The recent advancement in data science coupled with the revolution in digital and satellite
technology has improved the potential for artificial intelligence (AI) applications in the …

The demand forecasting technique which is modeled by artificial intelligence approaches
using artificial neural networks. The consumer product causers the difficulty in forecasting …

Used frying oil (UFO) has a great potential as feedstock for biodiesel production. This study
aims to develop an artificial neural network (ANN) model to predict biodiesel yield produced …

The supply chain of every enterprise comprises a highly distributed environment, in which
complex processes evolve in a network of companies and this distributed environment …

Support Vector Machine (SVM) is a popular machine learning method for classification,
regression, and other learning tasks. Support Vector Regression (SVR), a category for …

In this study, it was aimed to determine artificial neural network models with different
architectures using artificial neural network (ANN) methods used in future prediction studies …

The potential applications of artificial intelligence (AI) in the sector of forestry and wildlife has
grown and thanks to recent advancements in data science and analytics, as well as the …

The objective of the research is to forecast the trend of the printing and writing paper
consumption in Iran for a five-year period using both modern and classical methods. In order …

Cryptographic approaches are traditional and preferred methodologies used to preserve the
privacy of data released for analysis. Privacy Preserving Data Mining (PPDM) is a new trend …

Artificial neural networks (ann) are massively interconnected networks of simple elements,
which try to interact with the objects of the real world in the same way as that the biological …