We propose a quality control method based on machine learning neural networks to enhance the quality of high-frequency (HF) radar data. Unlike traditional quality control methods that rely on radar signals as indicators and involve extensive data manipulation in specialized software, our approach employs a Bi-LSTM neural network model. This method aims to improve data quality and streamline the quality control process. Through a series of analyses, we demonstrate the feasibility of using machine learning techniques to enhance radar data quality.
This review paper analyzes the recent applications of computational mechanics methods in combination with machine learning (ML) and neural network (NN) techniques, as found in the literature published between 2015 and 2024. We present how ML and NNs are enhancing traditional comp…
Ensuring robust railway safety is paramount for efficient and reliable transportation systems, a challenge increasingly addressed through advancements in artificial intelligence (AI). This review paper comprehensively explores the burgeoning role of AI in enhancing the safety of…
This study aims to predict Turkish consumer preferences for smart tablets on e-commerce platforms, focusing on consumer behavior in a developing country context. Key product attributes—such as processor speed, screen size, internal storage capacity, display resolution, RAM, proce…
This study presents a hybrid method based on traveling wave (TW) analysis and machine learning to determine the locations of lightning-induced faults in grid-connected photovoltaic (PV) systems. As part of the study, various lightning scenarios were simulated on a transmission li…
The development of Software-Defined Networks (SDNs) introduces new challenges in network security, particularly in detecting Distributed Denial of Service (DDoS) attacks and network anomalies. Due to the centralized architecture of SDN, traditional detection methods are often ins…
Transparency in business practices is essential for sustainability, ensuring that resources are used responsibly and that environmental and social impacts are properly measured and monitored, allowing the end consumer to make informed purchasing decisions without feeling cheated.…