This research aims to study and assess state-of-the-art physics-informed neural networks
(PINNs) from different researchers' perspectives. The PRISMA framework was used for a …

Modern agriculture incorporated a portfolio of technologies to meet the current demand for
agricultural food production, in terms of both quality and quantity. In this technology-driven …

This work addresses the intricate task of predicting the prices of diverse financial assets,
including stocks, indices, and cryptocurrencies, each exhibiting distinct characteristics and …

Computer vision, a subfield of AI, specifically deals with allowing computers to construe and
understand visual information from the world, often through digital images or videos. It is …

The soil plays a vital role in agriculture, and soil testing serves as the initial step in
determining the optimal nutrient levels for cultivating specific crops. Machine learning (ML) …

This study explores the potential application of deep learning techniques in stock market
prediction and investment decision-making. The authors used multi-temporary stock data …

Prediction of stock market data is difficult because of its complex and highly volatile nature.
In this work the historical data as well as the technical indicators are implemented for the …

Understanding ocean wave-current interactions' complex dynamics is crucial for coastal
engineering, marine operations, and climate research applications. This study introduces a …

Climate change is a pressing global issue that profoundly impacts ecosystems, economies,
and societies. Accurate climate trend prediction is crucial for informed decision-making and …

In the Field of computer science, artificial intelligence (AI) is a broad field, which is
concerned with structuring smart products and machines able to perform tasks which require …