Results 71 to 80 of about 10,511 (262)
Network traffic prediction model based on linear and nonlinear model combination
ETRI JournalWe propose a network traffic prediction model based on linear and nonlinear model combination. Network traffic is modeled by an autoregressive moving average model, and the error between the measured and predicted network traffic values is obtained. Then,
Lian Lian
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Short-term Gini coefficient estimation using nonlinear autoregressive multilayer perceptron model
HeliyonPoverty, an intricate global challenge influenced by economic, political, and social elements, is characterized by a deficiency in crucial resources, necessitating collective efforts towards its mitigation as embodied in the United Nations' Sustainable ...
Megat Syahirul Amin Megat Ali +7 more
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Langmuir adsortion isotherm with regular and irregular autoregressive error structures
Acta Scientiarum: Technology, 2018 The Langmuir isotherm is a nonlinear regression model, being one of the most applied in adsorption studies. In this type of study, the data are collected over time, which can provide correlated errors; in addition, the collection is not always done in an
Cristiane Costa da Fonseca Cintra +2 more
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The Impact of Resource Endowment and Digital Transformation on the Efficiency of Energy Transition
Energy Science &Engineering, EarlyView.Resource endowment has a significant positive direct effect and a stronger spatial spillover effect on ETE, while digital transformation can improve local efficiency but has some negative spillover effects on neighboring regions. ABSTRACT In contemporary society, improving energy transition efficiency (ETE) has become a necessary measure to ensure the ...
Junding Yang +5 more
wiley +1 more source
Nonlinear control study on aircraft engine using a generalized minimum variance approach
Advances in Mechanical Engineering, 2016 With the requirements of the advanced propulsion systems for aircraft control performance increasing, it has attracted the attention to design more efficient controller that is based on the nonlinear model over the flight envelope directly.
Bing Yu, Yang Gao, Jiqiang Wang
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Energy Science &Engineering, EarlyView.This study analyzes energy consumption and economic growth across 39 Sub‐Saharan African countries using a PVAR model. Findings reveal that non‐renewable energy and labor force growth stimulate economic growth, while renewable energy does not stimulate economic growth in the short run.
Amadou Cham +4 more
wiley +1 more source
Ensemble Deep Learning–Based Wind Power Forecasting With Self‐Adaptive Osprey Optimization Algorithm
Energy Science &Engineering, EarlyView.Design of Self‐Adaptive Osprey (SAO) algorithm: The novel SAO algorithm is designed by integrating the exploration capability of the conventional Osprey algorithm by including the self‐adaptiveness for enhancing the convergence rate. Ensemble Deep Learning for wind power forecasting: The wind forecasting is employed using the proposed Ensemble learning
Johncy Bai Johnson +3 more
wiley +1 more source
Asymmetric smooth transition autoregressive model in forecasting finance rate on consumer installment loans at commercial banks [PDF]
Journal of Mahani Mathematical ResearchEconomic and finance time series are typically asymmetric and are expected to be modeled using asymmetric nonlinear time series models. The logistic smooth transition autoregressive, LSTAR, model which is an asymmetric type of the smooth transition ...
Sedigheh Zamani Mehreyan
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Energy Science &Engineering, EarlyView.An AI‐driven CNN–LSTM forecasting framework is integrated with HOMER Pro to optimally design a grid‐connected PV–wind–BESS microgrid for a rural school in Bangladesh, achieving 91.7% renewable penetration, low energy cost (0.0397 USD/kWh), and an 81.5% reduction in CO2 emissions. ABSTRACT Hybrid renewable microgrid planning in HOMER Pro often relies on
Robiul Khan +5 more
wiley +1 more source
Journal of Forecasting, EarlyView.ABSTRACT We study the accuracy of a variety of parametric price duration‐based realized variance estimators constructed via various financial duration models and compare their forecasting performance with the performance of various nonparametric return‐based realized variance estimators.
Björn Schulte‐Tillmann +2 more
wiley +1 more source