Cryptocurrency is widely recognized as an alternative method for paying and exchanging
currency instead of using classic coins or gold; thus, it has infiltrated almost in all financial …

The tourism industry is one of the economic sectors that is overgrowing throughout the
world. Accurate tourism demand forecasting is needed for proper strategic planning …

This paper introduced a new ensemble learning approach, based on evolutionary fuzzy
cognitive maps (FCMs), artificial neural networks (ANNs), and their hybrid structure (FCM …

Natural gas constitutes one of the most actively traded energy commodity with a significant
impact on many financial activities of the world. The accurate natural gas price prediction …

Extreme learning machines (ELMs) are efficient for classification, regression, and time series
prediction, as well as being a clear solution to backpropagation structures to determine …

Machine learning is enabling transformative changes in the tourism industry. Various
machine learning algorithms and models can detect patterns in huge amounts of data for the …

This paper proposes a new hybrid deep learning framework that combines search query
data, autoencoders (AE) and stacked long-short term memory (staked LSTM) to enhance the …

All the motivations of adaptive strategies in conditions of dynamic environmental changes
come down to how effectively they describe the situation. If the market segment and the …

The machine learning approach has been widely used in many areas of studies, including
the tourism sector. It can offer powerful estimation for prediction. With a growing number of …

В статье для изучения российского и международного опыта прогнозирования
туристских потоков с применением алгоритмов машинного обучения была …