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Prediction model for cost data of a power transmission and transformation project based on pearson correlation coefficient-IPSO-ELM

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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

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

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

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

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)

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：陶然卫亚萍杨唐峰 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

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插层熔喷非织造材料的性能控制研究

建模与仿真 2022年第6期11卷 1614-1626页

作者：项辉梁云舒刘永清上海理工大学机械工程学院，上海上海理工大学光电信息与计算机工程学院，上海上海理工大学健康科学与工程学院，上海

本文在插层率固定的情况下，研究不同工艺参数组合的插层熔喷非织造材料的结构变量和产品性能。通过变量的调式建立最优化的多项式拟合模型，代入预处理后的数据，得到工艺参数与结构变量之间的关系，并通过数据可视化和三维拟合图使结... 详细信息

本文在插层率固定的情况下，研究不同工艺参数组合的插层熔喷非织造材料的结构变量和产品性能。通过变量的调式建立最优化的多项式拟合模型，代入预处理后的数据，得到工艺参数与结构变量之间的关系，并通过数据可视化和三维拟合图使结果更直观。对经过雅克–贝拉检验后的数据使用样本皮尔逊相关系数法，再辅以蒙特卡罗法和非线性规划模型求解出何时过滤效率的最优解。在满足实际生产条件的基础上，通过使用消除量纲且被转化为最大化变量后的数据，将其代入加权组合降维后的单目标规划模型，得到结构参数的组合使得过滤效率尽可能大的同时过滤阻力尽可能的小。

关键词：插层熔喷非织造材料多项式拟合皮尔逊相关系数蒙特卡罗法非线性规划模型 Intercalated Melt-Blown Nonwoven Materials Polynomial Fitting pearson correlation coefficient Monte Carlo Method Nonlinear Programming Model

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古代玻璃制品的成分分析与鉴别

Fuzzy Logic Implementation of Vulnerability Assessment in a Coastal Aquifer of Northern Sicily

建模与仿真 2023年第1期12卷 67-80页

作者：项辉王可金乐李霁昊李响上海理工大学机械工程学院，上海上海理工大学光电信息与计算机工程学院，上海上海理工大学出版印刷与艺术设计学院，上海

在经过初步分析后，使用SPSS中的Fisher判别分析对附件1的样本数据整体进行两次Fisher判别分析，得出化学成分中对于分类有明显影响的主要变量和高钾玻璃、铅钡玻璃的分类规律。分析得知风化文物的未风化采样点与未风化文物的采样点性... 详细信息

在经过初步分析后，使用SPSS中的Fisher判别分析对附件1的样本数据整体进行两次Fisher判别分析，得出化学成分中对于分类有明显影响的主要变量和高钾玻璃、铅钡玻璃的分类规律。分析得知风化文物的未风化采样点与未风化文物的采样点性质相似，故将其视为未分化组样本再使用excel进行统计性分析。首先使用SPSS分别画出高钾玻璃化学成分和铅钡玻璃化学成分的散点图，若判断具有线性关系，再使用皮尔逊相关系数进行不同类型玻璃文物化学成分相关性分析。考虑到风化作用的影响，所以将高钾玻璃和铅钡玻璃分为风化高钾、未风化高钾、风化铅钡、未风化铅钡4类进行分析。在进行未知文物的类型鉴别分析时，使用RUSBoost算法和决策树模型分别进行鉴别，将两种方法得到的结果使用ROC曲线进行比较得出类型鉴别结果更好的模型，并使用网格搜索法进行模型的敏感性分析。本文对于探究高钾、铅钡玻璃的分类规律以及玻璃文物的分类有一定的应用价值。

关键词： Fisher判别分析皮尔逊相关系数 RUSBoost算法决策树模型 ROC曲线网格搜索法 Fisher Discriminant Analysis pearson correlation coefficient RUSBoost Algorithm Decision Tree Model ROC Curve Grid Search Method

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Journal of Geoscience and Environment Protection 2021年第8期9卷 177-188页

作者： Antonio Cimino Adolfo Cimino Antonino Oieni Department of Physics University of Palermo Italy Consultant Geologist Sicilian Geologist Association Cammarata Italy Consultant Geologist Sicilian Geologist Association Tusa Italy

Aquifers can be defined as complex ecological systems. Their description is closely influenced by geometrical and geological parameters, which portray the hydrogeological behaviour of underground systems. This paper reports a contribution to assessing groundwater contamination risk in a particular Sicily sector, where deterministic approaches have methodically assessed and mapped vulnerability and quality of groundwater. In detail, in the coastal area of Acquedolci (Northern Sicily), already intensely surveyed in the frame of interdisciplinary projects on geological risk, implementing models and systems have been experimented, also considering fuzzy logic. Cartography issues are here presented and compared, with particular regard to the effect of stochastic hydrogeological elements (i.e. “depth to water”), locally characterized by variability for simultaneous climate, overdraft, irrigation and sea encroachment. The authors show how fuzzy logic, applied to vulnerability settings, contributes to a better comprehension of the passive scenery offered by aquifers in Acquedolci Sicily area.

关键词： Fuzzy Logic Groundwater Vulnerability Acquedolci Plain SINTACS Method pearson correlation coefficient