2 edition of Formulas and algorithms for optimizing the performance of rapidly changing satellite networks found in the catalog.
Written in English
|Statement||by Charles D. McLochlin|
|The Physical Object|
|Pagination||x, 104 leaves :|
|Number of Pages||104|
For the problem of poor link reliability caused by high-speed dynamic changes and congestion owing to low network bandwidth in ad hoc networks, an ant colony routing algorithm, based on reliable path under dual-channel condition (DSAR), is proposed. First, dual-channel communication mode is used to improve network bandwidth, and a hierarchical network model is proposed to optimize the dual. The Kalman filter model assumes the true state at time k is evolved from the state at (k − 1) according to = − + + where F k is the state transition model which is applied to the previous state x k−1;; B k is the control-input model which is applied to the control vector u k;; w k is the process noise which is assumed to be drawn from a zero mean multivariate normal distribution,, with.
Algorithms can save lives, make things easier and conquer chaos. But experts worry about governmental and corporate control of the data, and how algorithms can produce biased results and worsen digital divides. Neural networks are trained using the stochastic gradient descent optimization algorithm. This requires first the estimation of the loss on one or more training examples, then the calculation of the derivative of the loss, which is propagated backward through the network in order to update the weights.
There has also been signiﬁcant interest in obtaining the performance of RWA algorithms under dynamic traﬃc assumptions [BaH96], [KoA96], [SaS96]. For this purpose, stochastic models are employed for the call arrivals and service times. The performance of all-optical networks have been studied when some simple RWA al-gorithms are used. Analyze data, develop algorithms, and create mathematical models. Explore MATLAB Panel Navigation. SIMULINK. Run simulations, generate code, and test and verify embedded systems. Explore Simulink Panel Navigation. What’s new in the latest release of MATLAB and Simulink.
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Formulas and algorithms for optimizing the performance of rapidly changing satellite networks. By Charles D McLochlin. Abstract (Thesis) Thesis (Ph. D.)--University of Florida, (Bibliography) Includes bibliographical references (leaves )(Statement of Responsibility) by Charles D.
McLochlin Author: Charles D McLochlin. Formulas and algorithms for optimizing the performance of rapidly changing satellite networks. By Charles D McLochlin. Abstract. Vita. Topics: Artificial satellites in telecommunication (lcsh), Electric network topology (lcsh) OAI identifier: oai:www Author: Charles D McLochlin.
In this work, a datagram routing algorithm for LEO satellite networks is introduced. The algorithm generates minimum propagation delay paths. The performance of the algorithm is evaluated through.
Engineers tasked with optimizing a satellite network must juggle multiple variables to get the best overall result. Many of the basic design considerations involve the RF link, antenna size, satellite frequencies and satellite modems, but as satellite networks increasingly are interconnected with IP-based networks, network optimization includes Author: Greg Berlocher.
An example function that is often used for testing the performance of optimization algorithms on saddle points is the Rosenbrook function. The function is described by the formula: f(x,y) = (a-x)² + b(y-x²)², which has a global minimum at (x,y) = (a,a²). This is a non-convex function with a global minimum located within a long and narrow valley.
Keywords: Satellite network, Resources optimization, Genetic algorithms 1. Introduction. The satellite network which is components of types of satellite system in ﬀt orbit is the future trend of the main developments in information technology.
The various function equipment and logical resources in satellite constitute the whole. The book can be used for a course on network optimization or for part of a course on introductory optimization; such courses have ﬂourished in engineering, operations research, and applied mathematics curricula.
The book contains a large number of examples and exercises, which should enhance its suitability for classroom instruction. Charles D. McLochlin has written: 'Formulas and algorithms for optimizing the performance of rapidly changing satellite networks' -- subject(s): Electric network topology, Artificial satellites in.
The performance of ML algorithms suffers when training classes are highly unbalanced. In such a situation, ML algorithms tend to maximize performance by over-predicting the majority class (Liu et al., ). This is particularly undesirable for this study's predictions as the intended prediction target (rain) usually represents the minority class.
It is mainly related to the solution of the problem of time variance of satellite network topologies. Routing strategies are an important part of satellite network routing, for it can directly affect the performance of routing algorithms and traffic engineering.
Machine learning is an automated approach to building empirical models from the data alone.A key advantage of this is that we make no a priori assumptions about the data, its functional form, or probability distributions.
It is an empirical approach, so we do not need to provide a theoretical model. Optimization-Based Distributed Algorithms for Mobile Data Gathering in Wireless Sensor Networks Abstract: Recent advances have shown a great potential of mobile data gathering in wireless sensor networks, where one or more mobile collectors are employed to collect data from sensors via short-range communications.
Such image recognition algorithms have arrived at just the right moment in the aerospace field as they provide an excellent means of processing satellite photos.
"Five years ago we couldn't have done what we're able to do today", Pavel Machalek, co-founder and CEO SpaceKnow, a company specializing in satellite data analysis for commercial.
I know enough about optimization to read the technical paper. The analysis is interesting, but the algorithm itself is impractical. It relies on computing values of a smoothed function that is defined from the original function using an integral.
In real applications, computing this integral is likely to be harder than doing the optimization. INTRODUCTION Algorithms for function optimization are generally limited to convex regular functions.
However, many functions are multi-modal, discontinuous, and nondifferenName: Christopher R. A Satellite Routing Algorithm Based on Optimization of Both Delay and Bandwidth Abstract: The merits of the routing algorithm will have a direct impact on the performance of a communication network.
Traditional satellite routing algorithms are based on shortest path algorithm, the simply considering least delay, the least hop or the best link. The “ firefly algorithm ” (FFA) is a modern metaheuristic algorithm, inspired by the behavior of fireflies.
This algorithm and its variants have been successfully applied to many continuous optimization problems. This work analyzes the performance of the FFA when solving combinatorial optimization. The model uses satellite imagery to gather data and then executes an algorithm. The algorithm runs through millions of images across the globe comparing the presence of light in any given region during the day and at the night to predict the level of economic activity.
This method of comparison is called transfer learning. In the paper “Optimum performance-based seismic design using a hybrid optimization algorithm,” S. Talatahari et al. present a hybrid optimization method to optimum seismic design of steel frames considering four performance levels.
These performance levels are considered to determine the optimum design of structures to reduce the structural. A QoS-based Routing Algorithm in Multimedia Satellite Networks Chao Chen the optimization is not done between end users and the inter-satellite handovers are not considered.
The predictive routing protocol proposed in The performance evaluation of the algorithm is presented in Section IV. Finally, Section V concludes the paper. performance optimization), while the center of the recent book by Busoniu et al.
() is function approximation. Thus, by no means do RL researchers lack a good body of literature. However, what seems to be missing is a self-contained and yet relatively short summary that can help newcomers.
The rectified linear activation function has rapidly become the default activation function when developing most types of neural networks. As such, it is important to take a moment to review some of the benefits of the approach, first highlighted by Xavier Glorot, et al. in their milestone paper on using ReLU titled “ Deep Sparse.The merits of the routing algorithm will have a direct impact on the performance of a communication network.
Traditional satellite routing algorithms are based on shortest path algorithm, the simply considering least delay, the least hop or the best link-bandwidth utilization. For the request of real-time in information network, a routing algorithm BDSR (bandwidth-delay satellite routing.