Deep neural networks represent, nowadays, the most effective machine learning technology
in biomedical domain. In this domain, the different areas of interest concern the Omics (study …

Location estimation is one of the critical requirement for developing smart environment
products. Due to huge utilization and accessibility of WiFi infrastructure facility in indoor …

Neural network based on back-propagation (BP) algorithm is a widely used prediction
model. However, the nodes number of the first hidden layer, the learning rate and …

Precise indoor localization is of great importance to automatically track people or objects
indoors and plays a vital role in modern life. Despite a number of innovative research …

Accurate water level prediction is of great importance for water infrastructures such as dams,
embankments, and agriculture. However, the water level has nonlinear characteristics …

The problem of risk classification and prediction, an essential research direction, aiming to
identify and predict risks for various applications, has been researched in this paper. To …

The wireless sensor network (WSN) is gaining paramount importance due to its application
in real-time monitoring of vast geographical regions. The deployment paradigm shift is …

Based on axiomatic fuzzy set (AFS) theory and fuzzy information entropy, a novel fuzzy
oblique decision tree (FODT) algorithm is proposed in this paper. Traditional axis-parallel …

The data flow is an important parameter used in the optimization problem of Wireless Sensor
Networks. This paper presents an expert approach for improved data flow prediction based …

This research focuses on optimizing the performance of fuzzy grid partitioning for rule
generation in dataset classification. The objective is to develop an approach that improves …