Zhong Wang

Hefei Normal University

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Peibei Shi

Hefei Normal University

Jianxiang Xi

Xi'an High Tech University

Yongguang Bi

Guangdong Pharmaceutical University

Luhua Fu

Tianjin University

Ruina Li

Jiangsu University

Guijuan Wang

Shandong University

Changjie Liu

Northwest Institute of Eco-Environment and Resources

Hai‐Lan Huang

Minjiang University

Lanfang Lei

Hefei University

Yadong Wu

China Astronaut Research and Training Center

Cooperative Institutions

Chinese Academy of Sciences

Tianjin University

Zhejiang University

University of Science and Technology of China

University of Chinese Academy of Sciences

Northwestern Polytechnical University

Huazhong University of Science and Technology

Sun Yat-sen University

Southwest University of Science and Technology

Tsinghua University

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Study on design of interplex method for GNSS signal

China Communications (2014)

Youjun Feng Zhong Wang Dandan Chen

In order to satisfy sending multi-channel navigation signals in one frequency for modern GNSS(Global Navigation Satellite System), the principle of Interplex multiplexing were introduced. And the three-way multiplexing structure and the four-way multiplexing method were also optimized. The Galileo E1 signal, as the example of Interplex reuse, was analyzed in detail. The power configuration of the multiplexing efficiency and the minimum of the multiplexing efficiency were obtained.

Galileo (satellite navigation)

Spatial multiplexing

SIGNAL (programming language)

Time-division multiplexing

10.1109/cc.2014.7085380

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Optimizing matching of parameter for straight line shale shaker

Drilling & Production Technology (2000)

Zhong Wang

In order to solve the problem of optimizing matching of parameter for straight line shale shaker,the minimum fierce vibration force and maximum throw index are regarded asdesign object.The paper presents the design of line shale shaker,proposes out a method of optimizing parameter for line shaker.And optimizing parameter form for line shale shaker in accord with international standard GB/T 11648-89 was obtained.

Shaker

Line (geometry)

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Common Due Window with Earliness and Tardiness Penalties

Yunchou yu guanli (2001)

Zhong Wang

This paper discusses the sequencing with earliness and tardiness penalties in a single machine shop in which each job is assigned a constant due window and each job processing time distribution is assumed independent distribution, and under the constant due window the optimal sequence of n independent jobs has V character.

Tardiness

Constant (computer programming)

Due date

Sequence (biology)

Retard

Source

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Applying of the termwise-combination support vector machine to identification of reservoir and prediction of deliverability in tight reservoirs

Journal of Daqing Petroleum Institute (2011)

Pang Heqing Kuang Jian-chao Cai Zuohua Zhong Wang Huang Yao-zong

It is difficult to identify reservoir and predict deliverability accurately in the tight reservoir. This paper proposes a new modeling method —termwise-combination support vector machine (TCSVM). Firstly, we apply support vector classification (SVC) to achieve reservoir identification, and then use the support vector regression (SVR) to establish deliverability prediction model by category. Finally, reservoir identification and deliverability prediction are implemented in the TCSVM model. After the noise reduction, dimension reduction in the earlier days, this model can reduce interference from the categories of samples, thus improve greatly the accuracy of reservoir identification and deliverability prediction. The model is applied to identify reservoir and predict deliverability in M51 reservoir, which belongs to the central gas-field of Ordos Basin. Ninety two samples were acquired by zonal testing from the selected nineteen wells to identify the gas horizon, gas-bearing horizon, dry zone, water layer and deliverability prediction. The paper chooses seventy eight samples randomly for training, and the remaining 14 to be the testing. To establish the model of M51 reservoir in the central gas-field, we select ten parameters which related closely with the reservoir characteristics as input variables. Then we use the model to achieve reservoir identification and deliverability prediction. The results show that the model prediction error is lower than the traditional modeling method and polynomial self-organizing neural networks (MOSN). Especially, the principal component analysis and termwise-combination support vector machine model (PCA-TCSVM) prediction error is the lowest (average absolute error 0.359, average relative error 0.036). Therefore, PCA-TCSVM model can generally reduce interference from the categories of samples and improve the accuracy. This will have a positive significance for oil and gas exploration.

Reservoir computing

Identification

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The Method of Selecting the Evaluation Model for the State of Children's Growth Based on Machine Learning

Yubin Chen Dancheng Li Ning Wang Changyuan Wu Zhong Wang

Children's growth has always been the focus of social attention. Health problems can be found and solved as soon as possible through health risk evaluation. So it can promote the healthy growth of children. In this paper, a model selection method is proposed, which can select the suitable model from different factors, different grading standards and different models for the classification evaluation of children's growth. Factors including height, weight, head circumference, arm circumference, body mass index, subscapular skinfold thickness and triceps skinfold thickness. Grade results including bottom, above bottom, middle, below top and top. And we did experiments in KNN, Naive Bayes, logistic regression, decision tree, random forest, AdaBoosting and GBDT classifier models. The method proposed in this paper can certainly select children's growth evaluation model which can effectively evaluate children's growth status under given conditions.

Circumference

Grading (engineering)

10.1109/icaibd51990.2021.9458961

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Influence of Shale Gas Components on Jet Diffusion Flame

Advances in computer science research (2015)

S. Liu Zhong Wang Yang Zhao Ruina Li Lei Qu

Effect of different shale gas components on jet diffusion flame were studied using mathematical method in this paper.Changes of OH free radical in jet diffusion flame of two different shale gas components were researched, and the impacts of shale gas composition changes on mass fraction of methane, combustion velocity and temperature fields were also discussed compared with vehicle compression natural gas jet diffusion flames.The results show that, in process of shale gas diffusion combustion, OH free radical mainly in outer flame, higher concentration of OH free radicals produced by the combustion of shale gas with higher mass fraction of methane at the top of the flame; in the region the flame height is in the range of 0~3cm, mass fraction of methane is higher, methane consumption is fastest, and combustion is most intense; compared with shale gas with methane mass fraction of 62.9% and vehicle compression natural gas with methane mass fraction of 87.36%, shale gas with methane mass fraction of 93.5% has the highest Combustion temperature and the fastest combustion speed.

10.2991/icmra-15.2015.149

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Citations (1)

A self-learning framework for pedestrian detection

JUSTC (2020)

Zhong Wang Peibei Shi Guiquan Liu

Pedestrian detection

10.3969/j.issn.0253-2778.2020.01.010

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Analysis of Magnetic Field of the New Phase-Shifting Transformer

Advanced materials research (2014)

Zhong Wang Jing Zhao Bing Li

A novel phase shifting transformer is proposed for the application of multi-pulse rectifier, which is based linear motor, and has the advantages of simple structure, easy to manufacture, etc. Introduces the operating principle. Without considering flat phase shifting transformer longitudinal end-effect and transverse end-effect, analyzes the magnetic field distribution of the flat phase shifting transformer, it provides an optimal way to this novel phase shifting transformer.

Delta-wye transformer

Three-phase

10.4028/www.scientific.net/amr.1006-1007.919

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Study of Fault Diagnosis Distribution Network Based on Rough Set and Artificial Intelligence

Journal of Physics Conference Series (2021)

Hui Zhou Zhong Wang Chunqing Shi Chaoying Liu ShiQin Zhao

Abstract The current real-time data collected by the power grid includes remote measurement, remote signaling, and other fault factors. The research in this paper is based on the fault diagnosis technology of rough set theory and self-learning theory, taking fault influencing factors as conditional attributes, fault type as decision-making attribute, and generating rough set rule table through self-learning reduction through a large number of fault history records, the influence of meteorological factors, environmental factors, equipment factors and other factors on the probability of equipment failure, which can realize the route Risk level prediction and fault location. Case analysis shows that the distribution network diagnosis technology based on rough set plays an extremely important role in predicting the risk level of each section of the line and positioning after a fault occurs.

Decision table

10.1088/1742-6596/1754/1/012204

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Whispered Speech Conversion Based on the Inversion of Mel Frequency Cepstral Coefficient Features

Algorithms (2022)

Qiang Zhu Zhong Wang Yunfeng Dou Jian Zhou

A conversion method based on the inversion of Mel frequency cepstral coefficient (MFCC) features was proposed to convert whispered speech into normal speech. First, the MFCC features of whispered speech and normal speech were extracted and a matching relation between the MFCC feature parameters of whispered speech and normal speech was developed through the Gaussian mixture model (GMM). Then, the MFCC feature parameters of normal speech corresponding to whispered speech were obtained based on the GMM and, finally, whispered speech was converted into normal speech through the inversion of MFCC features. The experimental results showed that the cepstral distortion (CD) of the normal speech converted by the proposed method was 21% less than that of the normal speech converted by the linear predictive coefficient (LPC) features, the mean opinion score (MOS) was 3.56, and a satisfactory outcome in both intelligibility and sound quality was achieved.

Mel-frequency cepstrum

Cepstrum

10.3390/a15020068

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Citations (4)