Facilitating citizens with accurate traffic flow prediction increases the quality of life. Roadside sensors and devices are used to capture live streams huge data Internet Things (IoT) is becoming popular for deployment effective Intelligent Transportation Systems (ITS). Traffic from datastreams require building a data-driven model. This challenging task has attracted researchers better interpr...

The routing mechanisms in flying ad-hoc networks (FANETs) using unmanned aerial vehicles (UAVs) have been a challenging issue for many reasons, such as its high speed and different directions of use. In FANETs, the protocols send hello messages periodically maintenance routes. However, that are sent network increase bandwidth wastage on some occasions excessive number can also cause problem ene...

The integration analysis of multi-type geospatial information poses challenges to existing spatiotemporal data organization models and based on deep learning. For earthquake early warning, this study proposes a novel intelligent grid model GeoSOT (SGMG-EEW) for feature fusion data. This includes seismic sample (SGSM) three-dimensional group convolution neural network (3DGCNN-SGM). SGSM solves t...

In the present industrial revolution era, mechanical system becomes incessantly highly intelligent and composite. So, it is necessary to develop data-driven monitoring approaches for achieving quick, trustable, high-quality analysis in an automated way. Fault diagnosis essential process verify safety reliability operations of rotating machinery. The advent deep learning (DL) methods employed di...

Porosity is considered as an important petrophysical parameter in characterizing reservoirs, calculating in-situ oil reserves, and production evaluation. Nowadays, using intelligent techniques has become a popular method for porosity estimation. Support vector machine (SVM) a new intelligent method with a great generalization potential of modeling non-linear relationships has been introduced fo...

In automation flexible manufacturing systems, tool wear detection during the cutting process is one of the most important considerations. This study presents an intelligent system for online tool condition monitoring in drilling process .In this paper, analytical and empirical models have been used to predict the thrust and cutting forces on the lip and chisel edges of a new drill. Also an empi...