Results 91 to 100 of about 517,907 (286)

Survey of Transformer-based Time Series Forecasting Methods [PDF]

Jisuanji kexue
Time series forecasting,a critical technique for analyzing historical data to predict future trends,has been widely applied in fields such as finance and meteorology.However,traditional methods like the autoregressive moving average model and exponential
CHEN Jiajun, LIU Bo, LIN Weiwei, ZHENG Jianwen, XIE Jiachen
doaj   +1 more source

Mycobacterial cell division arrest and smooth‐to‐rough envelope transition using CRISPRi‐mediated genetic repression systems

FEBS Open Bio, EarlyView.
CRISPRI‐mediated gene silencing and phenotypic exploration in nontuberculous mycobacteria. In this Research Protocol, we describe approaches to control, monitor, and quantitatively assess CRISPRI‐mediated gene silencing in M. smegmatis and M. abscessus model organisms.
Vanessa Point, Wafaa Achache, Janïs Laudouze, Eliana Sepulveda Ramos, Mickaël Maziero, Céline Crauste, Stéphane Canaan, Pierre Santucci   +7 more
wiley   +1 more source

Ondaietas e previsão de séries de tempo: uma análise empírica

Economia Aplicada, 2003
This paper presents three case studies in time series forecasting. We try to compare the use of traditional ARIMA models with an alternative method that combines of ARIMA and Wavelets models. Two different approaches are applied.
Guilherme V. Homsy, Marcelo S. Portugal, Jorge P. Araujo   +2 more
doaj  

Nonstationary Functional Time Series Forecasting

Journal of Forecasting
ABSTRACTWe propose a nonstationary functional time series forecasting method with an application to age‐specific mortality rates observed over the years. The method begins by taking the first‐order differencing and estimates its long‐run covariance function.
Han Lin Shang, Yang Yang
openaire   +2 more sources

Enzymatic degradation of biopolymers in amorphous and molten states: mechanisms and applications

FEBS Open Bio, EarlyView.
This review explains how polymer morphology and thermal state shape enzymatic degradation pathways, comparing amorphous and molten biopolymer structures. By integrating structure–reactivity principles with insights from thermodynamics and enzyme engineering, it highlights mechanisms that enable efficient polymer breakdown.
Anđela Pustak, Aleksandra Maršavelski
wiley   +1 more source

Nonparametric modeling and forecasting electricity demand: an empirical study [PDF]

This paper uses half-hourly electricity demand data in South Australia as an empirical study of nonparametric modeling and forecasting methods for prediction from half-hour ahead to one year ahead.
Han Lin Shang
core  

Implementation of bagging in time series forecasting

Российский технологический журнал
Objectives. The purpose of the article is to build different models of bagging, to compare the accuracy of their forecasts for the test period against standard models, and to draw conclusions about the possibility of further use of the bagging technique ...
Ia. V. Gramovich, D. Yu. Musatov, D. A. Petrusevich   +2 more
doaj   +1 more source

Tumor‐stromal crosstalk and macrophage enrichment are associated with chemotherapy response in bladder cancer

FEBS Open Bio, EarlyView.
Chemoresistance in bladder cancer: Macrophage recruitment associated with CXCL1, CXCL5 and CXCL8 expression is characteristic of Gemcitabine/Cisplatin (Gem/Cis) Non‐Responder tumors (right side) while Responder tumors did not show substantial tumor‐stromal crosstalk (left side). All biological icons are attributed to Bioicons: carcinoma, cancerous‐cell‐
Sophie Leypold, Janik Riese, Lancelot Seillier, Mark Kühnel, Julia Pannhausen, Charlotte O. J. Fröhlich, Christian Martin, Peter Boor, Matthias Saar, Danny D. Jonigk, Nadine T. Gaisa, Michael Rose   +11 more
wiley   +1 more source

Optimal Forecasting of Noncausal Autoregressive Time Series [PDF]

In this paper, we propose a simulation-based method for computing point and density forecasts for univariate noncausal and non-Gaussian autoregressive processes.
Lanne, Markku, Luoto, Jani, Saikkonen, Pentti   +2 more
core   +1 more source

Time series forecasting using the normalization model

Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï
Empirical constructions of time series models based on the reduction of initial data to normally distributed values have been proposed. The goal of a normalization method is to construct an optimal forecast that is linear for the updated data, and the ...
Viktor Bondarenko, Valeriia Bondarenko
doaj   +1 more source