timing alters host responses to the bacterial pathogens Salmonella enterica, Listeria monocytogenes, and Streptococcus pneumoniae revealing that the effectiveness of immune defense depends not only
Devons Mo +2 more
wiley +1 more source
Improving Software Reliability Forecasting [PDF]
, 1996 This work investigates some methods for software reliability forecasting. A supermodel is presented as a suited tool for prediction of reliability in software project development.
Albeanu, Grigore +4 more
core +3 more sources
Time after time – circadian clocks through the lens of oscillator theory
FEBS Letters, EarlyView.Oscillator theory bridges physics and circadian biology. Damped oscillators require external drivers, while limit cycles emerge from delayed feedback and nonlinearities. Coupling enables tissue‐level coherence, and entrainment aligns internal clocks with environmental cues.
Marta del Olmo +2 more
wiley +1 more source
Predicting wind energy generation with recurrent neural networks [PDF]
, 2018 Decarbonizing the energy supply requires extensive use of renewable generation. Their intermittent nature requires to obtain accurate forecasts of future generation, at short, mid and long term.
Béjar Alonso, Javier +2 more
core +1 more source
Entanglement-Structured LSTM Boosts Chaotic Time Series Forecasting
Entropy, 2021 Traditional machine-learning methods are inefficient in capturing chaos in nonlinear dynamical systems, especially when the time difference Δt between consecutive steps is so large that the extracted time series looks apparently random.
Xiangyi Meng, Tong Yang
doaj +1 more source
FEBS Letters, EarlyView.Cryptochrome and PAS/LOV proteins play intricate roles in circadian clocks where they act as both sensors and mediators of protein–protein interactions. Their ubiquitous presence in signaling networks has positioned them as targets for small‐molecule therapeutics. This review provides a structural introduction to these protein families.
Eric D. Brinckman +2 more
wiley +1 more source
Forecasting growth with time series models [PDF]
, 1993 This paper compares the structure of three models for estimating future growth in a time series. It is shown that a regression model gives minimum weight to the last observed growth and maximum weight to the observed growth in the middle of the sample ...
Peña, Daniel
core +1 more source
Forecasting Time Series with VARMA Recursions on Graphs
, 2019 Graph-based techniques emerged as a choice to deal with the dimensionality issues in modeling multivariate time series. However, there is yet no complete understanding of how the underlying structure could be exploited to ease this task.
Isufi, Elvin +3 more
core +1 more source