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Deep random vector functional link transformer network with multiple output layers for significant wave height forecasting
Published 2025“…<p>Accurate control of wave energy devices relies heavily on precise forecasts of wave heights, yet the dynamic and fluctuating nature of historical wave data presents significant challenges to achieving this precision. …”
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Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series
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Forecasting Emerging Stock Market Crashes via Machine Learning
Published 2023Get full text
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National-level and state-level prevalence of overweight and obesity among children, adolescents, and adults in the USA, 1990–2021, and forecasts up to 2050
Published 2024“…We estimated the prevalence of overweight and obesity from 1990 to 2021 with forecasts to 2050 for children and adolescents (aged 5–24 years) and adults (aged ≥25 years) at the national level. …”
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A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption
Published 2019“…The proposed approach’s significance has two folds. Firstly, it is completely flexible. …”
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Randomized Deep Hopfield Network with Multiple Output Layers for Volatility Time Series Forecasting
Published 2025“…However, the inherent complexity and irregular variations in volatility time series data present significant challenges for accurate modeling. This study proposes a novel ensemble deep randomized Hopfield network (edRHN) for volatility forecasting. …”
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Loan guarantee, management earnings forecasts and cost of debt: evidence from Chinese manufacturing firms
Published 2024“…This study investigates the relationship between loan guarantees and the firm’s cost of debt and the moderating effect of management earnings forecasts. We find that loan guarantees have a significant negative relationship with the firm’s cost of debt. …”
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Recurrent ensemble random vector functional link neural network for financial time series forecasting
Published 2024“…However, the non-stationary and non-linear characteristics inherent in time series data pose significant challenges when accurately predicting future forecasts. …”
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Decomposition-based wind power forecasting models and their boundary issue: An in-depth review and comprehensive discussion on potential solutions
Published 2022“…<p>Recently, numerous forecasting models have been reported in the wind power forecasting field, aiming for reliable integration of renewable energy into the electric grid. …”
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Internet Searches for Medical Symptoms Before Seeking Information on 12-Step Addiction Treatment Programs: A Web-Search Log Analysis
Published 2019“…Specifically, symptom queries were first determined to be significantly predictive of subsequent 12-step queries if the probability of querying a medical symptom by those who later sought information about the 12-step program exceeded the probability of that same query being made by a comparison group of all other Bing users in the United States. …”
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Electric Vehicles Charging Station Load Forecasting Integration With Renewable Energy Using Novel Deep EfficientBiLSTMNet
Published 2025“…<p dir="ltr">The exponential increase in the adoption of Electric Vehicles (EVs) presents significant problems to the stability of the power grid. …”
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Morphological changes in amblyopic eyes in choriocapillaris and Sattler’s layer in comparison to healthy eyes, and in retinal nerve fiber layer in comparison to fellow eyes through...
Published 2021“…Results The method of measuring reflectivity is good to excellent reliability for all regions of interest except the fourth. The mean reflectivity of the choriocapillaris and Sattler’s layer in amblyopic eyes were significantly lower than in healthy eyes (p = 0.003 and p = 0.008 respectively). …”
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National-level and state-level prevalence of overweight and obesity among children, adolescents, and adults in the USA, 1990–2021, and forecasts up to 2050
Published 2024“…We estimated the prevalence of overweight and obesity from 1990 to 2021 with forecasts to 2050 for children and adolescents (aged 5–24 years) and adults (aged ≥25 years) at the national level. …”
Get full text
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Get full text
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Heteroscedastic ensemble deep random vector functional link neural network with multiple output layers for High Frequency Volatility Forecasting and Risk Assessment
Published 2025“…However, the dynamic nature and significant variability in financial <u>time series</u> data pose substantial challenges to achieving these forecasts. …”
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Non-Linear Programming-Based Energy Management for a Wind Farm Coupled with Pumped Hydro Storage System
Published 2022“…A random forest (RF) method is used to perform the power forecasting after the extraction of the weather data features using a kernel principal component analysis (KPCA) technique. …”
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Low Transportation Emission Analysis and Projection Using LEAP: The Case of Qatar
Published 2023“…This is especially true for road transportation, one of Qatar’s most significant sources of air pollution. To address this research gap, this study provides an invaluable resource for policymakers as it is the first to quantify the current and forecast future transport emissions. …”