Relevant bibliographies by topics / Back-pressure algorithm

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Back-pressure algorithm'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

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Journal articles on the topic "Back-pressure algorithm"

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S, Jotheeshwaran, and Kumaravel A. "Back Pressure Algorithm with CBDS." International Journal of Electronics and Communication Engineering 3, no. 12 (2016): 8–11. http://dx.doi.org/10.14445/23488549/ijece-v3i12p103.

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Ying, Lei, R. Srikant, Don Towsley, and Shihuan Liu. "Cluster-Based Back-Pressure Routing Algorithm." IEEE/ACM Transactions on Networking 19, no. 6 (2011): 1773–86. http://dx.doi.org/10.1109/tnet.2011.2141682.

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Haibo, Liang, and Li Hongyan. "Control Model of Throttle Back Pressure of Managed Pressure Drilling." Journal of Computational and Theoretical Nanoscience 13, no. 10 (2016): 7603–9. http://dx.doi.org/10.1166/jctn.2016.5759.

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This paper established a controlling model of Throttling Back Pressure system of Managed Pressure Drilling (MPD), and aim at its nonlinear characteristics of the model, a fuzzy-PID controlling method with a capability of parameter self-tuning was proposed. This method utilizes the idea of fuzzy controlling and designs a fuzzy inference theory to realize the function of online tuning PID control parameters. Through comparing this controlling algorithm with conventional controlling algorithms and analyzing, results showed that overshoot of this throttling back pressure controlling system using f
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Hai, Long, Qinghua Gao, Jie Wang, He Zhuang, and Ping Wang. "Delay-Optimal Back-Pressure Routing Algorithm for Multihop Wireless Networks." IEEE Transactions on Vehicular Technology 67, no. 3 (2018): 2617–30. http://dx.doi.org/10.1109/tvt.2017.2770183.

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Stolyar, Alexander L. "Large number of queues in tandem: Scaling properties under back-pressure algorithm." Queueing Systems 67, no. 2 (2010): 111–26. http://dx.doi.org/10.1007/s11134-010-9203-0.

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Jiao, Zhenzhen, Yan Yan, Baoxian Zhang, and Cheng Li. "An efficient network-coding based back-pressure scheduling algorithm for wireless multi-hop networks." International Journal of Communication Systems 30, no. 8 (2016): e3180. http://dx.doi.org/10.1002/dac.3180.

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Cai, Wenyu, Dongyang Zhao, Meiyan Zhang, Yinan Xu, and Zhu Li. "Improved Self-Organizing Map-Based Unsupervised Learning Algorithm for Sitting Posture Recognition System." Sensors 21, no. 18 (2021): 6246. http://dx.doi.org/10.3390/s21186246.

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As the intensity of work increases, many of us sit for long hours while working in the office. It is not easy to sit properly at work all the time and sitting for a long time with wrong postures may cause a series of health problems as time goes by. In addition, monitoring the sitting posture of patients with spinal disease would be beneficial for their recovery. Accordingly, this paper designs and implements a sitting posture recognition system from a flexible array pressure sensor, which is used to acquire pressure distribution map of sitting hips in a real-time manner. Moreover, an improved
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Wan, Liang Yong, Xue Feng Zhang, and Kai Yun Liu. "Intelligent Displacement Back Analysis Method of Three-Dimension Applied in Unsymmetrical Pressure Tunnel with Shallow Depth." Applied Mechanics and Materials 90-93 (September 2011): 2286–91. http://dx.doi.org/10.4028/www.scientific.net/amm.90-93.2286.

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Artificial neural network has been widely used in displacement back analysis, but it has the problems of large sample, over-fitting, local optimization and poor generalization performance, so it has the poor adaptability in the Geotechnical Engineering. Support Vector Machines algorithm has the advantages of small sample, global optimization and generalization performance. A direct optimization method based on genetic algorithm and the improved support vector regression algorithm (GA-SVR) is applied in order to identify multinomial parameters intelligently and forecast displacements fast and e
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Li, Zhenjun. "A Data Classification Algorithm of Internet of Things Based on Neural Network." International Journal of Online Engineering (iJOE) 13, no. 09 (2017): 28. http://dx.doi.org/10.3991/ijoe.v13i09.7587.

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<p style="margin: 1em 0px;"><span lang="EN-US"><span style="font-family: 宋体; font-size: medium;">To alleviate the pressure of data size, data transmission and data processing in the huge data dimension of the Internet of things., data classification is realized based on back propagation (BP) neural network algorithm. The working principle is deduced in detail. For the shortcomings of slow convergence and easy to fall into the local minimum, the combination of variable learning and momentum factors is used to improve the traditional back propagation algorithm. The results show
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Jie, Zhou, and Ma Qiurui. "Establishing a Genetic Algorithm-Back Propagation model to predict the pressure of girdles and to determine the model function." Textile Research Journal 90, no. 21-22 (2020): 2564–78. http://dx.doi.org/10.1177/0040517520922947.

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A Genetic Algorithm-Back Propagation (GA-BP) neural network method has been proposed to predict the clothing pressure of girdles in different postures. Firstly, a Back Propagation (BP) neural network model was used to predict the clothing pressure based on seven parameters, and three optimal functions of the model were derived. However, the prediction error 0.85411 of the network was more than the forecast requirement of 0.5 and the optimal initial weights and thresholds for the network could not be calculated. Therefore, a GA model and the BP neural network model were combined into a new GA-B
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Dissertations / Theses on the topic "Back-pressure algorithm"

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Zhao, Haiquan. "Measurement and resource allocation problems in data streaming systems." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34785.

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In a data streaming system, each component consumes one or several streams of data on the fly and produces one or several streams of data for other components. The entire Internet can be viewed as a giant data streaming system. Other examples include real-time exploratory data mining and high performance transaction processing. In this thesis we study several measurement and resource allocation optimization problems of data streaming systems. Measuring quantities associated with one or several data streams is often challenging because the sheer volume of data makes it impractical to store the
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Ryu, Jung Ho. "Congestion control and routing over challenged networks." Thesis, 2011. http://hdl.handle.net/2152/ETD-UT-2011-12-4620.

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This dissertation is a study on the design and analysis of novel, optimal routing and rate control algorithms in wireless, mobile communication networks. Congestion control and routing algorithms upto now have been designed and optimized for wired or wireless mesh networks. In those networks, optimal algorithms (optimal in the sense that either the throughput is maximized or delay is minimized, or the network operation cost is minimized) can be engineered based on the classic time scale decomposition assumption that the dynamics of the network are either fast enough so that these algorithms
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Li, Chih-Yuan, and 李之源. "Economic Dispatch for Back-Pressure Cogeneration Considering Power Wheeling Using Genetic Algorithms." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/62286758915385727796.

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碩士<br>中原大學<br>電機工程學系<br>88<br>Since deregulation in the power industry, there are more and more private corporations join electric power market. The government encourages private generators to install efficient generating facilities. Moreover, private generators can be excused from the duty of energy ratio if their generation efficiency reach a specific threshold. Hence the cogeneration system with a high efficiency is gaining highly attention. Independent power producer can sell electricity to specific customers directly or indirectly in the future in Taiwan. Therefore, the purpose of this th
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Wang, Yung-Yu, and 王永裕. "OPTIMUM OPERATION FOR A BACK-PRESSURE COGENERATION SYSTEM BY MODIFIED GENETIC ALGORITHMS." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/34099191456716438360.

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碩士<br>大同工學院<br>電機工程學系<br>84<br>This thesis proposed the Modified Genetic Algorithm (MGA) to enhance the robustness, search capability, and speed of Genetic Algorithms(GAs), such thatthe algorithms can be applied efficiently to the optimum operation of a back-pressure cogeneration system[1]. First, we utilize a simple example proposed by Sheble[2] to show thestrategies of MGA and compare our performances to the result of Sheble, andthen we make use of MGA to solve the optimum
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Book chapters on the topic "Back-pressure algorithm"

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Janghel, R. R., Anupam Shukla, and Ritu Tiwari. "Intelligent Decision Support System for Fetal Delivery using Soft Computing Techniques." In Data Mining. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2455-9.ch057.

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In the present work an attempt is made to develop an intelligent Decision support system (IDSS) using the pathological attributes to predict the fetal delivery to be done normal or by surgical procedure. The pathological tests like Blood Sugar (BR), Blood pressure (BP), Resistivity Index (RI) and systolic / Diastolic (S/P) ratio will be recorded at the time of delivery. All attributes lie within a specific range for normal patient. The database consists of the attributes for cases 2 (i.e. normal and surgical delivery). Soft computing technique namely Artificial Neural Networks (ANN) are used for simulator. The attributes from dataset are used for training &amp; testing of ANN models. Three models of ANN are trained using Back-Propagation Algorithm (BPA), Radial Basis Function Network (RBFN), Learning Vector Quantization Network (LVQN) and one hybrid approach is Adaptive Neuro-Fuzzy Inference System (ANFIS). The designing factors have been changed to get the optimized model, which gives highest recognition score. The optimized models of BPA, RBFN, LVQN and ANFIS gave accuracies of 93.75, 99.00, 87.50 and 99.50% respectively. Hence in our present research the ANFIS is the model whom efficiency and result are best .The ANFIS is the best network for mentioned problem. This system will assist doctor to take decision at the critical time of fetal delivery.
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Janghel, R. R., Anupam Shukla, and Ritu Tiwari. "Intelligent Decision Support System for Fetal Delivery using Soft Computing Techniques." In Biomedical Engineering and Information Systems. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-61692-004-3.ch007.

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In the present work an attempt is made to develop an intelligent Decision support system (IDSS) using the pathological attributes to predict the fetal delivery to be done normal or by surgical procedure. The pathological tests like Blood Sugar (BR), Blood pressure (BP), Resistivity Index (RI) and systolic / Diastolic (S/P) ratio will be recorded at the time of delivery. All attributes lie within a specific range for normal patient. The database consists of the attributes for cases 2 (i.e. normal and surgical delivery). Soft computing technique namely Artificial Neural Networks (ANN) are used for simulator. The attributes from dataset are used for training &amp; testing of ANN models. Three models of ANN are trained using Back-Propagation Algorithm (BPA), Radial Basis Function Network (RBFN), Learning Vector Quantization Network (LVQN) and one hybrid approach is Adaptive Neuro-Fuzzy Inference System (ANFIS). The designing factors have been changed to get the optimized model, which gives highest recognition score. The optimized models of BPA, RBFN, LVQN and ANFIS gave accuracies of 93.75, 99.00, 87.50 and 99.50% respectively. Hence in our present research the ANFIS is the model whom efficiency and result are best .The ANFIS is the best network for mentioned problem. This system will assist doctor to take decision at the critical time of fetal delivery.
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Conference papers on the topic "Back-pressure algorithm"

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Ying, L., R. Srikant, and D. Towsley. "Cluster-Based Back-Pressure Routing Algorithm." In IEEE INFOCOM 2008 - IEEE Conference on Computer Communications. IEEE, 2008. http://dx.doi.org/10.1109/infocom.2008.96.

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Ying, L., R. Srikant, and D. Towsley. "Cluster-Based Back-Pressure Routing Algorithm." In 27th IEEE International Conference on Computer Communications (INFOCOM 2008). IEEE, 2008. http://dx.doi.org/10.1109/infocom.2007.96.

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Xiao, Nan, Emilio Frazzoli, Yitong Li, Yiwen Luo, Yu Wang, and Danwei Wang. "Further study on extended back-pressure traffic signal control algorithm." In 2015 54th IEEE Conference on Decision and Control (CDC). IEEE, 2015. http://dx.doi.org/10.1109/cdc.2015.7402528.

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Xiao, Nan, Emilio Frazzoli, Yiwen Luo, Yitong Li, Yu Wang, and Danwei Wang. "Throughput optimality of extended back-pressure traffic signal control algorithm." In 2015 23th Mediterranean Conference on Control and Automation (MED). IEEE, 2015. http://dx.doi.org/10.1109/med.2015.7158897.

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Liu, Zhenghui, Lixiang Liu, and Jianzhou Chen. "Two-scale geographic back-pressure algorithm for deep space networks." In 2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS). IEEE, 2017. http://dx.doi.org/10.1109/icis.2017.7959968.

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Maipradit, Arnan, Juntao Gao, Tomoya Kawakami, and Minoru Ito. "Adaptive Traffic Control Algorithm Based on Back-Pressure and Q-Learning." In 2019 IEEE Intelligent Transportation Systems Conference - ITSC. IEEE, 2019. http://dx.doi.org/10.1109/itsc.2019.8917179.

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Wang, Xinkun, and Wenbo Xu. "Hydraulic Design of Micro-Irrigation Subunit Based on Genetic Algorithm." In ASME 2010 3rd Joint US-European Fluids Engineering Summer Meeting collocated with 8th International Conference on Nanochannels, Microchannels, and Minichannels. ASMEDC, 2010. http://dx.doi.org/10.1115/fedsm-icnmm2010-30233.

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With the difference between average discharge and design discharge of emitter to be the objective function, a based-genetic-algorithm model for micro-irrigation subunit hydraulic design is established, which takes the node pressure in the submain end as a decision variable and applies bisection algorithms and back step method to handle the hydraulic calculation of submain and laterals. Simulation results show that the model and algorithm possess excellent solving efficiency, accuracy, and good versatility and practical value. In the meanwhile, it can be also obtained that discharge and pressur
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Limido, Jérôme, Mohamed Trabia, Shawoon Roy, et al. "Modeling of Hypervelocity Impact Experiments Using Gamma-SPH Technique." In ASME 2017 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/pvp2017-65517.

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A series of experiments were performed to study plastic deformation of metallic plates under hypervelocity impact at the University of Nevada, Las Vegas (UNLV) Center for Materials and Structures using a two-stage light gas gun. In these experiments, cylindrical Lexan projectiles were fired at A36 steel target plates with velocities range of 4.5–6.0 km/s. Experiments were designed to produce a front side impact crater and a permanent bulging deformation on the back surface of the target without inducing complete perforation of the plates. Free surface velocities from the back surface of target
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Demol, Thibault, Jean-Pierre Izard, and Nicolas Tartare. "Efficient Probabilistic Calculation of a Thermal Transient on a 3D FE Model With Variable Heat Exchange Coefficient." In ASME 2013 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/pvp2013-97674.

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Probabilistic calculations are often used to evaluate reliability in nuclear industry. One of their main difficulties is that failure probabilities are, in this domain, very low and therefore their computations are very long. The speed of the calculations depends on the probabilistic algorithm and the complexity of the physical problem (usually modeled by a finite element analysis). The optimization of the probabilistic algorithms benefits from a wealth of literature but the physical problem is often very simplified by a lot of approximations. This paper develops a methodology to avoid some ap
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Bartsch, Christian, Magnus Hölle, Peter Jeschke, and Timo Metzler. "Quasi 2D Flow-Adaptive Algorithm for Pneumatic Probe Measurements." In ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/gt2016-56624.

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The subject of this paper is a flow-adaptive measurement grid algorithm developed for 1D and 2D flow field surveys with pneumatic probes in turbomachinery flows. The algorithm automatically determines the distribution and the amount of measurement points needed for an approximation of the pressure distribution within a predefined accuracy. The algorithm is based on transient traverses, conducted back and forth in the circumferential direction. The dynamic response of the pressure-measuring system is disregarded during the traverses, which serve to detect changes in the pressure field. In contr
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