4th International Conference on Artificial Intelligence and Applied Mathematics in Engineering

As general, this book is a collection of the most recent, quality research papers regarding applications of Artificial Intelligence and Applied Mathematics for engineering problems. The papers included in the book were accepted and presented in the 4th International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME 2022), which was held in Baku, Azerbaijan (Azerbaijan Technical University) between May 20 and 22, 2022. Objective of the book content is to inform the international audience about the cutting-edge, effective developments and improvements in different engineering fields. As a collection of the ICAIAME 2022 event, the book gives consideration for the results by especially intelligent system formations and the associated applications. The target audience of the book is international researchers, degree students, practitioners from industry, and experts from different engineering disciplines.

Presents advanced computing and networking technologies to enable intelligent and efficient IoT and CPS Includes papers from the 4th International Conference on Artificial Intelligence and Applied Mathematics in Engineering Written by experts in the field

Inhalt
Sentiment Analysis in Turkish using Transformer-based Deep Learning Models.- Mathematical Modeling of an Antenna Device Based on a T-shaped Waveguide of the Microwave Range.- Higher-order and stable numerical scheme for nonlinear diffusion system via compact finite difference and adaptive step-size Runge-Kutta methods.- Explainable Artificial Intelligence (XAI) for Deep Learning Based Intrusion Detection Systems.- A Color Channel Based Analysis on Image Tessellation.- Modeling of Shear Strength of Basalt Fiber Reinforced Clay (BFRC) Soil Using Artificial Neural Network (ANN).- Change of the Internet with Blockchain and Metaverse Technologies.- A Language-Free Hate Speech Identification on Code-Mixed Conversational Tweets.- Decision Trees in Causal Inference.- The Resilience of Unmanned Aerial Vehicles to Cyberattacks and Assessment of Potential Threats.<p