Results 41 to 50 of about 10,511 (262)
Integrating Deep Learning into Semiparametric Network Vector AutoRegressive Models
MathematicsNetwork vector AutoRegressive models play a vital role in multivariate time series analysis. However, previous research in the classic Network vector AutoRegressive (NAR) model is limited to strict assumptions of linearity and time-invariance of node ...
Yiming Tang +3 more
doaj +1 more source
Neural Information Processing and Time‐Series Prediction with Only Two Dynamical Memristors
Advanced Electronic Materials, EarlyView.The present study demonstrates how simple circuits with only two memristive devices are utilized to perform high complexity temporal information processing tasks, like neural spike detection in noisy environment, or time‐series prediction. This circuit simplicity is enabled by the dynamical complexity of the memristive devices, i.e.
Dániel Molnár +12 more
wiley +1 more source
Identification of vector autoregressive models with nonlinear contemporaneous structure
Journal of Economic Dynamics and Control, 2023 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Francesco Cordoni +2 more
openaire +4 more sources
Advanced Electronic Materials, EarlyView.Physical reservoir computing (PRC) based on spin wave interference has demonstrated high computational performance, yet room for improvement remains. In this study, we fabricated this concept PRC with eight detectors and evaluated the impact of the number of detectors using a chaotic time series prediction task.
Sota Hikasa +6 more
wiley +1 more source
Evaluation of Combined ARMA-ARCH and BL-ARCH models in Modeling Lake Urmia water level [PDF]
علوم و مهندسی آبیاری, 2017 Many nonlinear models have been developed based on the mean errors modeling. However, the non-linear models with Autoregressive conditional heteoscedasticity are based on variance modeling. These models are combined with linear models, partly to increase
Mohammad Nazeri Tahrudi +3 more
doaj +1 more source
The Relationship Between Interest Rates and Agricultural Commodity Price Dynamics
Agribusiness, EarlyView.ABSTRACT The U.S. Federal Reserve has undertaken several interest rate interventions in the past decade. This study explores the relationship between U.S. corn and soybean prices and Federal Reserve monetary policy interventions, in the short and long run.
Zhining Sun, Ani L. Katchova
wiley +1 more source
Time-series clustering and forecasting household electricity demand using smart meter data
Energy Reports, 2023 This study forecasts electricity consumption in a smart grid environment. We present a bottom-up prediction method using a combination of forecasting values based on time-series clustering using advanced metering infrastructure (AMI) data, one of the ...
Hyojeoung Kim, Sujin Park, Sahm Kim
doaj +1 more source
Modeling nonlinear processes with generalized autoregressions
Applied Mathematics Letters, 1990 AbstractA general procedure for modeling stochastic, nonlinear, dynamic process from time series data is proposed. The approach represents a natural generalization of linear autoregressions. The derivation of a state space representation from the resulting difference-equation model is discussed.
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Price Transmission During Promotions: A Case Study of Spanish Milk Brands
Agribusiness, EarlyView.ABSTRACT Price promotion is the marketing tool typically used by retail brands to boost sales and gain market share. In this paper, we intend to investigate the price transmission mechanism among competitive brands in Spain when price reductions that are associated with price promotions take place.
Yasmine Bedoui +2 more
wiley +1 more source
IEEE Access, 2021 An accurate state of charge (SOC) estimation depends on an accurate battery model. The influence of nonlinear and unstable interference factors makes the accurate SOC estimation difficult.
Qiao Wang +4 more
doaj +1 more source