Approach for CM/DM Current Extraction and Crosstalk Analysis of Twisted-Wire Pairs with Random Non-uniform Twisting

2021 ◽  
Vol 35 (12) ◽  
pp. 1477-1484
Author(s):  
Chao Huang ◽  
Yan Zhao ◽  
Wei Yan ◽  
Yanxing Ji ◽  
Qiangqiang Liu ◽  
...  
Keyword(s):  
Transmission Lines ◽  
Unit Length ◽  
High Frequencies ◽  
Random Combination ◽  
Full Wave ◽  
The Neural Network ◽  
Arbitrary Position ◽  
Neural Network Algorithm ◽  
The Common ◽  
Twisted Wire

In this paper, a twisted-wire pairs (TWP) with random non-uniform twisting is established. It is divided into a complete pitch segment and a noncomplete pitch segment by the ratio between the pitch and the length. The randomness of the actual TWP cable is accurately simulated by the following methods: 1) random combination of complete pitch segments; 2) random combination of non-complete pitch segments; 3) random combination between 1) and 2). Based on the TWP model, an equivalent multi-conductor transmission lines (MTLs) model can be obtained. The neural network algorithm is introduced to describe the complex relationship between the arbitrary position of the TWP and the per-unit-length (p.u.l) parameter matrix. In addition, the crosstalk and the common-mode (CM) and differential-mode (DM) noise under field-to-wire coupling are predicted. The numerical results show that crosstalk and CM/DM noise in TWP cable are susceptible to the twisted pitch at high frequencies. Compared with full-wave simulation, the accuracy of the proposed method is proved.

Prediction and Suppression of Twisted-wire Pair Crosstalk Based on Beetle Swarm Optimization Algorithm

2021 ◽  
Vol 36 (4) ◽  
pp. 435-441
Author(s):  
Jianming Zhou ◽  
Shijin Li ◽  
Wu Zhang ◽  
Wei Yan ◽  
Yang Zhao ◽  
...  
Keyword(s):  
Transmission Lines ◽  
Unit Length ◽  
Back Propagation ◽  
Telegraph Equation ◽  
Frequency Domain Method ◽  
Cross Sectional ◽  
Swarm Optimization ◽  
Value Decomposition ◽  
Sectional Shape ◽  
Twisted Wire

Based on the theory of multi-conductor transmission lines (MTL), this paper proposes a new method for predicting and suppressing crosstalk of twisted-wire pair (TWP). The per unit length (p.u.l) RLCG parameters change caused by the inconsistent cross-sectional shape of TWP, changes in parameters make it difficult to solve the telegraph equation. In this paper, the method of transmission lines cascade is used. TWP is divided into several segments, and p.u.l parameters of each segment are predicted. Compared with before method, we propose a higher precision algorithm—beetle swarm optimization (BSO) to optimize the weights of back-propagation (BP) neural network, which predict p.u.l parameters at each segment. On this basis, it is divided into two steps: 1) Use MTL frequency domain method combined with lines’ terminal conditions to solve crosstalk and compare with CST simulation results; 2) Use the singular value decomposition (SVD) method to add matrix modules at both ends of lines for suppressing crosstalk. The results show that proposed method in this paper is consistent with the simulation, and the accuracy is higher than before

scholarly journals Forecasting Number of COVID-19 in Bali Province Using Neural Network Algorithm

2021 ◽  
pp. 72
Author(s):  
Ida Ayu Utari Dewi ◽  
I Kadek Noppi Adi Jaya ◽  
Kadek Oky Sanjaya
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Time Series Data ◽  
Large Family ◽  
Series Data ◽  
Severe Illness ◽  
Network Algorithm ◽  
The Neural Network ◽  
Neural Network Algorithm ◽  
The Common

COVID-19 (coronavirus disease 2019) is a large family of viruses that cause mild to severe illness, such as the common cold or colds and serious illnesses such as MERS and SARS. COVID-19 has become a pandemic, meaning that there has been an increase in cases of the disease which is quite fast and there has been spread between countries and caused enormous losses in various countries. The increasing number of COVID-19 cases every day in Indonesia, including in Bali Province and the resulting losses underlie the forecasting of the number of COVID-19 in Bali Province. Forecasting is carried out using the Neural Network algorithm for time series data on the number of COVID-19 in Bali Province. The data used is data on the number of COVID-19 in the Bali Province in the form of time series data sourced from the Bali Provincial Health Office. The entire forecasting process uses the Rapidminer Studio tools starting from preprocessing, modeling, testing and validation. The results of the RMSE (Root Mean Square Error) evaluation value based on testing for the positive patients were 18.956, the patients recovered were 15.413, the patients under treatment were 5.066 and the patients who died was 0.233.

Miniature UWB Filter Using Three-Quarters Wavelength Resonator with Direct-Connected Feed Method

2012 ◽  
Vol 571 ◽  
pp. 721-724
Author(s):  
Cai Peng
Keyword(s):  
Transmission Lines ◽  
Linear Structure ◽  
Ultra Wideband ◽  
Input Output ◽  
Transmission Zeros ◽  
Full Wave ◽  
Quarter Wavelength ◽  
Ring Structures ◽  
Loss Characteristic ◽  
Better Than

A miniature ultra-wideband (UWB) bandpass filter using three-quarters wavelength resonators is presented in this paper. Direct-connected feed method is employed between the input/output ports and the resonators in order to overcome the shortcomings due to the gap-coupled feed method and produce two transmission zeros in the lower and upper stopbands. On the other hand, two quarter-wavelength matching transmission lines are introduced to the input/output ports to improve the reflection loss characteristic in the passband of the filter. In addition, the resonators are folded to be open ring structures, which are more miniaturized than the conventional linear structure. As a consequence, the filter is compact in size and exhibits good performance. The filter is successfully realized in theory and verified by full wave EM simulation, and simulated frequency response results show that the fabricated filter has an insertion loss of better than 1dB in the passband and two rejections of greater than 25dB in most of the stopbands.

Modified methodology of computation of admissible continuous currents of plain conductors of overhead transmission lines and catenaries

2021 ◽  
Vol 2 (2) ◽  
pp. 36-43
Author(s):  
Evgeniy P. FIGURNOV ◽  
◽  
Yury I. ZHARKOV ◽  
Valeriy I. KHARCHEVNIKOV ◽  
◽  
...  
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Transmission Lines ◽  
Power Transmission ◽  
Convection Heat Transfer ◽  
Heating And Cooling ◽  
Continuous Current ◽  
The Subject ◽  
The Common ◽  
Overhead Power Transmission Line

Methodology provided summarizes published, original and foreign theoretic and experimental data on the subject of heating and cooling of standard and shaped conductors of overhead power transmission line and uses those of them which are most affected to fundamental heat-transfer laws. Computation surface area of standard and shaped wire formulas are given. The common formula of convection heat transfer coefficient is provided, based on wind speed and direction, concerning antiicing mode. Parameters of this formula do not coincide with those existing, as they are based on experimental data on standard and shaped conductors but not on round tubes. Formula of computation of heat transfer power under the influence of solar radiation is given. Summarized formula of admissible continuous current computation is given, all the components have detailed description in the article.

scholarly journals A Method for the Statistical Evaluation of Crosstalk Effect Between Three Parallel Conductors

1999 ◽  
Vol 22 (2) ◽  
pp. 111-119
Author(s):  
P. T. Trakadas ◽  
C. N. Capsalis
Keyword(s):  
Closed Form ◽  
Uniform Distribution ◽  
Transmission Lines ◽  
Statistical Evaluation ◽  
Unit Length ◽  
Surrounding Medium ◽  
Probabilistic Approach ◽  
Random Variable ◽  
Mutual Inductance ◽  
Theoretical Results

There are several cases at which, in order to evaluate the crosstalk effect among transmission lines carrying useful signals, there is a need for probabilistic approach. This paper considers the problem of crosstalk estimation between transmission lines consisting of three conductors in a homogeneous surrounding medium, where the distance between the conductors is a random variable described by uniform distribution. The transmission lines are considered as electrically short. A closed-form equation is developed for the statistical distribution of the per-unit-length mutual inductance(lm)and an analytical one is described for the evaluation of the per-unit-length capacitance(cm). Theoretical results are compared with simulated ones for validation purposes.

scholarly journals Design and Modeling of New UWB Metamaterial Planar Cavity Antennas with Shrinking of the Physical Size for Modern Transceivers

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Mohammad Alibakhshi Kenari
Keyword(s):  
Transmission Lines ◽  
Patch Antenna ◽  
Patch Antennas ◽  
Frequency Bandwidth ◽  
Left Handed ◽  
Full Wave ◽  
Radiation Properties ◽  
Unit Cells ◽  
Constitutive Parameters ◽  
Large Frequency

A variety of antennas have been engineered with MTMs and MTM-inspired constructs to improve their performance characteristics. This report describes the theory of MTMs and its utilization for antenna's techniques. The design and modeling of two MTM structures withε-μconstitutive parameters for patch antennas are presented. The framework presents two novel ultrawideband (UWB) shrinking patch antennas filled with composite right-/left-handed transmission line (CRLH-TL) structures. The CRLH-TL is presented as a general TL possessing both left-handed (LH) and right-handed (RH) natures. The CRLH-TL structures enhance left-handed (LH) characteristics which enable size reduction and large frequency bandwidth. The large frequency bandwidth and good radiation properties can be obtained by adjusting the dimensions of the patches and CRLH-TL structures. This contribution demonstrates the possibility of reducing the size of planar antennas by using LH-transmission lines. Two different types of radiators are investigated—a planar patch antenna composed of fourO-formed unit cells and a planar patch antenna composed of sixO-shaped unit cells. A CRLH-TL model is employed to design and compare these two approaches and their realization with a varying number ofL-Cloaded unit cells. Two representative antenna configurations have been selected and subsequently optimized with full-wave electromagnetic analysis. Return loss and radiation pattern simulations of these antennas prove the developed concept.

scholarly journals WRF-Chem Simulation of Winter Visibility in Jiangsu, China, and the Application of a Neural Network Algorithm

Atmosphere ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 520
Author(s):  
Peishu Zong ◽  
Yali Zhu ◽  
Huijun Wang ◽  
Duanyang Liu
Keyword(s):  
Neural Network ◽  
Wind Speed ◽  
Extinction Coefficient ◽  
Wrf Model ◽  
Jiangsu Province ◽  
Network Algorithm ◽  
The Neural Network ◽  
Noticeable Improvement ◽  
Neural Network Algorithm ◽  
Meteorological Elements

In this paper, the winter visibility in Jiangsu Province is simulated by WRF-Chem (Weather Research and Forecasting (WRF) model coupled with Chemistry) with high spatiotemporal resolutions. Simulation results show that WRF-Chem has good capability to simulate the visibility and related local meteorological elements and air pollutants in Jiangsu in the winters of 2013–2017. For visibility inversion, this study adopts the neural network algorithm. Meteorological elements, including wind speed, humidity and temperature, are introduced to improve the performance of WRF-Chem relative to the visibility inversion scheme, which is based on the Interagency Monitoring of Protected Visual Environments (IMPROVE) extinction coefficient algorithm. The neural network offers a noticeable improvement relative to the inversion scheme of the IMPROVE visibility extinction coefficient, substantially improving the underestimation of winter visibility in Jiangsu Province. For instance, the correlation coefficient increased from 0.17 to 0.42, and root mean square error decreased from 2.62 to 1.76. The visibility inversion results under different humidity and wind speed levels show that the underestimation of the visibility using the IMPROVE scheme is especially remarkable. However, the underestimation issue is essentially solved using the neural network algorithm. This study serves as a basis for further predicting winter haze events in Jiangsu Province using WRF-Chem and deep-learning methods.

Using neural network model to estimate the rental price of residential properties

2019 ◽  
Vol 24 (2) ◽  
pp. 217-230
Author(s):  
Olalekan Shamsideen Oshodi ◽  
Wellington Didibhuku Thwala ◽  
Tawakalitu Bisola Odubiyi ◽  
Rotimi Boluwatife Abidoye ◽  
Clinton Ohis Aigbavboa
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Predictive Accuracy ◽  
Content Type ◽  
The Neural Network ◽  
Residential Properties ◽  
African Context ◽  
Neural Network Algorithm ◽  
The Government

Purpose Estimation of the rental price of a residential property is important to real estate investors, financial institutions, buyers and the government. These estimates provide information for assessing the economic viability and the tax accruable, respectively. The purpose of this study is to develop a neural network model for estimating the rental prices of residential properties in Cape Town, South Africa. Design/methodology/approach Data were collected on 14 property attributes and the rental prices were collected from relevant sources. The neural network algorithm was used for model estimation and validation. The data relating to 286 residential properties were collected in 2018. Findings The results show that the predictive accuracy of the developed neural network model is 78.95 per cent. Based on the sensitivity analysis of the model, it was revealed that balcony and floor area have the most significant impact on the rental price of residential properties. However, parking type and swimming pool had the least impact on rental price. Also, the availability of garden and proximity of police station had a low impact on rental price when compared to balcony. Practical implications In the light of these results, the developed neural network model could be used to estimate rental price for taxation. Also, the significant variables identified need to be included in the designs of new residential homes and this would ensure optimal returns to the investors. Originality/value A number of studies have shown that crime influences the value of residential properties. However, to the best of the authors’ knowledge, there is limited research investigating this relationship within the South African context.

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