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Full-Text Articles in Physical Sciences and Mathematics
Integer Solutions To Optimization Problems And Modular Sequences Of Nexus Numbers, Jeremy T. Davis
Integer Solutions To Optimization Problems And Modular Sequences Of Nexus Numbers, Jeremy T. Davis
Electronic Theses and Dissertations
In this thesis, we examine the use of integers through two ideas. As mathematics teachers, we prefer students not use calculators on assessments. In order to require this, students compute the problems by hand. We take a look at the classic Calculus I optimization box problem while restricting values to integers. In addition, sticking with the integer theme, we take a new look at the nexus numbers. Nexus numbers are extensions of the hex and rhombic dodecahedral numbers. We put these numbers into a sequence, and through a few computations of modular arithmetic, we analyze the sequences and their patterns …
Networking And Security Solutions For Vanet Initial Deployment Stage, Baber Aslam
Networking And Security Solutions For Vanet Initial Deployment Stage, Baber Aslam
Electronic Theses and Dissertations
Vehicular ad hoc network (VANET) is a special case of mobile networks, where vehicles equipped with computing/communicating devices (called "smart vehicles") are the mobile wireless nodes. However, the movement pattern of these mobile wireless nodes is no more random, as in case of mobile networks, rather it is restricted to roads and streets. Vehicular networks have hybrid architecture; it is a combination of both infrastructure and infrastructure-less architectures. The direct vehicle to vehicle (V2V) communication is infrastructure-less or ad hoc in nature. Here the vehicles traveling within communication range of each other form an ad hoc network. On the other …
A Fitness Function Elimination Theory For Blackbox Optimization And Problem Class Learning, Gautham Anil
A Fitness Function Elimination Theory For Blackbox Optimization And Problem Class Learning, Gautham Anil
Electronic Theses and Dissertations
The modern view of optimization is that optimization algorithms are not designed in a vacuum, but can make use of information regarding the broad class of objective functions from which a problem instance is drawn. Using this knowledge, we want to design optimization algorithms that execute quickly (efficiency), solve the objective function with minimal samples (performance), and are applicable over a wide range of problems (abstraction). However, we present a new theory for blackbox optimization from which, we conclude that of these three desired characteristics, only two can be maximized by any algorithm. We put forward an alternate view of …