The main goal of this research paper is to apply a deep neural network model for time series
forecasting of environmental variables. Accurate forecasting of snow cover and NDVI are …

This review article offers a comprehensive analysis of current developments in the
application of machine learning for cancer diagnostic systems. The effectiveness of machine …

Because of the complexity, nonlinearity, and volatility, stock market forecasting is either
highly difficult or yields very unsatisfactory outcomes when utilizing traditional time series or …

In power fingerprint identification, feature information is insufficient when using a single
feature to identify equipment, and small load data of specific customers, difficult to meet the …

An early brain tumor diagnosis is crucial for effective and proactive treatment, which
improves the patient's survival rate. In this paper, we propose a novel Deep Convolutional …

Agriculture is critical for a country's population growth and economic expansion. In Saudi
Arabia (SA), agriculture relies on groundwater, seasonal water, desalinated water, and …

Groundwater nitrate contamination is a significant concern in agricultural watersheds
worldwide with it becoming a more pervasive problem in the last three decades. Models are …

Internet of things (IoT) devices' evolution and growth have boosted system efficiency,
reduced human labour, and improved operational efficiency; however, IoT devices pose …

Hyperspectral images can easily discriminate different materials due to their fine spectral
resolution. However, obtaining a hyperspectral image (HSI) with a high spatial resolution is …

The specific characteristics of remote sensing images, such as large directional variations,
large target sizes, and dense target distributions, make target detection a challenging task …