Energy‐efficient workload allocation in fog‐cloud based services of intelligent transportation systems using a learning classifier system

Pmipv6 Based Intelligent Transportation Systems

Intelligent transportation system (ITS) consists of moving networks, where the network mobility (NEMO) basic support is adopted as a mobility management protocol for moving networks. Even though NEMO basic support (NBS) provides a basic mobility support for ITS systems, the mobile routers (MR) need to participate in the mobility signaling. In the literature, network based mobility management su...

Intelligent and Robust Genetic Algorithm Based Classifier

The concepts of robust classification and intelligently controlling the search process of genetic algorithm (GA) are introduced and integrated with a conventional genetic classifier for development of a new version of it, which is called Intelligent and Robust GA-classifier (IRGA-classifier). It can efficiently approximate the decision hyperplanes in the feature space. It is shown experime...

HITS: A History-Based Intelligent Transportation System

Transportation is the driving force of any country. Today we are facing an explosion in the number of motor vehicles that affects our daily routines. Intelligent transportation systems (ITS) aim to provide efficient tools that solve traffic problems. Predicting route congestions during different day periods can help drivers choose better routes for their trips. In this paper we propose “HITS” a...

Vision-Based Intelligent Control of Transportation Systems

NEW CRITERIA FOR RULE SELECTION IN FUZZY LEARNING CLASSIFIER SYSTEMS

Designing an effective criterion for selecting the best rule is a major problem in theprocess of implementing Fuzzy Learning Classifier (FLC) systems. Conventionally confidenceand support or combined measures of these are used as criteria for fuzzy rule evaluation. In thispaper new entities namely precision and recall from the field of Information Retrieval (IR)systems is adapted as alternative...