The integration of deep learning (DL) techniques with geographical information system (GIS)
offers a promising avenue for gaining novel insights into environmental phenomena by …

Data-driven fault diagnosis has become a hot topic of research in recent years, due to its
wide applicability, high accuracy, and ease of modeling. In data-driven fault diagnosis …

Aflatoxins, harmful substances found in peanuts, corn, and their derivatives, pose significant
health risks. Addressing this, the presented research introduces an innovative MSGhostDNN …

This investigation seeks to reconcile the interpretability of artificial intelligence with the
imperative of maintaining optimal performance, through the introduction of the IFNN model …

Abstract Dempster–Shafer (D–S) evidence theory is used to process multisource data fusion
and uncertainty problems. When faced with strongly contradictory evidence, there are …

Conventional preference analysis methods often implicitly neglect the influence of online
review reliability and cannot fully consider customer psychological needs, eg, reference …

This research paper presents a comprehensive study on optimizing the critical artificial
intelligence (AI) factors influencing cost management in civil engineering projects using a …

This study investigates the integration and utilization of diverse data forms within consumer
electronics, with a particular emphasis on Internet of Things (IoT) technologies. We introduce …

Making informed decisions and improving organizational performance are crucial in the
modern, data-driven environment. These processes are significantly shaped by a number of …

Cervical cancer is entirely preventable if diagnosed at an early stage; however, the current
rate of cervical cancer screening participation is not very adequate, and early detection …