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Relevant bibliographies by topics / Parameters of network

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Academic literature on the topic 'Parameters of network'

Author: Grafiati

Published: 28 June 2021

Last updated: 3 February 2022

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Journal articles on the topic "Parameters of network"

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PELLEGRINI, Lilla, Monica LEBA, and Alexandru IOVANOVICI. "CHARACTERIZATION OF URBAN TRANSPORTATION NETWORKS USING NETWORK MOTIFS." Acta Electrotechnica et Informatica 20, no. 4 (2020): 3–9. http://dx.doi.org/10.15546/aeei-2020-0019.

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We use tools and techniques specific to the field of complex networks analysis for the identification and extraction of key parameters which define ”good” patterns and practices for designing public transportation networks. Using network motifs we analyze a set of 18 cities using public data sets regarding the topology of network and discuss each of the identified motifs using the concepts and tools of urban planning.

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Romanov, Oleksandr, Ivan Saychenko, Anton Marinov, and Serhii Skolets. "RESEARCH OF SDN NETWORK PERFORMANCE PARAMETERS USING MININET NETWORK EMULATOR." Information and Telecommunication Sciences, no. 1 (June 29, 2021): 24–32. http://dx.doi.org/10.20535/2411-2976.12021.24-32.

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Background. The implementation of the new modern services on existing networks requires replacement or modernization of the old equipment. This negatively affects the efficiency of providing users with new types of services and their cost. Therefore, the issues/tasks of implementing SDN technology in the construction of networks are in the center of attention of representatives of science-research organizations and telecom operators. SDN networks have the advantages of flexible scaling of the system without replacing existing server and network equipment, eliminating operator dependence on spe

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Zhou, Yang. "Research on Network Control Based on QoS of the Network." Advanced Materials Research 989-994 (July 2014): 4265–68. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.4265.

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With the technology improvement of computer communication and multimedia coding, real time communication such as audio and video is introduced to networks and become a dominant way of communication.In the control of network, the optimization problem of the network controller based on network Quality of service (QoS) is a very important problem in the research of network control. Considering the influence of network quality—of service (QoS) on the control performance,a system model combining the network parameters and the control parameters is established for networked control systems (NCSs). B

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LIU, WEI-YI, and KUN YUE. "BAYESIAN NETWORK WITH INTERVAL PROBABILITY PARAMETERS." International Journal on Artificial Intelligence Tools 20, no. 05 (2011): 911–39. http://dx.doi.org/10.1142/s0218213011000449.

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Interval data are widely used in real applications to represent the values of quantities in uncertain situations. However, the implied probabilistic causal relationships among interval-valued variables with interval data cannot be represented and inferred by general Bayesian networks with point-based probability parameters. Thus, it is desired to extend the general Bayesian network with effective mechanisms of representation, learning and inference of probabilistic causal relationships implied in interval data. In this paper, we define the interval probabilities, the bound-limited weak conditi

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Wang, Jia Jia, Yong Xiang Zhang, Wei Gong Zhang, and Hua Zhang Zhou. "Measuring Parameters of SpaceWire Network." Advanced Materials Research 159 (December 2010): 522–26. http://dx.doi.org/10.4028/www.scientific.net/amr.159.522.

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SpaceWire is used for on-board satellite networks. It is proposed by the ESA as the basis for future data-handing architectures. It takes an indispensable role for the shortage of bandwidth of bus among data processing. Based on the research of SpaceWire Network, some parameters, such as delay, bit error ratio, bandwidth and throughput, a new scheme of the testing about the parameters of SpaceWire was proposed. Then its implementation technology was analyzed and explained.

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Besfat, Henok M., Zelalem Hailu Gebeyehu, and Sudhir K. Routray. "Estimation of Parameters of 5G Network Dimensioning." International Journal of Electronics, Communications, and Measurement Engineering 10, no. 2 (2021): 15–32. http://dx.doi.org/10.4018/ijecme.2021070102.

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Cellular network traffic increases rapidly, and new services are introduced every year. For proper planning and design of such networks, exact requirements must be known with good accuracy. Dimensioning is an important part of network planning and design. Dimensioning is essential to determine the network requirements. In the coming years, fifth-generation (5G) will be deployed widely. 5G infrastructure is hybrid of wireless and optical components. For 5G network dimensioning, there is a need of a hybrid model. In this paper, the authors develop mathematical expressions for 5G network dimensio

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Chechin, G. V. "Select main parameters of Internet traffic exchange network." Issues of radio electronics 49, no. 5 (2020): 10–16. http://dx.doi.org/10.21778/2218-5453-2020-5-10-16.

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The article considers the urgent problem of mathematical modeling of the Internet traffic exchange network. A mathematical model of an Internet traffic exchange network with an arbitrary number IX (Internet Exchange Point, IX, IXP) in the form of a Queuing network is presented. The model allows you to analyze alternative options for building a traffic exchange network and determine the optimal parameters of its structure: minimize the average delay and select the bandwidth of communication channels, the performance of traffic exchange nodes with restrictions on reliability and cost, and select

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Buranova, M., and R. Latypov. "MPLS Network Parameters Analysis when Changing the Topology." Proceedings of Telecommunication Universities 5, no. 3 (2019): 6–12. http://dx.doi.org/10.31854/1813-324x-2019-5-3-6-12.

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One of the main tasks in network design is to evaluate the probability-time characteristics of the functioning of information and communication networks. Considering that the traffic of modern networks possesses the properties of self-similarity, we observe the difficulties while using the traditional mathematical apparatus of public serve theory. This paper presents us the results of jitter simulation estimating the delay, the probability of traffic loss when traffic processing in MPLS network. It was taken the real multimedia traffic and an on-off flow with a distribution of Pareto periods o

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Ma, Yifang, and Zhiming Zheng. "Extracting principal parameters of complex networks." International Journal of Modern Physics C 26, no. 09 (2015): 1550103. http://dx.doi.org/10.1142/s012918311550103x.

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The evolution of networks or dynamic systems is controlled by many parameters in high-dimensional space, and it is crucial to extract the reduced and dominant ones in low-dimensional space. Here we consider the network ensemble, introduce a matrix resolvent scale function and apply it to a spectral approach to get the similarity relations between each pair of networks. The concept of Diffusion Maps is used to get the principal parameters, and we point out that the reduced dimensional principal parameters are captured by the low order eigenvectors of the diffusion matrix of the network ensemble

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NITTA, TOHRU. "THE UNIQUENESS THEOREM FOR COMPLEX-VALUED NEURAL NETWORKS WITH THRESHOLD PARAMETERS AND THE REDUNDANCY OF THE PARAMETERS." International Journal of Neural Systems 18, no. 02 (2008): 123–34. http://dx.doi.org/10.1142/s0129065708001439.

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This paper will prove the uniqueness theorem for 3-layered complex-valued neural networks where the threshold parameters of the hidden neurons can take non-zeros. That is, if a 3-layered complex-valued neural network is irreducible, the 3-layered complex-valued neural network that approximates a given complex-valued function is uniquely determined up to a finite group on the transformations of the learnable parameters of the complex-valued neural network.

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Dissertations / Theses on the topic "Parameters of network"

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Åkesson, Emma. "Information visualization of network parameters in private cellular network solutions." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280858.

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In the upcoming years, industrial enterprises are expected to undergo a major transformation, as the Internet of Things (IoT) reaches widespread adoption. A key enabler behind this transformation, known as Industry 4.0, is the 5th generation of cellular networks (5G). Through privately owned networks, enterprises will be able to utilize the 5G technology to tailor the network to meet their needs in terms of security, reliability, and quality of service. Although much of the technology is currently in place, few efforts have been dedicated to help enterprises understand and optimise the value t

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Biswas, Sanjeet Kumar. "Analysis and comparison of network performance with different network parameters." FIU Digital Commons, 1999. http://digitalcommons.fiu.edu/etd/1703.

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The purpose of this study was to analyze the network performance by observing the effect of varying network size and data link rate on one of the most commonly found network configurations. Computer networks have been growing explosively. Networking is used in every aspect of business, including advertising, production, shipping, planning, billing, and accounting. Communication takes place through networks that form the basis of transfer of information. The number and type of components may vary from network to network depending on several factors such as requirement and actual physical placem

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Ikiz, Suheyla. "Performance Parameters Of Wireless Virtual Private Network." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607094/index.pdf.

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ABSTRACT PERFORMANCE PARAMETERS OF WIRELESS VIRTUAL PRIVATE NETWORK KZ, S&uuml<br>heyla Ms.c, Department of Information Systems Supervisor: Assoc. Prof. Dr. Nazife Baykal Co-Supervisor: Assist. Prof. Dr. Yusuf Murat Erten January 2006, 78 pages As the use of PC&rsquo<br>s and handheld devices increase, it expected that wireless communication would also grow. One of the major concerns in wireless communication is the security. Virtual Private Network (VPN) is the most secure solution that ensures three main aspect of security: authentication, accountability and encryption can use in wireless ne

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Ramaisa, Motlalepula. "Inferring congestion from delay and loss characteristics using parameters of the three-parameter Weibull distribution." Diss., Pretoria : [s.n.], 2005. http://upetd.up.ac.za/thesis/available/etd-08282007-112036.

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Gustavsson, Jonas. "Automated Performance Optimization of GSM/EDGE Network Parameters." Thesis, Linköping University, Linköping University, Communication Systems, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-52565.

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<p>The GSM network technology has been developed and improved during several years which have led to an increased complexity. The complexity results in more network parameters and together with different scenarios and situations they form a complex set of configurations. The definition of the network parameters is generally a manual process using static values during test execution. This practice can be costly, difficult and laborious and as the network complexity continues to increase, this problem will continue to grow.This thesis presents an implementation of an automated performance optimi

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Shaun, Ferdous Jahan. "Multi-Parameters Miniature Sensor for Water Network Management." Thesis, Paris Est, 2018. http://www.theses.fr/2018PESC1138/document.

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L’eau est une ressource vitale, indispensable à la vie sur terre. A l’instar de nombreuses autres ressources naturelles, l’eau propre à la consommation est soumise à une forte pression à cause de l’impact de l’activité humaine d’une part et de l’augmentation continue de la population mondiale d’autre part. Une pression tellement forte que l’eau propre représente l’un des 17 objectifs de développement durable des Nations Unies. Dans ce contexte, une gestion rationnelle et durable de la ressource s’avère indispensable. Dans ce but, un système intelligent de supervision des réseaux d’eau potable

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Tobolka, Lukáš. "Problematika návrhu síťové infrastruktury." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-442356.

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The aim of this diploma thesis is to look at the design of network infrastructure in practice. There are individual procedures, brands, standards that must be followed when designing. It includes a brief general overview of terminal elements, cable systems and related matters. In general, methods for measuring optical lines and parameters for measuring metallic networks are described here. The possible complications that accompany it are briefly described in the implementation. The network design methodology is also described here on the example of a specific object. Before the actual handover

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Lux, Matthew William. "Estimation of gene network parameters from imaging cytometry data." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/23082.

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Synthetic biology endeavors to forward engineer genetic circuits with novel function. A major inspiration for the field has been the enormous success in the engineering of digital electronic circuits over the past half century. This dissertation approaches synthetic biology from the perspective of the engineering design cycle, a concept ubiquitous across many engineering disciplines. First, an analysis of the state of the engineering design cycle in synthetic biology is presented, pointing out the most limiting challenges currently facing the field. Second, a principle commonly used in electro

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Karayaka, Hayrettin Bora. "Neural network modeling and estimation of synchronous machine parameters /." The Ohio State University, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488195633519029.

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McCloskey, Rosemary Martha. "Phylogenetic estimation of contact network parameters with approximate Bayesian computation." Thesis, University of British Columbia, 2016. http://hdl.handle.net/2429/58663.

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Models of the spread of disease in a population often make the simplifying assumption that the population is homogeneously mixed, or is divided into homogeneously mixed compartments. However, human populations have complex structures formed by social contacts, which can have a significant influence on the rate and pattern of epidemic spread. Contact networks capture this structure by explicitly representing each contact that could possibly lead to a transmission. Contact network models parameterize the structure of these networks, but estimating their parameters from contact data requires exte

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Books on the topic "Parameters of network"

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Mavaddat, R. Network scattering parameters. World Scientific, 1996.

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Network scattering parameters. World Scientific, 1996.

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Canada, Atomic Energy of. Generation of Synthetic Fracture Parameters For Crack Network Analysis. s.n, 1985.

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United Nations. Economic Commission for Europe. Transport Division. Inventory of main standards and parameters of the E waterway network "Blue Book". United Nations, 2012.

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Tan, Xiao-nan. Systolic calculation of parameters for optimal routing in a type of shuffle-exchange network. University of Toronto, Computer Systems Research Institute, 1986.

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Lemmon, Michael. Competitively inhibited neural networks for adaptive parameter estimation. Kluwer Academic, 1991.

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Lemmon, Michael. Competitively Inhibited Neural Networks for Adaptive Parameter Estimation. Springer US, 1991.

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Lemmon, Michael. Competitively Inhibited Neural Networks for Adaptive Parameter Estimation. Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-4044-1.

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Zuev, Sergey, Ruslan Maleev, and Aleksandr Chernov. Energy efficiency of electrical equipment systems of autonomous objects. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1740252.

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When considering the main trends in the development of modern autonomous objects (aircraft, combat vehicles, motor vehicles, floating vehicles, agricultural machines, etc.) in recent decades, two key areas can be identified. The first direction is associated with the improvement of traditional designs of autonomous objects (AO) with an internal combustion engine (ICE) or a gas turbine engine (GTD). The second direction is connected with the creation of new types of joint-stock companies, namely electric joint-stock companies( EAO), joint-stock companies with combined power plants (AOKEU).&#x0D

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Patan, Maciej. Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems. Springer Berlin Heidelberg, 2012.

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Book chapters on the topic "Parameters of network"

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Chowdhury, Dhiman Deb. "Timing Parameters." In NextGen Network Synchronization. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71179-5_2.

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Ghatak, Abhijit. "Initialization of Network Parameters." In Deep Learning with R. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-5850-0_4.

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Almond, Russell G., Robert J. Mislevy, Linda S. Steinberg, Duanli Yan, and David M. Williamson. "Parameters for Bayesian Network Models." In Bayesian Networks in Educational Assessment. Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2125-6_8.

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Yonemura, Tomoko, Yoshikazu Hanatani, Taichi Isogai, Kenji Ohkuma, and Hirofumi Muratani. "Generating Parameters for Algebraic Torus-Based Cryptosystems." In Cryptology and Network Security. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17619-7_12.

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Sumongkayothin, Karin, Pakpoom Rachtrachoo, Arnuphap Yupuech, and Kasidit Siriporn. "OVERSCAN: OAuth 2.0 Scanner for Missing Parameters." In Network and System Security. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36938-5_13.

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Colbourn, C., and E. Litvak. "Bounding network parameters by approximating graphs." In DIMACS Series in Discrete Mathematics and Theoretical Computer Science. American Mathematical Society, 1991. http://dx.doi.org/10.1090/dimacs/005/06.

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Kumar, B. Naveen, and P. V. Kumar. "Learning Parameters for Hybrid Bayesian Network." In International Conference on Mobile Computing and Sustainable Informatics. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49795-8_25.

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Tozzo, Veronica, and Annalisa Barla. "Multi-parameters Model Selection for Network Inference." In Complex Networks and Their Applications VIII. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36687-2_47.

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Tschiatschek, Sebastian, Peter Reinprecht, Manfred Mücke, and Franz Pernkopf. "Bayesian Network Classifiers with Reduced Precision Parameters." In Machine Learning and Knowledge Discovery in Databases. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33460-3_10.

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Badrieh, Fuad. "Multi-Port Network: Z- and Y-Parameters." In Spectral, Convolution and Numerical Techniques in Circuit Theory. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-71437-0_42.

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Conference papers on the topic "Parameters of network"

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Hummel, Robert A., Joshua A. Taylor, and Franz S. Hover. "Numerical Optimization of Generative Network Parameters." In ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-39262.

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We address the early design of complex, large-scale systems by viewing them as random networks and optimizing structure over their generative parameters. In this approach, we do not seek specific topologies, but rather classes of near-optimal networks which correspond to desirable statistical behavior, while also allowing flexibility to accommodate unmodeled constraints. Functionally, we perform the optimization of generative parameters on small networks (e.g., one hundred nodes) and use the results to design large networks (e.g., one thousand or more nodes). This approach is a computationally

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Filho, Milton B. Do Coutto, Julio C. Stacchini de Souza, and Edwin B. M. Meza. "Correcting electrical network parameters." In Energy Society General Meeting (PES). IEEE, 2009. http://dx.doi.org/10.1109/pes.2009.5275400.

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Embrechts, Mark J., Aaron L. Schweizerhof, Mark Bushman, and Mike H. Sabatella. "Neural Network Modeling of Turbofan Parameters." In ASME Turbo Expo 2000: Power for Land, Sea, and Air. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/2000-gt-0036.

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This research involves the development and validation of neural network models for several engine parameters for a turbofan engine. The investigation encompasses data collection, data translation, development of the neural network models, and testing. The data used to train and validate the neural network models was acquired from state of the art models as well as flight tests. During this study, different neural network architectures and training algorithms are exercised and evaluated for a turbofan engine operating at steady-state conditions. In addition, studies are performed to optimize th

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Cika, Petr, Stepan Grabovsky, Vaclav Zeman, and Vlastimil Clupek. "Network Emulator of Transmission Parameters of Data Networks." In 2018 10th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT). IEEE, 2018. http://dx.doi.org/10.1109/icumt.2018.8631254.

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Kulkarni, Samrat, Beth Polonsky, and Mohamed El-Sayed. "FTTH Network Economics: Key Parameters Impacting Technology Decisions." In 2008 13th International Telecommunications Network Strategy and Planning Symposium (NETWORKS). IEEE, 2008. http://dx.doi.org/10.1109/netwks.2008.4763668.

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Kulkarni, Samrat, Mohamed El-Sayed, Paul Gagen, and Beth Polonsky. "FTTH network economics: Key parameters impacting technology decisions." In 2008 13th International Telecommunications Network Strategy and Planning Symposium (NETWORKS). IEEE, 2008. http://dx.doi.org/10.1109/netwks.2008.6231299.

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Kumar, Manish, and Devendra P. Garg. "Neural Network Based Intelligent Learning of Fuzzy Logic Controller Parameters." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-59589.

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Design of an efficient fuzzy logic controller involves the optimization of parameters of fuzzy sets and proper choice of rule base. There are several techniques reported in recent literature that use neural network architecture and genetic algorithms to learn and optimize a fuzzy logic controller. This paper presents methodologies to learn and optimize fuzzy logic controller parameters that use learning capabilities of neural network. Concepts of model predictive control (MPC) have been used to obtain optimal signal to train the neural network via backpropagation. The strategies developed have

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Lluna, Eduardo, A. Edith Navarro, Diego Ramírez, and Silvia Casans. "Sensor Network to Measure Electric Parameters." In 2010 Fourth International Conference on Sensor Technologies and Applications (SENSORCOMM). IEEE, 2010. http://dx.doi.org/10.1109/sensorcomm.2010.81.

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Devarakonda, Kanchan, Sotirios G. Ziavras, and Roberto Rojas-Cessa. "Measuring Network Parameters with Hardware Support." In 2007 International Conference on Networking and Services. IEEE, 2007. http://dx.doi.org/10.1109/icns.2007.80.

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Cooper, Colin, Tomasz Radzik, and Yiannis Siantos. "Estimating network parameters using random walks." In 2012 Fourth International Conference on Computational Aspects of Social Networks (CASoN). IEEE, 2012. http://dx.doi.org/10.1109/cason.2012.6412374.

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Reports on the topic "Parameters of network"

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Shenker, S., and J. Wroclawski. General Characterization Parameters for Integrated Service Network Elements. RFC Editor, 1997. http://dx.doi.org/10.17487/rfc2215.

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Al-Qadi, Imad, Egemen Okte, Aravind Ramakrishnan, Qingwen Zhou, and Watheq Sayeh. Truck-Platoonable Pavement Sections in Illinois’ Network. Illinois Center for Transportation, 2021. http://dx.doi.org/10.36501/0197-9191/21-002.

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Truck platooning has many benefits over traditional truck mobility. Literature shows that platooning improves safety and reduces fuel consumption between 5% and 15% based on platoon configuration. In Illinois, trucks carry more than 50% of freight tonnage and constitute 25% of the traffic on interstates. Deployment of truck platooning within interstate highways would result in significant fuel savings, but may have a direct impact on flexible pavement performance. The channelization of the platoon and reduced rest time between consecutive loads would accelerate the damage accumulation at the c

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Henderson, Tim, Vincent Santucci, Tim Connors, and Justin Tweet. National Park Service geologic type section inventory: Klamath Inventory & Monitoring Network. National Park Service, 2021. http://dx.doi.org/10.36967/nrr-2286915.

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A fundamental responsibility of the National Park Service (NPS) is to ensure that park resources are preserved, protected, and managed in consideration of the resources themselves and for the benefit and enjoyment by the public. Through the inventory, monitoring, and study of park resources, we gain a greater understanding of the scope, significance, distribution, and management issues associated with these resources and their use. This baseline of natural resource information is available to inform park managers, scientists, stakeholders, and the public about the conditions of these resources

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Henderson, Tim, Mincent Santucci, Tim Connors, and Justin Tweet. National Park Service geologic type section inventory: Chihuahuan Desert Inventory & Monitoring Network. National Park Service, 2021. http://dx.doi.org/10.36967/nrr-2285306.

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A fundamental responsibility of the National Park Service is to ensure that park resources are preserved, protected, and managed in consideration of the resources themselves and for the benefit and enjoyment by the public. Through the inventory, monitoring, and study of park resources, we gain a greater understanding of the scope, significance, distribution, and management issues associated with these resources and their use. This baseline of natural resource information is available to inform park managers, scientists, stakeholders, and the public about the conditions of these resources and t

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Makedonska, Nataliia, Edward Michael Kwicklis, Jeffrey De'Haven Hyman, and Suzanne Michelle Bourret. Discrete Fracture Network Modeling to Estimate Upscaled Parameters for the Topopah Spring, Lava Flow, and Tiva Canyon Aquifers at Pahute Mesa, Nevada National Security Site. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1623419.

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Henderson, Tim, Vincent Santucci, Tim Connors, and Justin Tweet. National Park Service geologic type section inventory: Northern Colorado Plateau Inventory & Monitoring Network. National Park Service, 2021. http://dx.doi.org/10.36967/nrr-2285337.

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A fundamental responsibility of the National Park Service (NPS) is to ensure that park resources are preserved, protected, and managed in consideration of the resources themselves and for the benefit and enjoyment by the public. Through the inventory, monitoring, and study of park resources, we gain a greater understanding of the scope, significance, distribution, and management issues associated with these resources and their use. This baseline of natural resource information is available to inform park managers, scientists, stakeholders, and the public about the conditions of these resources

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Pettit, Chris, and D. Wilson. A physics-informed neural network for sound propagation in the atmospheric boundary layer. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41034.

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We describe what we believe is the first effort to develop a physics-informed neural network (PINN) to predict sound propagation through the atmospheric boundary layer. PINN is a recent innovation in the application of deep learning to simulate physics. The motivation is to combine the strengths of data-driven models and physics models, thereby producing a regularized surrogate model using less data than a purely data-driven model. In a PINN, the data-driven loss function is augmented with penalty terms for deviations from the underlying physics, e.g., a governing equation or a boundary condit

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Rouil, Richard, Antonio Izquierdo, Camillo Gentile, David Griffith, and Nada Golmie. Nationwide Public Safety Broadband Network Deployment: Network Parameter Sensitivity Analysis. National Institute of Standards and Technology, 2015. http://dx.doi.org/10.6028/nist.ir.8039.

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Farhi, Edward, and Hartmut Neven. Classification with Quantum Neural Networks on Near Term Processors. Web of Open Science, 2020. http://dx.doi.org/10.37686/qrl.v1i2.80.

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We introduce a quantum neural network, QNN, that can represent labeled data, classical or quantum, and be trained by supervised learning. The quantum circuit consists of a sequence of parameter dependent unitary transformations which acts on an input quantum state. For binary classification a single Pauli operator is measured on a designated readout qubit. The measured output is the quantum neural network’s predictor of the binary label of the input state. We show through classical simulation that parameters can be found that allow the QNN to learn to correctly distinguish the two data sets. W

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Bowles, David, Michael Williams, Hope Dodd, et al. Protocol for monitoring aquatic invertebrates of small streams in the Heartland Inventory & Monitoring Network: Version 2.1. National Park Service, 2021. http://dx.doi.org/10.36967/nrr-2284622.

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The Heartland Inventory and Monitoring Network (HTLN) is a component of the National Park Service’s (NPS) strategy to improve park management through greater reliance on scientific information. The purposes of this program are to design and implement long-term ecological monitoring and provide information for park managers to evaluate the integrity of park ecosystems and better understand ecosystem processes. Concerns over declining surface water quality have led to the development of various monitoring approaches to assess stream water quality. Freshwater streams in network parks are threaten

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