This study proposes a new hybrid model that combines LSTM and BiLSTM neural networks
with GARCH type model forecasts using an ensemble approach to forecast volatility for one …

In biogeomechanics, which describes the mechanical responses to microbial-rock
interactions and its succeeding alterations, there is complexity in the estimation and …

This paper contributes to the ongoing debate on the nature and characteristics of the
volatility transmission channels of major crash events in international stock markets between …

Forecasting tourism demand in a timely manner is critical for ensuring the smooth operation
of the tourism industry. Over time, time series models have been widely applied to estimate …

Food choice motives (ie, mood, health, natural content, convenience, sensory appeal, price,
familiarities, ethical concerns, and weight control) have an important role in transforming the …

Abstract Gross Domestic Product (GDP) is significant for measuring the strength of national
and global economies in urban profiling areas. GDP is significant because it provides …

Accurate simulation of sea ice is critical for predictions of future Arctic sea ice loss, looming
climate change impacts, and more. A key feature in Arctic sea ice is the formation of melt …

In the contemporary landscape, fraud is a widespread challenge in today's financial
landscape, requiring innovative methods and technologies to detect and prevent losses from …

In this paper, RNN (Recurrent Neural Network) algorithm is used to conduct an in‐depth
analysis of HR strategic decision‐making and an HR strategic decision model is constructed …

Investment predicated on price trends stands as one of the most prevalent and efficacious
approaches, hinging on its capacity to accurately discern the price trajectory for each asset …