A time series is a sequence of time-ordered data, and it is generally used to describe how a
phenomenon evolves over time. Time series forecasting, estimating future values of time …

The dual-memristor hyperchaotic map has not yet received much attention and application,
and its complexity and flexibility deserve further improvement. To this end, a novel two …

The use of wavelet analysis contributes to better modeling for financial time series in the
sense of both frequency and time. In this study, S&P500 and NASDAQ data are separated …

Wind power prediction plays a critical role in the economic deployment of power systems
including wind farm. To improve the prediction accuracy of wind power, a chaotic wind …

Promoters are an important regulatory element in the genome that control gene expression,
and their abnormalities have been linked to various diseases. Therefore, accurately …

The mechanical condition prediction can realize the early warning of mechanical fault, which
is of great significance to the safe operation of high-voltage circuit breaker (HVCB) and the …

With the gradual transformation of energy industries around the world, the trend of industrial
reform led by clean energy has become increasingly apparent. As a critical link in the new …

Electricity generation in Brazil heavily depends on hydroelectric power, making it vulnerable
to fluctuations due to its reliance on weather patterns. Accurately forecasting water inflow …

Accurate bike-sharing demand prediction is crucial for bike allocation rebalancing and
station planning. In bike-sharing systems, the bike borrowing and returning behavior exhibit …

Speech emotion recognition (SER) is difficult since emotions are complex and dynamic
processes involving multiple dimensions and sub-dimensions. Feature extraction is a …