This study presents a quantum photonic approach to time-series forecasting, enhancing prediction accuracy through multiphoton ...

Artificial intelligence is becoming a game changer in Missoula’s real estate scene, from forecasting home prices to optimizing rental performance. Local housing data shows a low sales vacancy rate, ...

Artificial intelligence (AI) is emerging as a powerful tool to predict food consumption patterns and guide policy decisions, ...

Combining machine learning and feature selection, this research accurately predicts aluminum levels in marine environments, ...

A new satellite-based analytical framework enables accurate estimation of crop sowing and emergence dates at the field scale. By integrating daily ...

Precise stock market prediction remains a continual challenge because to the unpredictable, variable, and non-linear nature of financial time series data. Conventional models such as ARIMA and SVR ...

A machine learning-based model for student grade prediction employs the above-stated data, the student's current performance, and variables like attendance, study hours, homework submission, and sleep ...

Based on the composite ranking methodology that considers all criteria (AIC, BIC, SSE, RMSE), the Linear model is selected as the best-performing model. The Linear model demonstrates superior ...

A Flask-based REST API for managing personal finances with SQLite database, statistical analysis, and income forecasting using linear regression. pfm_project/ ├── api/ │ ├── __init__.py │ └── ...

ABSTRACT: Nowadays, understanding and predicting revenue trends is highly competitive, in the food and beverage industry. It can be difficult to determine which aspects of everyday operations have the ...

ABSTRACT: Nowadays, understanding and predicting revenue trends is highly competitive, in the food and beverage industry. It can be difficult to determine which aspects of everyday operations have the ...