Journal articles: 'Measurement of network parameters'

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Rahman, F., A. Kumar, G. Nagendra, and G. S. Gupta. "Network Approach for Physiological Parameters Measurement." IEEE Transactions on Instrumentation and Measurement 54, no. 1 (February 2005): 337–46. http://dx.doi.org/10.1109/tim.2004.834595.

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Li, Xia. "The Parameters Measurement of the Network Performance." Applied Mechanics and Materials 380-384 (August 2013): 850–53. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.850.

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By using active method of injecting test flow data into the network the parameters of throughput, bandwidth, delay jitter, packet loss can be gained, UDP network performance of the single network segment can be tested. According to the measurement results, the network should be properly distributed for the access connection number and allocation of bandwidth for each client to improve the network performance.

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Bianco, Fernando L., German Naldini, Jose Amado, Santiago Chiale, and Felipe Gonzalez. "Measurement Module S parameters for vector network analyzer." IEEE Latin America Transactions 11, no. 1 (February 2013): 236–41. http://dx.doi.org/10.1109/tla.2013.6502809.

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Shahar, L., and G. Even-Tzur. "Extraction of the deterministic ingredient of a dynamic geodetic control network." Journal of Geodetic Science 2, no. 1 (January 1, 2012): 68–75. http://dx.doi.org/10.2478/v10156-011-0027-6.

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Extraction of the deterministic ingredient of a dynamic geodetic control networkA minimum constraints solution, which resolves the datum defect of a control network, is an arbitrary solution that may result in a systematic error in the estimation of the deformation parameters. This error is not derived from measurements and is usually inconsistent with the geophysical reality. A free network is affected only by errors of measurement and, therefore, a free network is an accepted way of coping with this problem. Study of deformations, which is based on the use of geodetic measurements, is usually performed today by defining a kinematic model. Such a model, when used to describe a complex geophysical environment, can lead to the partial estimation of the deterministic dynamics, which characterize the entire network. These dynamics are themselves expressed in measurements, as the adjustment systems' residuals. The current paper presents an extension of the definition of the parameters that are revalued. This extension enables the cleaning of measurements by means of the extraction of datum elements that have been defined by geodetic measurement. This cleaning minimizes the effects of these elements on the revaluated deformation. The proposed algorithm may be applied to achieve the simultaneous estimation of the physical parameters that define the geophysical activity in the network.

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Zhang, Dianjin, Guangyu Zhang, and Longqiu Li. "Calibration of a six-axis parallel manipulator based on BP neural network." Industrial Robot: the international journal of robotics research and application 46, no. 5 (August 19, 2019): 692–98. http://dx.doi.org/10.1108/ir-12-2018-0248.

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Purpose This paper aims to provide a simple and flexible calibration method of parallel manipulators for improving the position accuracy only using partial pose information. Design/methodology/approach The overall idea of this method is to use BP neural network to fit the relationship between calibration parameters and measurement parameters and then adjust calibration parameters according to measurements. Findings The calibration method significantly improves the position accuracy of the six-axis parallel manipulator. Simulation shows that the accuracy can be improved by increasing the number of positions consisted of samples to train BP neural network, and when the position number is increased, the descent velocity of fitting error is decreased. Originality/value The method is general for various parallel mechanisms and simple for measurement process. It can be applied to the calibration of various mechanisms without analyzing the mathematical relationship between measurements and calibration parameters. The measurement parameters can be flexibly selected to simplify measurement process, which saves calibration cost and time.

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Beckie, Roger. "Measurement Scale, Network Sampling Scale, and Groundwater Model Parameters." Water Resources Research 32, no. 1 (January 1996): 65–76. http://dx.doi.org/10.1029/95wr02921.

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Borovskikh, L. P., and N. G. Chitashvili. "Invariant measurement of three-element two-terminal network parameters." Measurement Techniques 33, no. 1 (January 1990): 63–67. http://dx.doi.org/10.1007/bf00866822.

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Jamróz, Dariusz, Tomasz Niedoba, Paulina Pięta, and Agnieszka Surowiak. "The Use of Neural Networks in Combination with Evolutionary Algorithms to Optimise the Copper Flotation Enrichment Process." Applied Sciences 10, no. 9 (April 29, 2020): 3119. http://dx.doi.org/10.3390/app10093119.

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The paper presents a way of combining neural networks with evolutionary algorithms in order to find optimal parameters of the copper flotation enrichment process. The neural network was used in order to build a model describing the flotation process. The network learning was carried out with the use of samples from previous empirical measurements of the actual process. The model created in this way made it possible to find optimal parameters not only from among the measurement spaces, but also those that go beyond the measurements. Then, evolutionary algorithms were used in order to find optimal flotation parameters. The learned neural network previously described was used to calculate the criterion in the evolutionary algorithm.

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LIU, ZAIWEN, XIAOYI WANG, and LIFENG CUI. "AN INTELLIGENT SOFT MEASUREMENT METHOD FOR PREDICTING PARAMETERS." International Journal of Information Acquisition 04, no. 01 (March 2007): 47–56. http://dx.doi.org/10.1142/s0219878907001150.

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An intelligent soft measurement and information processing method for predicting parameters of process control system was proposed. Process neural network (PNN) is a new configuration of artificial neural network put forward in recent years. Some algorithms of PNN were discussed, and these algorithms were based on function orthogonal basis expansion, yet the convergence rate was comparatively low. An improved algorithm for raising training speed based on function orthogonal basis expansion in PNN for soft measurement was researched. After increasing the normalizing rule on the original algorithm, and introducing function momentum adjustment item and learning rate automatically adjustment method for network weight function, the training time of learning algorithm for PNN was reduced, and a good result was represented by simulation in wastewater treatment system.

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Staszek, Kamil, Slawomir Gruszczynski, and Krzysztof Wincza. "Tunable multiport system for measurement of two-port scattering parameters." International Journal of Microwave and Wireless Technologies 9, no. 1 (August 17, 2015): 99–112. http://dx.doi.org/10.1017/s1759078715001312.

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A novel multiport system, allowing for measurements of scattering parameters in over-two-octave frequency range is proposed. It is composed of two directional couplers and a standard 4 × 4 Butler matrix, and does not require any isolators. The presented system features a uniform power distribution providing the high precision of measurements, which can be further enhanced by a simple adjustment of the system's parameters. A comprehensive analysis of the proposed system configurations, a fully analytical calibration for transmission coefficient measurement, and the estimation of maximum measurement error are given. The proposed measuring system has been experimentally verified in a wide frequency range 1–5 GHz, by measurements of S-parameters of exemplary components. The measurement results are very close to the values obtained with the use of a commercial vector network analyser within the 50 dB range of measured values’ magnitude.

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Leskelä, Lasse. "Stabilization of an Overloaded Queueing Network Using Measurement-Based Admission Control." Journal of Applied Probability 43, no. 01 (March 2006): 231–44. http://dx.doi.org/10.1017/s0021900200001492.

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Admission control can be employed to avoid congestion in queueing networks subject to overload. In distributed networks, the admission decisions are often based on imperfect measurements on the network state. In this paper, we study how the lack of complete state information affects the system performance, by considering a simple network model for distributed admission control. The stability region of the network is characterized and it is shown how feedback signaling makes the system very sensitive to its parameters.

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Leskelä, Lasse. "Stabilization of an Overloaded Queueing Network Using Measurement-Based Admission Control." Journal of Applied Probability 43, no. 1 (March 2006): 231–44. http://dx.doi.org/10.1239/jap/1143936256.

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Admission control can be employed to avoid congestion in queueing networks subject to overload. In distributed networks, the admission decisions are often based on imperfect measurements on the network state. In this paper, we study how the lack of complete state information affects the system performance, by considering a simple network model for distributed admission control. The stability region of the network is characterized and it is shown how feedback signaling makes the system very sensitive to its parameters.

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Yeom, Kyung-Whan, and Abdule-Rahman Ahmed. "Measurement of Noise Parameters Using 6-Port Network (Invited Paper)." Journal of Korean Institute of Electromagnetic Engineering and Science 26, no. 2 (February 27, 2015): 119–26. http://dx.doi.org/10.5515/kjkiees.2015.26.2.119.

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Davis, W. A., C. F. Bunting, and S. E. Bucca. "Measurement and analysis for stripline material parameters using network analyzers." IEEE Transactions on Instrumentation and Measurement 41, no. 2 (April 1992): 286–90. http://dx.doi.org/10.1109/19.137362.

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Tretyak, Kornyliy, and Igor Savchyn. "Posteriori Optimization of Active Geodetic Monitoring Networks." Reports on Geodesy and Geoinformatics 96, no. 1 (June 1, 2014): 67–77. http://dx.doi.org/10.2478/rgg-2014-0007.

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Abstract This paper presents developed method of a posteriori optimization of measurement results of active geodesic monitoring networks with taking into account the parameters of accuracy and reliability. Filtering the measurement results of active geodetic monitoring networks is in out of order exclusion vectors with maximum corrections, which is determined from successive iterations of network adjustment. After each iteration it’s determined the mean square error of unit weight and the parameter of network reliability. Sifting vectors with maximal errors leads to accuracy improving and reliability deterioration of network. Using entropy approach is defined group of vectors in which the value of accuracy and reliability is optimal. Using the developed method performed a posteriori optimization of active precision geodesic monitoring network of the Dnieper, Dniester and Kanev HPP. The represented method can also be used for the optimization of any active geodesic monitoring networks with large quantity of redundant measurements

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Kerneis, A., A. Déguin, and M. Feinberg. "A colony count model for the control of drinking water distribution systems." Revue des sciences de l'eau 9, no. 2 (April 12, 2005): 189–205. http://dx.doi.org/10.7202/705248ar.

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The purpose of this study is to select a process control parameter for monitoring microbial regrowth in a network and to develop a more accurate and relevant quality control of supply water. Two parameters were examined as potential process control parameters: the water residence time in the network and the concentration of biodegradable organic matter. Residence time calculations were carried out and validated by tracer studies in a branched network and then in a simply looped network. The measurement of the natural dissolved organic carbon (DOC) consumption in the network was preferred to the determination of any in vitro biodegradation. The measurement of consumption requires the determination of DOC in treated water and in supply water. It is simpler and less expensive than other biodegradable organic matter determinations. A model for colony counts as a function of the residence time was developed in order to demonstrate that this parameter can be used for process controlling. This model was very well adjusted to data collected in a network in winter, spring and summer. This process control parameter was then used in order to locate and estimate the quantity of water whose colony counts exceed the European directive guide level. Accurate correlation measurements between colony counts and DOC consumed in the network were carried out in three distinct systems. No significant correlations were measured. For these three networks, biodegradable organic matter measurements based on DOC determinations were demonstrated to be unreliable process control parameters for monitoring bacterial regrowth.

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Kalyuzhniy, D. "Identification of the parameters of equivalent circuits of connections of the electric network in the problem of distribution of their actual contributions." Lighting engineering and power engineering 1, no. 57 (2020): 33–38. http://dx.doi.org/10.33042/2079-424x-2020-1-57-33-38.

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One of the current problems of modern electricity is the distribution of actual contributions for lowering the quality of electricity at the point of general connection of electricity networks. Despite the large number of developed methods to address this issue, their adequacy depends on the accuracy of identification of the parameters of the schemes of replacement of elements of the electrical network. In this regard, the article considers the problem of identifying the parameters of equivalent schemes of replacement of the power system, mixed passive and active loads, taking into account the sources of electricity in their composition. Two approaches were considered to obtain the initial data on parametric identification. The first of them is based on local measurements of the parameters of the electrical network. The second - on distributed measurements. As a result, the areas of solution of this problem for each of the types of organization of measuring systems taking into account the active intervention in the operation of the electrical network are identified. Methods of approximate calculation of parameters of passive mixed load substitution schemes in three-phase three- and four-wire electric networks, which are based on local measurements, are determined. Methods of exact calculation of parameters of schemes of substitution of electric power system and active mixed loading which are based on the distributed measurements are defined. In addition, the requirements for the organization of a distributed measurement system, which are based on the use of a full-fledged system of SmartGrid with additional application of methods and tools of vector measurement and system of SCADA. Key words - point of common connection; equivalent substitution sema; identification of parameters of the substitution scheme; mixed load; power system.

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Simić, Milan, Peter Planinšič, Dragan Denić, Dušan Gleich, Dragan Živanović, and Marko Malajner. "SOFTWARE BASED EXPERIMENTAL SYSTEM FOR ELECTRICAL POWER QUALITY MEASUREMENT USING THE WIRELESS SENSOR NETWORK MODULES." Facta Universitatis, Series: Automatic Control and Robotics 16, no. 2 (October 24, 2017): 131. http://dx.doi.org/10.22190/fuacr1702131s.

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Experimental system for measurement of standard electrical power quality (PQ) parameters, based on wireless sensor network (WSN), is presented in this paper. System includes generator of reference voltage waveforms, software application for measurement of standard PQ parameters and two microcontroller based wireless sensor modules for transmitting and receiving of measurement results. Reference voltage signals are provided using signal generator with possibility for simulation of typical network disturbances, presented in some previously published papers. This PQ signal generator is functionally supported by the virtual instrumentation software and data acquisition card. Measurements of basic quality parameters for reference test signals are performed using the LabVIEW software application. Time interval for each measurement cycle is 1 s. For communication is used wireless sensor network based on communication standard IEEE 802.15.4 (Zigbee). Hardware configuration includes two wireless sensor modules SPaRCMosquito v.2, based on the microcontroller with Cortex M3 architecture. Transfer of measurement results, between computer and wireless sensor modules on transmitter and receiver points, are provided using standard USB interface.

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Liu, Xing, Xian Yan Chen, Yuan Lin, Long Fang Ye, Fen Xiao, and Qing Huo Liu. "A Coaxial Measurement System for Electromagnetic Parameters at Microwave Frequencies." Advanced Materials Research 881-883 (January 2014): 1832–35. http://dx.doi.org/10.4028/www.scientific.net/amr.881-883.1832.

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In this paper, an improved coaxial measurement system with a newly designed coaxial fixture is presented. The electromagnetic parameters of samples are retrieved from the scattering parameters measured by a vector network analyzer (VNA) at microwave frequencies. The measurements of air and PTFE in the range of 1~6 GHz were carried out to verify the reliability and the accuracy of this measurement system. By using frequency-sweep and data processing techniques, the multiplicity of roots is eliminated. The results show that this system can effectively be applied to measure the material electromagnetic parameters of absorbing materials with high accuracy in a wide frequency band.

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Zaidan, Martha A., Ola Surakhi, Pak Lun Fung, and Tareq Hussein. "Sensitivity Analysis for Predicting Sub-Micron Aerosol Concentrations Based on Meteorological Parameters." Sensors 20, no. 10 (May 19, 2020): 2876. http://dx.doi.org/10.3390/s20102876.

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Sub-micron aerosols are a vital air pollutant to be measured because they pose health effects. These particles are quantified as particle number concentration (PN). However, PN measurements are not always available in air quality measurement stations, leading to data scarcity. In order to compensate this, PN modeling needs to be developed. This paper presents a PN modeling framework using sensitivity analysis tested on a one year aerosol measurement campaign conducted in Amman, Jordan. The method prepares a set of different combinations of all measured meteorological parameters to be descriptors of PN concentration. In this case, we resort to artificial neural networks in the forms of a feed-forward neural network (FFNN) and a time-delay neural network (TDNN) as modeling tools, and then, we attempt to find the best descriptors using all these combinations as model inputs. The best modeling tools are FFNN for daily averaged data (with R 2 = 0.77 ) and TDNN for hourly averaged data (with R 2 = 0.66 ) where the best combinations of meteorological parameters are found to be temperature, relative humidity, pressure, and wind speed. As the models follow the patterns of diurnal cycles well, the results are considered to be satisfactory. When PN measurements are not directly available or there are massive missing PN concentration data, PN models can be used to estimate PN concentration using available measured meteorological parameters.

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Wilkins, J., M. V. Nguyen, and B. Rahmani. "Application of Convolutional Neural Network In LAWN Measurement." Signal & Image Processing : An International Journal 12, no. 1 (February 28, 2021): 1–8. http://dx.doi.org/10.5121/sipij.2021.12101.

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Lawn area measurement is an application of image processing and deep learning. Researchers used hierarchical networks, segmented images, and other methods to measure the lawn area. Methods’ effectiveness and accuracy varies. In this project, deep learning method, specifically Convolutional neural network, was applied to measure the lawn area. We used Keras and TensorFlow in Python to develop a model that was trained on the dataset of houses then tuned the parameters with GridSearchCV in ScikitLearn (a machine learning library in Python) to estimate the lawn area. Convolutional neural network or shortly CNN shows high accuracy (94 -97%). We may conclude that deep learning method, especially CNN, could be a good method with a high state-of-art accuracy.

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Chudzik, Stanisław, and Waldemar Minkina. "An Idea of a Measurement System for Determining Thermal Parameters of Heat Insulation Materials." Metrology and Measurement Systems 18, no. 2 (January 1, 2011): 261–74. http://dx.doi.org/10.2478/v10178-011-0008-2.

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An Idea of a Measurement System for Determining Thermal Parameters of Heat Insulation MaterialsThe article presents the prototype of a measurement system with a hot probe, designed for testing thermal parameters of heat insulation materials. The idea is to determine parameters of thermal insulation materials using a hot probe with an auxiliary thermometer and a trained artificial neural network. The network is trained on data extracted from a nonstationary two-dimensional model of heat conduction inside a sample of material with the hot probe and the auxiliary thermometer. The significant heat capacity of the probe handle is taken into account in the model. The finite element method (FEM) is applied to solve the system of partial differential equations describing the model. An artificial neural network (ANN) is used to estimate coefficients of the inverse heat conduction problem for a solid. The network determines values of the effective thermal conductivity and effective thermal diffusivity on the basis of temperature responses of the hot probe and the auxiliary thermometer. All calculations, like FEM, training and testing processes, were conducted in the MATLAB environment. Experimental results are also presented. The proposed measurement system for parameter testing is suitable for temporary measurements in a building site or factory.

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Kim, Jongmin, Duc Long Luong, Wansoo Nah, and SoYoung Kim. "Measurement of Multi-Port S-Parameters using Four-Port Network Analyzer." JSTS:Journal of Semiconductor Technology and Science 13, no. 6 (December 31, 2013): 589–93. http://dx.doi.org/10.5573/jsts.2013.13.6.589.

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Kubrak, O. N. "Measurement of dielectric parameters with the aid of automatic network analyzers." Measurement Techniques 30, no. 1 (January 1987): 87–90. http://dx.doi.org/10.1007/bf00865737.

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Yun, Xu, Su Yan, Zhu Xinhua, and Luo Zhihang. "Network dynamic field calibration for micro inertial measurement unit." Transactions of the Institute of Measurement and Control 41, no. 10 (December 19, 2018): 2826–37. http://dx.doi.org/10.1177/0142331218811465.

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Calibration accuracy of micro inertial measurement unit (MIMU) will affect the navigation accuracy of micro strap-down inertial navigation system. Generally, when the application environment changes (i.e. environment temperature and humidity), the specific force and angular rate output by MIMU will be changed, which were influenced by the zero bias of accelerometers, the zero drift of gyroscopes and so on. Thus, it is necessary to carry out the field calibration for MIMU. Aiming at the application of multi MIMUs, the network dynamic field calibration method is proposed in this paper. According to the navigation attitude and velocity error models, the estimating model is established. Then, the observability for the parameters in the estimating model is analyzed. By fusing the output information of MIMUs and GPS, vehicle experiments are carried out with the designed maneuvers in order to estimate the parameters. The experiment result illustrated that the proposed network dynamic filed calibration can efficiently realize the calibration for the parameters in the model of several MIMUs simultaneously.

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Alasl, M. Kashefi, M. Khosravi, M. Hosseini, G. R. Pazuki, and R. Nezakati Esmail Zadeh. "Measurement and mathematical modelling of nutrient level and water quality parameters." Water Science and Technology 66, no. 9 (November 1, 2012): 1962–67. http://dx.doi.org/10.2166/wst.2012.333.

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Physico-chemical water quality parameters and nutrient levels such as water temperature, turbidity, saturated oxygen, dissolved oxygen, pH, chlorophyll-a, salinity, conductivity, total nitrogen and total phosphorus, were measured from April to September 2011 in the Karaj dam area, Iran. Total nitrogen in water was modelled using an artificial neural network system. In the proposed system, water temperature, depth, saturated oxygen, dissolved oxygen, pH, chlorophyll-a, salinity, turbidity and conductivity were considered as input data, and the total nitrogen in water was considered as output. The weights and biases for various systems were obtained by the quick propagation, batch back propagation, incremental back propagation, genetic and Levenberg–Marquardt algorithms. The proposed system uses 144 experimental data points; 70% of the experimental data are randomly selected for training the network and 30% of the data are used for testing. The best network topology was obtained as (9-5-1) using the quick propagation method with tangent transform function. The average absolute deviation percentages (AAD%) are 2.329 and 2.301 for training and testing processes, respectively. It is emphasized that the results of the artificial neural network (ANN) model are compatible with the experimental data.

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Hartawan, I. Nyoman Buda, and I. Gusti Made Ngurah Desnanjaya. "ANALISIS KINERJA PROTOKOL ZIGBEE DI DALAM DAN DI LUAR RUANGAN SEBAGAI MEDIA KOMUNIKASI DATA PADA WIRELESS SENSOR NETWORK." Jurnal RESISTOR (Rekayasa Sistem Komputer) 1, no. 2 (October 28, 2018): 65–72. http://dx.doi.org/10.31598/jurnalresistor.v1i2.320.

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Wireless sensor network is a technology used in supporting monitoring activities both inside and outside environment. Data communication on wireless sensor networks is done wirelessly. The Zigbee protocol is one of the protocols used in data communication on wireless sensor networks as an implementation of XBEE devices. In this study measurement of Zigbee protocol performance on XBEE devices inside and outside environment. The measurement conditions in the room are limited by the wall partition, while the outdoor conditions are line of sight. Measurements were made by sending packet data using XCTU software, by testing distance parameters, packet delay, packet loss, RSSI, and throughput with 84 Bytes packet data size. The results showed that the measurement results of XBEE Pro S2 devices that were carried out indoors were able to communicate with a maximum distance of 30 meters, while the outdoor measurements showed the communication capability of XBEE Pro S2 devices reached a maximum distance of 600 meters.

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Rolfes, I., B. Will, and B. Schiek. "Calibration-measurement unit for the automation of vector network analyzer measurements." Advances in Radio Science 6 (May 26, 2008): 27–30. http://dx.doi.org/10.5194/ars-6-27-2008.

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Abstract. With the availability of multi-port vector network analyzers, the need for automated, calibrated measurement facilities increases. In this contribution, a calibration-measurement unit is presented which realizes a repeatable automated calibration of the measurement setup as well as a user-friendly measurement of the device under test (DUT). In difference to commercially available calibration units, which are connected to the ports of the vector network analyzer preceding a measurement and which are then removed so that the DUT can be connected, the presented calibration-measurement unit is permanently connected to the ports of the VNA for the calibration as well as for the measurement of the DUT. This helps to simplify the calibrated measurement of complex scattering parameters. Moreover, a full integration of the calibration unit into the analyzer setup becomes possible. The calibration-measurement unit is based on a multiport switch setup of e.g. electromechanical relays. Under the assumption of symmetry of a switch, on the one hand the unit realizes the connection of calibration standards like one-port reflection standards and two-port through connections between different ports and on the other hand it enables the connection of the DUT. The calibration-measurement unit is applicable for two-port VNAs as well as for multiport VNAs. For the calibration of the unit, methods with completely known calibration standards like SOLT (short, open, load, through) as well as self-calibration procedures like TMR or TLR can be applied.

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Gusinsky, A. V. "GENERALIZED MATHEMATICAL MODEL OF THE CALIBRATION PROCESSAND THE DIRECT MEASUREMENT OF THE PARAMETERS MULTIPOLE." Devices and Methods of Measurements 9, no. 1 (March 20, 2018): 96–105. http://dx.doi.org/10.21122/2220-9506-2018-9-1-96-105.

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The quality of measuring systems of the microwave range, including vector network analyzers, largely depends on the reliability of calibration procedures and direct measurements, which allow to take into account information about the reproducible errors of measuring systems for subsequent correction. The aim of the paper is mathematical modeling of the errors of the measuring system for the generalized case for 2-n pole device.The problems of increasing the accuracy of measuring microwave systems due to compensation of systematic errors determined during calibration are considered. Calibration of measuring systems and correction of the results of direct measurements based on calibration results require the use of appropriate mathematical models of errors. Mathematical models of errors are represented in the form of multipolar errors, included between the object of measurement and the measuring system, which is assumed to be ideal, free of errors. The article proposes a generalized mathematical model of errors, described by a network of errors containing n ports connected to the n-port measuring system, and n ports connected to the n port of the measurement object. To obtain in general form the calibration equation for the 2n-port model of the error multipolar network, its transmission wave matrix [T], recorded in a cellular form, was used, and then a relationship was found between the measurement result in a matrix form with the cellular wave matrix T. A solution for finding the error matrix of matrix equation that connects the matrices known from the results of the corresponding attestation for the standards with the results of measurements during calibration in the matrix form. When solving this equation, a matrix product of «sandwich» type appears due to the cellular wave matrix [T]. The solution is possible when using the Kronecker product of two matrix, the matrix translation operator, the RS operator of the matrix, and the Gaussian elimination method. An equation is obtained for reconstructing the actual values of the scattering matrix of the measurement object, starting from the results of direct measurements in the matrix form and the error matrix. When solving the reconstruction equation, it is advisable to use a matrix inverse to the transmission matrix [T].The developed generalized mathematical model can be used, for example, when it is necessary to measure the parameters of complex microwave devices made on boards (wafer), with probe transitions to measuring ports, where it is important to consider the presence of additional microwave power leaks between ports.

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Yu Zhijing, 于之靖, and 潘晓 Pan Xiao. "Camera Internal-Parameters Calibration Based on the Construction of Initial Measurement Network." Acta Optica Sinica 32, no. 11 (2012): 1112003. http://dx.doi.org/10.3788/aos201232.1112003.

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Li, Wenzhi, Jing Wang, Zesong Fei, Yuqiao Ren, Xiao Yang, and Xiaoqi Wang. "Radio Link Parameters Based QoE Measurement of Voice Service in GSM Network." Communications and Network 05, no. 03 (2013): 448–54. http://dx.doi.org/10.4236/cn.2013.53b2083.

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Li, Xia, and Sheng Xun Wang. "The Research and Implementation of TCP Measurement Technology." Applied Mechanics and Materials 220-223 (November 2012): 3020–23. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.3020.

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This article gives the outline of the method of TCP measurement, and the open source codes are combined to make the active measurement for TCP into reality. Some network parameters such as throughput, bandwidth and TCP windows size can be measured to show the performance of the network. Accordingly the network stream can be observed, the network capacity and the performance is determined so that the network can provide higher QOS.

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Vasjanov, Aleksandr, and Vaidotas Barzdenas. "A Methodology Improving Off-Chip, Lumped RF Impedance Matching Network Response Accuracy." Electronics 7, no. 9 (September 10, 2018): 188. http://dx.doi.org/10.3390/electronics7090188.

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Impedance matching is concurrent with any radio frequency (RF) circuit design and is essential for maximizing the gain and efficiency while minimizing the noise of high-frequency amplifiers as well as some mixer topologies. The main impedance matching network components are capacitors, inductors, and RF transformers all of which contain parasitic parameters that influence the matching response S11 curve. After calculating matching network component values using classical matching techniques, the measured and simulated response curves differ depending on the target frequency. This results in multiple calculations and measurement cycles in order to precisely match the source and load at the desired frequency. This article proposes an algorithm and methodology of estimating component parasitic parameters and taking them into account when calculating the main component parameters (capacitance and inductance). The proposed algorithm has been implemented as a toolbox in Cadence Virtuoso and verified through simulation and measurements. Measurement results show, that at 500 MHz 10% tolerance components with parasitics included and values based on classical theory provide a 3.2–9.8% offset from the target frequency. In the same conditions, matching networks with compensated (according to the proposed algorithm) values provide 0.1–8.8% target frequency offset. At 1500 MHz 10% components provided 4–12.3% (non-compensated) and 1–8.7% (compensated) target frequency offset ranges. At 3000 MHz. The frequency offset range of using compensated matching network component values is reduced from 5.5–15.1% to 1.3–8.1%.

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Zabłudowski, Łukasz, Beata Marciniak, Damian Ledziński, and Mirosław Maszewski. "Reliability in Low Emission Wireless Measurement Networks." Solid State Phenomena 237 (August 2015): 107–11. http://dx.doi.org/10.4028/www.scientific.net/ssp.237.107.

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Wireless sensor networks called WSN’s increasingly find their wide application in various distributed measurement systems. Currently, many manufacturers focus on implementation of these devices in energy meters. In addition these devices are increasingly being considered as a system that do not carry big financial effort to be implement as a measuring systems of key safety parameters in production environments. Such environments are becoming an important element to ensure reliable transmission between measuring devices broadcasting. Another challenge in the systems under consideration is to provide low emissivity in the network. The low emissivity provides less interference between operating devices. This premise has an important effect on networks with large numbers of nodes.

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Tan, Ming Gui, Yean Chun Tea, Jee-Hou Ho, Hui-Ting Goh, Hoon Kiat Ng, and Ing Kong. "A motion sensor network for quantitative gait measurement." World Journal of Engineering 12, no. 6 (December 1, 2015): 619–26. http://dx.doi.org/10.1260/1708-5284.12.6.619.

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Quantitative gait analysis is an important research area to enable physiotherapist to perform systematic studies and health diagnosis of the lower extremity of patients throughout the rehabilitation. The quantitative measurement of ambulatory gait can be performed by using convenient and economical wearable sensors outside specialized motion laboratories. In this paper, a sensor system consisting of three tri-axial accelerometers, two flex sensors and four force sensors was developed. Subject testing were carried out to obtain temporal and spatial gait parameters. The performance of the sensor suite is compared to results from camera videos analysed by Kinovea motion tracking software.

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Ahmed, Abdul-Rahman, Dong-Hyun Lee, and Kyung-Whan Yeom. "On-wafer noise parameters measurement using an extended six-port network and conventional noise figure analyzer." International Journal of Microwave and Wireless Technologies 9, no. 4 (September 9, 2016): 821–29. http://dx.doi.org/10.1017/s1759078716000842.

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In this paper, we demonstrate the successful implementation of an onwafer noise parameters test set that employs an extended six-port network and a conventional noise figure analyzer. The necessary formulation that enables the calibration of the noise parameter test set as well as extraction of the noise wave correlation matrix of a two-port device under test (DUT) was tested for coaxial connector-type DUT measurement in an earlier work but not for onwafer-type DUT. Furthermore, we demonstrate the performance of this technique against data obtained from the well-known tuner method. Measurement carried out for very low-noise figure (2 dB) onwafer-type amplifier demonstrates the capability of our technique. The measured noise parameters show fluctuations in minimum noise figure, NFminof ±0.1 dB, and in noise resistance Rnof about 2%. This test set is simple and fast leading to tremendous time- and cost-savings as well as a simplified procedure in onwafer noise parameters measurements.

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Vladislavić, Đani, Darko Huljenić, and Julije Ožegović. "Virtual Network Resource Optimization Model for Network Function Virtualization." Wireless Communications and Mobile Computing 2021 (August 17, 2021): 1–21. http://dx.doi.org/10.1155/2021/9928210.

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Network function virtualization (NFV) is a concept aimed at achieving telecom grade cloud ecosystem for new-generation networks focusing on capital and operational expenditure (CAPEX and OPEX) savings. This study introduces empirical throughput prediction model for the virtual network function (VNF) and network function virtualization infrastructure (NFVI) architectures based on Linux kernel. The model arises from the methodology for performance evaluation and modeling based on execution area (EA) distribution by CPU core pinning. EA is defined as a software execution unit that can run isolated on a compute resource (CPU core). EAs are derived from the elements and packet processing principles in NFVIs and VNFs based on Linux kernel. Performing measurements and observing linearity of the measured results open the possibility to apply model calibration technique to achieve general VNF and NFVI architecture model with performance prediction and environment setup optimization. The modeling parameters are derived from the cumulative packet processing cost obtained by measurements for collocated EAs on the CPU core hosting the bottleneck EA. The VNF and NFVI architecture model with performance prediction is successfully validated against the measurement results obtained in emulated environment and used to predict optimal system configurations and maximal throughput results for different CPUs.

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Zhai, Weifang, Yongli Liu, and Yiran Jiang. "Research on Integrated Parameter Measurement and Control System of Low Voltage Distribution Network." International Journal of Advanced Pervasive and Ubiquitous Computing 9, no. 3 (July 2017): 32–46. http://dx.doi.org/10.4018/ijapuc.2017070103.

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In order to ensure the safe operation of the distribution network and to understand the operation of the distribution network, it is necessary to monitor the various operating parameters of the distribution network in real time and to send the various measurement parameters to the dispatching and monitoring center in time. So the low-voltage distribution network integrated parameter measurement and control has been widely used. This paper introduces a design method of combining two sets of reactive power compensator and distribution network measuring and controlling device into one part. The distribution network measurement and control, power factor correction and reactive power compensation are realized. In a word, the system has simple structure, high precision, and strong anti-interference ability, among other advantages, with great market potential.

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Hrbac, Roman, Vaclav Kolar, Mikolaj Bartlomiejczyk, Tomas Mlcak, Petr Orsag, and Jakub Vanc. "A Development of a Capacitive Voltage Divider for High Voltage Measurement as Part of a Combined Current and Voltage Sensor." Elektronika ir Elektrotechnika 26, no. 4 (August 7, 2020): 25–31. http://dx.doi.org/10.5755/j01.eie.26.4.25888.

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This article deals with the development of capacitive voltage divider for high voltage measurements and presents a method of analysis and optimization of its parameters. This divider is a part of a combined voltage and current sensor for measurements in high voltage power networks. The sensor allows continuous monitoring of the network distribution status and performs a quick diagnosis and location of possible network failures. Deployment of these devices will support semi-autonomous control of power networks and it can be considered as a step from traditional power grids toward smart grids. This is a worldwide trend connected with increasing number of renewable energy sources and plug-in electric vehicles as described in. In this way, it contributes to the reliability of the distribution network. Together with automated control techniques and fault location methods, it enables its self-healing capability. The following characteristics required for the sensor include: current measurement error up to 2 %, voltage measurement error up to 0.5 %, and power measurement error up to 5 %. At the same time, it is necessary that the sensor is cost-effective - relatively cheap. There were selected capacitors made in series production for the capacitive divider designing. The capacitive voltage divider was tested in terms of time and temperature stability; the results are described in the paper. Then, the method of mathematical correction of a temperature dependence of the capacitive voltage divider was suggested and tested.

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Häck, Michael, and Manfred Köhne. "Estimation of wastewater process parameters using neural networks." Water Science and Technology 33, no. 1 (January 1, 1996): 101–15. http://dx.doi.org/10.2166/wst.1996.0010.

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The use of on-line process analyzers for continuous measurement of wastewater components is often accompanied by unpredictable breakdown or necessary maintenance work at the analyzers, leading to fault time in the measurements. In this paper a new method is presented, allowing the approximate calculation or estimation of those process parameters which are temporarily not available. The calculation is based on auxiliary parameters; the results can be used for process control. Therefore, besides the output of the process analyzers, easily and directly measurable auxiliary parameters are determined. The correlations between these auxiliary parameters and the process parameters actually of interest (COD, NH4, etc.) are detected and used for the estimation of the process parameters in case of a breakdown. Information processing is executed by a neural network, enabling the detection of non-linear static or dynamic correlations, based only on information given by the measured values. The network is trained by data recorded before the breakdown of an on-line analyzer. By this, an optimal adaptation to the current wastewater composition is possible. This method was tested on a municipal wastewater treatment plant near Siegen (Germany). The results obtained are presented in this paper.

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Carpenter, Chris. "Artificial Neural Network Models and Predicts Reservoir Parameters." Journal of Petroleum Technology 73, no. 01 (January 1, 2021): 44–45. http://dx.doi.org/10.2118/0121-0044-jpt.

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This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper IPTC 19854, “Modeling and Prediction of Resistivity, Capillary Pressure, and Relative Permeability Using Artificial Neural Network,” by Mustafa Ba alawi, SPE, King Fahd University of Petroleum and Minerals; Salem Gharbi, SPE, Saudi Aramco; and Mohamed Mahmoud, King Fahd University of Petroleum and Minerals, prepared for the 2020 International Petroleum Technology Conference, Dhahran, Saudi Arabia, 13–15 January. The paper has not been peer reviewed. Copyright 2020 International Petroleum Technology Conference. Reproduced by permission. Capillary pressure and relative permeability are essential measurements that affect multiphase fluid flow in porous media directly. The processes of measuring these parameters, however, are both time-consuming and expensive. Artificial-intelligence methods have achieved promising results in modeling extremely complicated phenomena in the industry. In the complete paper, the authors generate a model by using an artificial-neural-network (ANN) technique to predict both capillary pressure and relative permeability from resistivity. Capillary Pressure and Resistivity Capillary pressure and resistivity are two of the most significant parameters governing fluid flow in oil and gas reservoirs. Capillary pressure, the pressure difference over the interface of two different immiscible fluids, traditionally is measured in the laboratory. The difficulty of its calculation is related to the challenges of maintaining reservoir conditions and the complexity of dealing with low-permeability and strong heterogeneous samples. Moreover, unless the core materials are both available and representative, a restricted number of core plugs will lead to inadequate reservoir description. On the other hand, resistivity can be obtained by either lab-oratory analysis or through typical and routine well-logging tools in real time. Both parameters have similar attributes, given their dependence on wetting-phase saturation. Despite many studies in the literature that are reviewed in the complete paper, improvement of capillary pressure and resistivity modeling remains an open research area. Artificial Intelligence in Petroleum Engineering In addition to labor and expense concerns, conventional methods to measure resistivity, capillary pressure, and relative permeability depend primarily, with the exception of resistivity from well logs, on the availability of core samples of the desired reservoir. The literature provides several attempts to model these parameters in order to avoid many of the requirements of measurement. However, the performance of many of these models is restricted by assumptions and constraints that require further processing. For example, the accuracy of prediction of capillary pressure from resistivity is highly dependent on the tested core permeability, which requires measuring it as well to achieve the full potentiality of the model.

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Sun hongbing, Yu along, and Li zheng. "The Automatic Multiple Parameters Measurement System of Engine Based on Wireless Sensor Network." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 4, no. 20 (November 30, 2012): 250–58. http://dx.doi.org/10.4156/aiss.vol4.issue20.30.

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Tong, L., Y. Tian, Q. Y. Wang, and Y. S. Ling. "The Calibrating Theory in the Network Parameters Measurement of Microwave and MMW Devices." International Journal of Infrared and Millimeter Waves 27, no. 9 (May 8, 2007): 1307–14. http://dx.doi.org/10.1007/s10762-006-9131-6.

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Chae, Namyi, Heekwon Yang, Bang Yong Lee, and Chankil Lee. "Measurement of environmental parameters in polar regions based on a ubiquitous sensor network." Cold Regions Science and Technology 123 (March 2016): 22–31. http://dx.doi.org/10.1016/j.coldregions.2015.11.003.

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Yan, Li Wen, and Qi Bao He. "The Study of Error Separation in On-Site Measurement Based on Bayesian Network." Applied Mechanics and Materials 229-231 (November 2012): 1369–72. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.1369.

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The measurement error contains many errors in NC machine tools processing and those errors will be mapped to workpiece at certain regularity. The control of error caused by cutting parameters during the precision and ultra precision process is one of the key technologies in NC machine tools processing. This article introduces Bayesian networks into the dynamic error separation modeling, with the learning process of Bayesian network structure and establishes the error separation model based on Bayesian networks, then carries out the comparison and analysis between simulate and experimental data to verify the feasibility of the method.

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Vanin, Valery, Alexandr Bulychov, Maxim Popov, Olga Vasilyeva, and Maria Shakhova. "Measurement of currents and voltages non-sinusoidal parameters in power supply systems with rectifier load." MATEC Web of Conferences 245 (2018): 06007. http://dx.doi.org/10.1051/matecconf/201824506007.

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The use of frequency-controlled electric drives in industry and municipal services is accompanied by the problem of their negative impact on the distribution network. As examples, the results of measurements of power quality indices in the power supply system of an oil producing enterprise and on the supply input of a railway traction substation are given. It is shown that the voltage subgroup total harmonic distortions (THDS) can exceed their rated permitted values in 100% of the measurement time.

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Glubokov, Alexander Vladimirovich, Svetlana Vladimirovna Glubokova, Alexey Vileninovich Shulepov, and Sergey Evgenievich Ped. "Spectral Parameters of Straightness Deviation Evaluation." Materials Science Forum 876 (October 2016): 74–79. http://dx.doi.org/10.4028/www.scientific.net/msf.876.74.

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Spectral analysis of different profiles obtained during straightness deviation measurement was performed. The several profiles are showed, for which the value of straightness deviation is the same, but its behavior differs greatly. Spectral parameters characterizing the type of straightness deviation are proposed. The automated system based on factors of fuzzy-set theory with implementation in the form of neural network is developed.

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Hu, Qizhou, and Minjia Tan. "A KIND OF COORDINATED EVOLUTION MEASUREMENT MODEL FOR TRAFFIC NETWORK BASED ON COMPLEXITY DEGREE." Transport 35, no. 4 (October 6, 2020): 389–400. http://dx.doi.org/10.3846/transport.2020.13626.

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Coordinated evolution is a process with complexity, temporality, spatiality, and continuity. The existed methods cannot relevantly satisfy and measure the degree of coordinated evolution in real conditions. Aiming at solving the coordinated evolution problems for the urban traffic network, the information complexity must be evaluated, this paper uses the multi-dimensional connection number for compressing the factors of traffic network. Firstly, the basic characteristics of traffic network are analysed on the definition of traffic information complexity. The traffic network measurement model is established based on the information entropy, and the coordinated evolution rocess of the multi-layer urban traffic network is analysed for defining the ordered parameters of the traffic network. Then the coordinated measurement model for the multi-layer traffic network is constructed by the ordered parameters. In addition, we set up a coordinated evolution model according to the proposed estimation criteria of the ordered parameters and the theory of the multi-dimensional connection numbers. The case analysis shows that the order degree of Hangzhou traffic network is 0.7929, which approaches to 1 as while the comprehensive coordinated index of Hangzhou multi-layer traffic network is 0.3323, which clearly and intuitively gives a measurement value for the multi-layer urban traffic network. The result is also effectively verified the validity of the proposed models.

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Seleznev, Vadim E. "Numerical Adaptation of Pipeline Network Models on Measurement Archive." ISRN Applied Mathematics 2014 (February 9, 2014): 1–6. http://dx.doi.org/10.1155/2014/146591.

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We propose an adaptation method for gas dynamic pipeline network models to enable credible representation of actual properties of real simulation objects. The presentation is illustrated by fitting equivalent pipeline section roughnesses used in the models to accommodate the influence of flow resistance on gas transport parameters. The method is based on the setting up and solution of a series of special parametric identification problems based on a limited set of field measurement data at local (in space) network points. This method can be used by specialists in mathematical modeling of gas transport systems to solve practical parametric identification problems.

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Chen, Guang Wei. "The Design of Photoelectric Measuring System on Railway Track Parameters." Applied Mechanics and Materials 483 (December 2013): 555–58. http://dx.doi.org/10.4028/www.scientific.net/amm.483.555.

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Based on the analysis of the current railway track parameters measurement system, a digital system based on embedded processor is designed. The paper introduces the principle of the system , structure and methods. The system is still based on the deviation detection principle of three point method, using high brightness light source as a measurement point, in combination with linear CCD imaging features, completed the orbit measurement system of the digital processing, and through the network to complete the communication with PC. The photoelectric measuring system is realized in trajectory parameters of high accuracy and real time measurement; Also for the future development of tamping on railway cars plays a positive role.

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Journal articles on the topic 'Measurement of network parameters'

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