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Forecasting

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Hybrid deep learning models with multi-classification investor sentiment to forecast the prices of China's leading stocks.

PloS one
The prediction of stock prices has long been a captivating subject in academic research. This study aims to forecast the prices of prominent stocks in five key industries of the Chinese A-share market by leveraging the synergistic power of deep learn...

Forecasting water quality variable using deep learning and weighted averaging ensemble models.

Environmental science and pollution research international
Water quality variables, including chlorophyll-a (Chl-a), play a pivotal role in comprehending and evaluating the condition of aquatic ecosystems. Chl-a, a pigment present in diverse aquatic organisms, notably algae and cyanobacteria, serves as a val...

Deep learning framework for epidemiological forecasting: A study on COVID-19 cases and deaths in the Amazon state of ParĂ¡, Brazil.

PloS one
Modeling time series has been a particularly challenging aspect due to the need for constant adjustments in a rapidly changing environment, data uncertainty, dependencies between variables, volatile fluctuations, and the need to identify ideal hyperp...

Big data and artificial intelligence in cancer research.

Trends in cancer
The field of oncology has witnessed an extraordinary surge in the application of big data and artificial intelligence (AI). AI development has made multiscale and multimodal data fusion and analysis possible. A new era of extracting information from ...

Advances, challenges, and future research needs in machine learning-based crash prediction models: A systematic review.

Accident; analysis and prevention
Accurately modelling crashes, and predicting crash occurrence and associated severities are a prerequisite for devising countermeasures and developing effective road safety management strategies. To this end, crash prediction modelling using machine ...

Development and performance comparison of optimized machine learning-based regression models for predicting energy-related carbon dioxide emissions.

Environmental science and pollution research international
Accurate prediction of CO emissions for the countries has become a crucial task in decision-making processes for planning energy conversion and usage, supporting the design of effective emissions reduction strategies, and helping to achieve the goal ...

Deep learning precipitation prediction models combined with feature analysis.

Environmental science and pollution research international
Precise rainfall forecasting modeling assumes a pivotal role in water resource planning and management. Conducting a comprehensive analysis of the rainfall time series and making appropriate adjustments to the forecast model settings based on the cha...

Contextually enhanced ES-dRNN with dynamic attention for short-term load forecasting.

Neural networks : the official journal of the International Neural Network Society
In this paper, we propose a new short-term load forecasting (STLF) model based on contextually enhanced hybrid and hierarchical architecture combining exponential smoothing (ES) and a recurrent neural network (RNN). The model is composed of two simul...

A model to forecast the two-year variation of subjective wellbeing in the elderly population.

BMC medical informatics and decision making
BACKGROUND: The ageing global population presents significant public health challenges, especially in relation to the subjective wellbeing of the elderly. In this study, our aim was to investigate the potential for developing a model to forecast the ...