first learning of human drivers, which then 'mutate` to CAVs, are trained to optimize routing policies with the implemented algorithm. When the training is finished, it uses raw results to compute a ...

A new technical paper titled “Cross-Layer Design of Vector-Symbolic Computing: Bridging Cognition and Brain-Inspired Hardware Acceleration” was published by researchers at Purdue University and ...

Combinatorial optimisation is a fundamental field in applied mathematics and computer science that focuses on finding an optimal object from a finite set of objects. In this context, problems are ...

Abstract: To address the Vehicle Routing Problem with Time Windows (VRPTW), this paper presents a novel Dual Adaptive Genetic Algorithm (DAGA). While numerous metaheuristic algorithms have been ...

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.

Ad hoc network is a collection of mobile nodes which dynamically form a temporary network without any infrastructure or centralize entity. There are number of routing protocol exists in ad hoc network ...

Created my own topology to set up static routing. Also implemented an "application" layer routing protocol which implements distance vector routing using Bellman-Ford algorithm.

We now have planes, trains, and automobiles. So is it really a big deal if you have to travel several hours to date someone? What’s the issue if you live in Maryland and want to see someone in Rhode ...

We now have planes, trains, and automobiles. So what’s the big deal if you have to travel a few hours to date someone? What’s the issue if you live in Maryland and want to see someone in New York, ...

Abstract: In order to solve the problem of routing protocols using the distributed Bellman-Ford (DBF) algorithm converge very slowly to the correct routes when link costs increase, and in the case ...