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Clean Energy 2021年第4期5卷 756-764页

作者： Ju Xin Liu ShangKe Xiao YanLi Wan Ye State Grid Ningxia Electric Power Co.Ltd Eco-Tech Research Institute NingXia Yinchuan750004P.R.China

In view of the difficulty in predicting the cost data of power transmission and transformation projects at present,a method based on pearson correlation coefficient-improved particle swarm optimization(IPSO)-extreme learning machine(ELM)is *** this paper,the pearson correlation coefficient is used to screen out the main influencing factors as the input-independent variables of the ELM algorithm and IPSO based on a ladder-structure coding method is used to optimize the number of hidden-layer nodes,input weights and bias values of the ***,the prediction model for the cost data of power transmission and transformation projects based on the pearson correlation coefficient-IPSO-ELM algorithm is *** the analysis of calculation examples,it is proved that the prediction accuracy of the proposed method is higher than that of other algorithms,which verifies the effectiveness of the model.

关键词： cost data of power transmission and transformation project pearson correlation coefficient IPSO-ELM algorithm project-cost prediction

Regression models of pearson correlation coefficient

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Statistical Theory and Related Fields 2023年第2期7卷 97-106页

作者： Abdisa G.Dufera Tiantian Liu Jin Xu School of Stistis East China Normal University ShanghaiPeople's Republic of China Faculty of Industial Engineering and Management Technion-Israel Institute of TechnologyHaifalsrael Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE East China Normal UniversityShanghaiPeople's Republic of China

We propose two simple regression models of pearson correlation coefficient of two normal responses or binary responses to assess the effect of covariates of ***-based inference is established to estimate the regression coefficients,upon which bootstrap-based method is used to test the significance of covariates of *** studies show the effectiveness of the method in terms of type-I error control,power performance in moderate sample size and robustness with respect to model *** illustrate the application of the proposed method to some real data concerning health measurements.

关键词： Binary responses bivariate normal responses pearson correlation coefficient regression

Statistical analysis of fracture properties based on particle swarm optimization and pearson correlation coefficient method

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Global Geology 2015年第1期18卷 41-48页

作者： ZHOU Yin FENG Xuan Enhedelihai LUO Teng YANG Xueting HE Mei College of Geo-Exploration Science and Technology Jilin University

Prediction of reservoir fracture is the key to explore fracture-type reservoir. When a shear-wave propagates in anisotropic media containing fracture,it splits into two polarized shear waves: fast shear wave and slow shear wave. The polarization and time delay of the fast and slow shear wave can be used to predict the azimuth and density of fracture. The current identification method of fracture azimuth and fracture density is cross-correlation method. It is assumed that fast and slow shear waves were symmetrical wavelets after completely separating,and use the most similar characteristics of wavelets to identify fracture azimuth and density,but in the experiment the identification is poor in accuracy. pearson correlation coefficient method is one of the methods for separating the fast wave and slow wave. This method is faster in calculating speed and better in noise immunity and resolution compared with the traditional cross-correlation method. pearson correlation coefficient method is a non-linear problem,particle swarm optimization( PSO) is a good nonlinear global optimization method which converges fast and is easy to implement. In this study,PSO is combined with the pearson correlation coefficient method to achieve identifying fracture property and improve the computational efficiency.

关键词： fracture property shear-wave splitting statistic analysis pearson correlation coefficient particleswarm optimization

Intrusion Detection System Using Voting-Based Neural Network

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Tsinghua Science and Technology 2021年第4期26卷 484-495页

作者： Mohammad Hashem Haghighat Jun Li Department of Automation Tsinghua UniversityBeijing 100084China

Several security solutions have been proposed to detect network abnormal behavior. However, successful attacks is still a big concern in computer society. Lots of security breaches, like Distributed Denial of Service(DDoS),botnets, spam, phishing, and so on, are reported every day, while the number of attacks are still increasing. In this paper, a novel voting-based deep learning framework, called VNN, is proposed to take the advantage of any kinds of deep learning structures. Considering several models created by different aspects of data and various deep learning structures, VNN provides the ability to aggregate the best models in order to create more accurate and robust results. Therefore, VNN helps the security specialists to detect more complicated attacks. Experimental results over KDDCUP'99 and CTU-13, as two well known and more widely employed datasets in computer network area, revealed the voting procedure was highly effective to increase the system performance, where the false alarms were reduced up to 75% in comparison with the original deep learning models, including Deep Neural Network(DNN), Convolutional Neural Network(CNN), Long Short-Term Memory(LSTM), and Gated Recurrent Unit(GRU).

关键词： deep learning Voting-based Neural Network(VNN) network security pearson correlation coefficient

Investigation on the relationship between hydraulic loss and vortex evolution in pump mode of a pump-turbine

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Journal of Hydrodynamics 2022年第4期34卷 555-569页

作者： Yong-lin Qin De-you Li Hong-jie Wang Zhan-sheng Liu Xian-zhu Wei Xiao-hang Wang School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001China State Key Laboratory of Hydro-Power Equipment Harbin Institute of Large Electrical MachineryHarbin 150040China

Hydraulic loss and vorticity are two most common methods in analyzing the flow characteristics in hydro-machine,i.e.,centrifugal pump,Francis turbine,*** the relationship and correlation between hydraulic loss and vortex evolution are not uncovered *** this study,hydraulic loss is regarded as the combination of dissipation effect and transportation effect in flow ***,vorticityωcan be decomposed into two parts,namely the Liutex partω_(R),the shear partωs,of whichω_(R)is regarded as the third-generation vortex identification method for its precise and rigorous definition of local rigid rotation part of *** on the dimensional analysis,two new physical quantities related to vorticity(ω,ω_(R)andωS),namely enstrophyΩ,vorticity transport intensity T are adopted to express the energy characteristic in vortex evolution ***,operating points at pump mode of an ultra-high head reversible pump-turbine are selected as the research object and the numerical results calculated using SST k-ωturbulence model are consistent well with the experimental *** correlation coefficient is adopted to evaluate the correlation between hydraulic loss and vortex evolution in main flow *** show that apart from the spiral casing domain,the enstrophy of shear partΩs has very strong correlation with dissipation effect and Liutex transport intensity TR has stronger correlation with transportation effect when compared with other forms of *** correlation between Liutex transport intensity TR and transportation effect is strong in stay/guide vanes(SGVs)while reduce to medium level in runner and draft tube *** spiral casing domain,all forms of vorticity show weak or very weak correlation with transportation *** on the proposed method,we believe that the relationship and correlation between hydraulic loss and vortex evolution in other hydraulic machineries can also be clearly investigated.

关键词： Hydraulic loss enstrophy vorticity transportation pearson correlation coefficient

Short-term Load Prediction of Integrated Energy System with Wavelet Neural Network Model Based on Improved Particle Swarm Optimization and Chaos Optimization Algorithm

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Journal of Modern Power Systems and Clean Energy 2021年第6期9卷 1490-1499页

作者： Leijiao Ge Yuanliang Li Jun Yan Yuqian Wang Na Zhang IEEE School of Electrical and Information Engineering Tianjin University Concordia Institute for Information Systems Engineering Concordia University Sany Heavy Machinery Co. Ltd. Department of Electrical Engineering Inner Mongolia University of Technology

To improve energy efficiency and protect the environment,the integrated energy system(IES)becomes a significant direction of energy structure *** paper innovatively proposes a wavelet neural network(WNN)model optimized by the improved particle swarm optimization(IPSO)and chaos optimization algorithm(COA)for short-term load prediction of *** proposed model overcomes the disadvantages of the slow convergence and the tendency to fall into the local optimum in traditional WNN ***,the pearson correlation coefficient is employed to select the key influencing factors of load ***,the traditional particle swarm optimization(PSO)is improved by the dynamic particle inertia *** jump out of the local optimum,the COA is employed to search for individual optimal particles in *** the iteration,the parameters of WNN are continually optimized by ***,the feedback link is added to the proposed model,where the output error is adopted to modify the prediction ***,the proposed model is employed for load *** experimental simulation verifies that the proposed model significantly improves the prediction accuracy and operation efficiency compared with the artificial neural network(ANN),WNN,and PSO-WNN.

关键词： Integrated energy system(IES) load prediction chaos optimization algorithm(COA) improved particle swarm optimization(IPSO) pearson correlation coefficient wavelet neural network(WNN)

Sources of Particular Pollutants inAmbient Air at a Petrochemical Enterprise

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China Petroleum Processing & Petrochemical Technology 2013年第4期15卷 33-37页

作者： Xue Jianliang Zhao Dongfeng ChengJianguang Chen Lu Liu Wei College of Chemical and Environmental Engineering Shandong University of Science and Technology College of Chemical Engineering China University of Petroleum (East China)

The study on source apportionment of particular pollutants in ambient air at a petrochemical enterprise is the ba-sis of the control over air pollution. Through analyzing particular pollutants in the samples collected from one petrochemi- cal enterprise in northwestern China, the sources of particular pollutants were discussed. The test results showed that con- centrations of particular pollutants in different sites were remarkably different. Results showed that the sampling sites with higher concentrations of particular pollutants, including toluene, xylenes, NH3 and H2S, were located at the boundary of the petrochemical enterprise. Instead, the concentrations of NMHC in the ambient air sampling sites were higher than those at the boundary of the petrochemical enterprise. The sampling sites with higher concentrations of particular pollutants were located in the area that was close to the petrochemical enterprise. The results obtained from the pearson correlation co- efficients analyses, the factor analyses, and x^2-tests of the particular pollutants had revealed that NH3, H2S, toluene and xylenes at all sampling sites came from the same source, while NMHC might come from some other sources besides the petrochemical enterprise.

关键词： particular pollutants sources apportionment pearson correlation coefficient

Basic Characteristics,Spatial Disparity and Its Major Influencing Factors of Service Industry in China

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Chinese Geographical Science 2009年第4期19卷 314-324页

作者： SHEN Yuming QIU Ling REN Wangbing CAO Yi HU Dan SONG Yujing College of Resource Environment and Tourism Capital Normal University Beo＇ing 100048 China Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China Graduate University of Chinese Academy of Sciences Beo＇ing 100049 China Academy of Macroeconomic Research National Development and Reform Commission Beijing 100038 China

Based on the analysis of its basic characteristics, this article investigated the disparities of Chinese service industry among the three regions （the eastern China, the western China and the middle China） and inter-provincial disparities of that in the three regions by Theil coefficient and cluster analysis. Then, major factors influencing its spatial disparity were explored by correlation analysis and regression analysis. The conclusions could be drawn as follows. 1） The development of Chinese service industry experienced three phases since the 1980s： rapid growth period, slow growth period, and recovery period. From the proportion of value-added and employment, its development was obviously on the low level. From the composition of industrial structure, traditional service sectors were dominant, but modem service sectors were lagged. Moreover, its spatial disparity was distinct. 2） The level of Chinese service industry was divided into five basic regional ranks： well-developed, developed, relatively-developed, underdeveloped and undeveloped regions, As a whole, the overall structure of spatial disparity was steady in 1990-2005. But there was notable gradient disparity in the interior structure of service industry among different provinces. Furthermore, the overall disparity expanded rapidly in 1990-2005. The inter-provincial disparity of service industry in the three regions, especially in the eastern China, was bigger than the disparity among the three regions. And 3） the level of economic development, the level of urban development, the scale of market capacity, the level of transportation and telecommunication, and the abundance of human resources were major factors influencing the development of Chinese service industry.

关键词： service industry Theil coefficient pearson correlation coefficient cluster analysis spatial disparity China

Metaphor Analysis Method Based on Latent Semantic Analysis

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Journal of Donghua University(English Edition) 2021年第1期38卷 83-90页

作者： TAO Ran WEI Yaping YANG Tangfeng School of Computer Science and Technology Donghua UniversityShanghai 201620China College of Foreign Languages Donghua UniversityShanghai 201620China

Current research on metaphor analysis is generally knowledge-based and corpus-based,which calls for methods of automatic feature extraction and weight *** natural language processing(NLP),latent semantic analysis(LSA),and pearson correlation coefficient,this paper proposes a metaphor analysis method for extracting the content words from both literal and metaphorical corpus,calculating correlation degree,and analyzing their *** value of the proposed method was demonstrated through a case study by using a corpus with keyword“飞翔(fly)”.When compared with the method of pearson correlation coefficient,the experiment shows that the LSA can produce better results with greater significance in correlation *** is also found that the number of common words that appeared in both literal and metaphorical word bags decreased with the correlation *** case study also revealed that there are more nouns appear in literal corpus,and more adjectives and adverbs appear in metaphorical *** method proposed will benefit NLP researchers to develop the required step-by-step calculation tools for accurate quantitative analysis.

关键词： latent semantic analysis(LSA) metaphor natural language processing(NLP) pearson correlation coefficient

Parameter value selection strategy for complete coverage path planning based on the Lüsystem to perform specific types of missions

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Frontiers of Information Technology & Electronic Engineering 2023年第2期24卷 231-244页

作者： Caihong LI Cong LIU Yong SONG Zhenying LIANG School of Computer Science and Technology Shandong University of TechnologyZibo255000China School of Mechanical Electrical&Information EngineeringShandong University(Weihai)Weihai264209China

We propose a novel parameter value selection strategy for the Lüsystem to construct a chaotic robot to accomplish the complete coverage path planning(CCPP)*** algorithm can meet the requirements of high randomness and coverage rate to perform specific types of ***,we roughly determine the value range of the parameter of the Lüsystem to meet the requirement of being a dissipative ***,we calculate the Lyapunov exponents to narrow the value range ***,we draw the phase planes of the system to approximately judge the topological distribution characteristics of its ***,we calculate the pearson correlation coefficient of the variable for those good ones to judge its random ***,we construct a chaotic robot using variables with the determined parameter values and simulate and test the coverage rate to study the relationship between the coverage rate and the random characteristics of the *** above selection strategy gradually narrows the value range of the system parameter according to the randomness requirement of the coverage *** the proposed strategy,proper variables can be chosen with a larger Lyapunov exponent to construct a chaotic robot with a higher coverage *** chaotic system,the Lorenz system,is used to verify the feasibility and effectiveness of the designed *** proposed strategy for enhancing the coverage rate of the mobile robot can improve the efficiency of accomplishing CCPP tasks under specific types of missions.

关键词： Chaotic mobile robot Lüsystem Complete coverage path planning(CCPP) Parameter value selection strategy Lyapunov exponent pearson correlation coefficient