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5th Annual China Marketing International Conference of Chinese-Scholar-Marketing-Association (CMIC) - Marketing Strategy in the Sharing Economy - Localization and Globalization

作者： Wang Xiaobing Bao Yeqing Li Yiru China JiliangUniv Econim & Management Sch Hangzhou Zhejiang Peoples R China Univ Alabama Grad Sch Huntsville AL USA

Base on supply-side reform, electricity consumption has become a key indicators in Keqiang Index which proposed by Premier Li in 2007. The paper to scientifically analyze the relationship between the electric power supply and demand with GDP, and explore the relationship between the economic development trend of industry and the electricity consumption of the whole society. Based on the multiple linear regression models, used from 2001 to 2015 years dates of China with EViews 8.0 tools to forecast electricity consumption can maximally achieve the controllability of the Electric Power-GDP Relationship, and founding the energy-GDP elasticity reduced step by step, the electric power use much more efficacy in China.

关键词： supply-side reform electric power-GDP multiple linear regression model

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Offshore Wind Speed Forecasting: The Correlation between Satellite-Observed Monthly Sea Surface Temperature and Wind Speed over the Seas around the Korean Peninsula

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ENERGIES 2017年第7期10卷 994-994页

作者： Kim, Jin-Young Kim, Hyun-Goo Kang, Yong-Heack Korea Inst Energy Res New & Renewable Energy Data Ctr 152 Gajeong Ro Daejeon 34129 South Korea

Wind power forecasting is a key role for large-scale wind power penetration on conventional electric power systems by understanding stochastic nature of winds. This paper proposes an empirical statistical model for forecasting monthly offshore wind speeds as a function of remotely sensed sea surface temperatures over the seas around the Korean Peninsula. The model uses the optimal lagged multiple linear regression method, and predictors are characterized by mixed periodicities derived from the autocorrelation between spatially variable satellite-observed sea surface temperatures and wind speeds at all grid points over a period of about ten years (2001 to 2008). Offshore wind speeds were found to be correlated with sea surface temperatures within a seasonal range of two-to four-month lags. In particular, offshore wind speeds were closely associated with the sea surface temperature at lag 4 M, followed by lag 3Mand lag 2 M. Correlation is less at lag 1Mas compared lag 2 M, lag 3 M and lag 4 M. The results demonstrate that this approach successfully produces accurate depictions of monthly wind speeds at the gridded network. The hindcast offshore wind speeds and wind power density showed slightly improved skills compared to the seasonally varying climatology with the value of root-mean square errors, +18% and +23%, respectively. The spatial distributions of the monthly gridded wind speed and wind power density remained fairly stable from one month to another, whereas individual regions displayed slight differences in variability. The results of this study are expected to be useful in establishing guidelines for operating and managing nascent offshore farms around the Korean Peninsula.

关键词： offshore wind speed forecasting correlation monthly wind speed sea surface temperature satellite statistical approach multiple linear regression model

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BMC PSYCHIATRY 2017年第1期17卷 309-309页

作者： Yang, Wei-Cheng Lin, Ching-Hua Wang, Fu-Chiang Lu, Mei-Jou Kaohsiung Municipal Kai Syuan Psychiat Hosp 130Kaisyuan 2nd Rd Kaohsiung 80276 Taiwan Kaohsiung Med Univ Dept Psychiat Coll Med Fac Med 100Shihcyuan 1st Rd Kaohsiung 80708 Taiwan

Background: The aim of this study was to explore the relationships between depressive symptoms and health-related quality of life (HRQOL) measurements for inpatients with major depressive disorder (MDD) before and after 6-week fluoxetine treatment, and to elucidate the factors related to the HRQOL changes. Methods: A total of 131 inpatients with MDD were enrolled to receive 20 mg of fluoxetine for 6 weeks. Symptom severity and adverse events were assessed at weeks 0, 1, 2, 3, 4, and 6 using the 17-item Hamilton Depression Rating Scale (HAMD-17) and UKU Side Effect Rating Scale, respectively. HRQOL was measured using the Short Form 36 (SF-36), including 8 subscales, physical component summary (PCS) and mental component summary (MCS), at baseline and week 6. Spearman's coefficient, Cohen's d, and multiple linear regression model were used for statistical analysis. Results: One hundred and six patients completing all measures at weeks 0 and 6 entered the analysis. HAMD-17 negatively correlated with SF-36 at baseline and week 6. The HAMD-17 had a larger effect size than SF-36. MCS, rather than PCS, showed statistically significant improvement. After using multiple linear regression analysis, age at onset, HAMD-17 score change, and number of adverse events reported during the trial period were related to MCS change after adjusting for confounding variables. Conclusions: Fluoxetine treatment was associated with an improvement in depressive symptomology and HRQOL. Depressive symptoms had a greater extent of change than HRQOL. Clinicians must consider the negative effects of adverse events caused by antidepressants on the improvement of HRQOL.

关键词： HRQOL Changes Health-related Quality Of Life (HRQOL) Fluoxetine Treatment multiple linear regression model Physical Component Summary (PCS)

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Prediction of Extractable Cd,Pb and Zn in Contaminated Woody Habitat Soils Using a Change Point Detection Method

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Pedosphere 2016年第3期26卷 282-298页

作者： Christophe WATERLOT Christelle PRUVOT Géraldine BIDAR Clémentine FRITSCH Annette DE VAUFLEURY Renaud SCHEIFLER Francis DOUAY Groupe ISA Laboratoire Genie Civil et geo-Environnement(LGCgE)Lille 59046(France) Departement Chrono-Environment UMR UFC/CNRS 6249 USC INRAUniversite Bourgogne Franche-ComteBesancon 25030(France)

Accumulation of heavy metals in soils poses a potential risk to plant production, which is related to availability of the metals in soil. The phytoavailability of metals is usually evaluated using extracting solutions such as salts, acids or chelates. The purpose of this study was to identify the most significant soil parameters that can be used to predict the concentrations of acetic and citric acidextractable cadmium(Cd), lead(Pb) and zinc(Zn) in contaminated woody habitat topsoils. multiple linear regression models were established using two analysis strategies and three sets of variables based on a dataset of 260 soil samples. The performance of these models was evaluated using statistical parameters. Cation exchange capacity, CaCO_3, organic matter, assimilated P, free Al oxide,sand and the total metal concentrations appeared to be the main soil parameters governing the solubility of Cd, Pb and Zn in acetic and citric acid solutions. The results strongly suggest that the metal solubility in extracting solutions is extractable concentrationdependent since models were overall improved by incorporating a change point. This change point detection method was a powerful tool for predicting extractable Cd, Pb and Zn. Suitable predictions of extractable Cd, Pb and Zn concentrations were obtained, with correlation coefficient(adjusted r) ranging from 0.80 to 0.99, given the high complexity of the woody habitat soils studied. Therefore,the predictive models can constitute a decision-making support tool for managing phytoremediation of contaminated soils, making recommendations to control the potential bioavailability of metals. The relationships between acetic and/or citric acid-extractable concentrations and the concentrations of metals into the aboveground parts of plants need to be predicted, in order to make their temporal monitoring easier.

关键词： acetic acid citric acid contaminated soil extractability metals multiple linear regression model soil parameters

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Bio-energy conversion performance, biodegradability, and kinetic analysis of different fruit residues during discontinuous anaerobic digestion

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WASTE MANAGEMENT 2016年第6期52卷 295-301页

作者： Zhao, Chen Yan, Hu Liu, Yan Huang, Yan Zhang, Ruihong Chen, Chang Liu, Guangqing Beijing Univ Chem Technol Coll Chem Engn Biomass Energy & Environm Engn Res Ctr Beijing 100029 Peoples R China Beijing Univ Chem Technol Coll Life Sci & Technol Beijing 100029 Peoples R China Univ Calif Davis Dept Biol & Agr Engn Davis CA 95616 USA

Huge amounts of fruit residues are produced and abandoned annually. The high moisture and organic contents of these residues makes them a big problem to the environment. Conversely, they are a potential resource to the world. Anaerobic digestion is a good way to utilize these organic wastes. In this study, the biomethane conversion performances of a large number of fruit residues were determined and compared using batch anaerobic digestion, a reliable and easily accessible method. The results showed that some fruit residues containing high contents of lipids and carbohydrates, such as loquat peels and rambutan seeds, were well fit for anaerobic digestion. Contrarily, residues with high lignin content were strongly recommended not to be used as a single substrate for methane production. multiple linear regression model was adopted to simulate the correlation between the organic component of these fruit residues and their experimental methane yield, through which the experimental methane yield could probably be predicted for any other fruit residues. Four kinetic models were used to predict the batch anaerobic digestion process of different fruit residues. It was shown that the modified Gompertz and Cone models were better fit for the fruit residues compared to the first-order and Fitzhugh models. The first findings of this study could provide useful reference and guidance for future studies regarding the applications and potential utilization of fruit residues. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Fruit residues Batch anaerobic digestion Substrate characteristics Methane production performance multiple linear regression model Kinetics

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A meta-model based simulation optimization using hybrid simulation-analytical modeling to increase the productivity in automotive industry

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MATHEMATICS AND COMPUTERS IN SIMULATION 2016年 120卷 120-128页

作者： Dengiz, Bema Ic, Yusuf Tansel Belgin, Onder Baskent Univ Dept Ind Engn TR-06810 Ankara Turkey Natl Prod Ctr Turkey TR-06690 Ankara Turkey

Simulation modeling is one of the most useful techniques to analyze and evaluate the dynamic behavior of the complex manufacturing systems. Combining the mathematical power of an analytical method and the modeling capability of simulation with optimization approach called hybrid simulation-analytical modeling has been presented rarely. In this study a production control model is developed for a paint shop department in an automotive company in Turkey. As a real case study, the optimum operating setting of a paint shop production line of automotive company is determined using hybrid simulation optimization approach. In the optimization stage of the study Design of Experiment (DoE) is used to identify critical variables of the system by fitting a polynomial to the experimental data in a multiple linear regression analysis. The meta-model is validated and shown that it provides good approximations to simulation results. Findings from hybrid simulation-analytical optimization approach give invaluable knowledge to the company for the re-designing and control of current manufacturing system to increase its productivity. (C) 2015 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.

关键词： Simulation optimization Design of experiment multiple linear regression model Paint shop production line Automotive industry

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A pipe leakage detection method for water floor warm system using multiple linear regression models

A pipe leakage detection method for water floor warm system ...

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2016 IEEE International Conference of Online Analysis and Computing Science(ICOACS 2016)

作者： Jie Li Guorong Chen Meng Lu Min Gao Wu Han Xukun Xia Online Analysis and Computing Science Laboratory Chongqing University of Science and Technology School of Electrical and Information Engineering Chongqing University of Science and Technology School of Petroleum Engineering Chongqing University of Science and Technology

This paper presented a multiple linear regression model to solve the leakage detection of warm water *** normal detection is to pressurize the pipes,where the disadvantage is the leakage can't be noticed in real *... 详细信息

关键词： water floor warm pipe leakage detection multiple linear regression model

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The Influence of Chemical Element on Properties of Deformed Steel Bar

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数字化用户 2017年第16期 120-121页

作者：王昱 710072 西北工业大学理学院陕西西安

This paper establishes the multiple linear regression model and the optimizing model, which adjust the composition proportion with the best strategy to improve the structure properties and control the cost by a company. Firstly, in order to get the effective data, we take filtering process method to eliminate withdrawn data. As for the numerous data, we take the pretreatment to revise the data until getting the reasonable data. Then according to the question, we set up a multiple linear regression model. Dealing with the correlation between these chemical elements, we adopt cluster analyses to discuss the result. Secondly, based on the model one, we mainly adopt controlled variable method. At first, we take the content of the chemical elements as dependent variable and the three properties as independent variable. Then we get the functional expression. Taking the important degree of the corresponding independent variables of the regression coefficient into consideration, we find out the coefficients can representative the influential degree. In this way, we could get the influence rule. Thirdly, with the improvement of the model, we set up a partial differential equation to attain the better results.

关键词： multiple linear regression model

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Research on Chinese Import Trade Based on Mulitiple linear regression model

Research on Chinese Import Trade Based on Mulitiple Linear R...

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2016 2nd Workshop on Advanced Research and Technology in Industry Applications(WARTIA 2016)

作者： Biao Xu School of North China Power University

ISBN: (纸本)9781510824430

This paper uses OLS parameter estimation method and GDP,per capita disposable income,export,foreign investment and exchange rate fluctuations as the five factors for our multiple linear regression analysis,and the economic significance,statistical significance and econometric test are *** conclusions are that:(1) the main factors that affect the import trade are GDP,urban residents per capita disposable income,total exports,influence of foreign investment on import trade,and fluctuations in the exchange rate,which has a negative influence on import *** two factors:GDP and the impact of foreign investment,have a serious overlap relationship and causes the col-linearity *** influence of exchange rate on import trade,can display by urban residents per capita disposable income.(2) According to the results of the test for heteroscedasticity can be concluded that the effect of 2007-2014 data of the model don't have heteroscedasticity.(3) The autocorrelation test shows that,the import trade by a year ago has majorly impact on the nowadays,total imports often with national fundamentals associated *** three quarter of imported trade resulted in an increase in the import trade *** front of the fourth quarter of imports often have a negative impact.

关键词： Import multiple linear regression model OLS econometric test

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Statistical modelling of the Conductivity Performance of Poly(3,4-ethylene- dioxythiophene/poly(Styrene Sulfonic Acid) Films

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CURRENT ANALYTICAL CHEMISTRY 2016年第2期12卷 124-140页

作者： Diah, Anang W. M. Holdsworth, Clovia I. Nur, Darfiana Beh, Eric Tadulako Univ Fac Teacher Training & Educ Discipline Chem Palu 94118 Indonesia Univ Newcastle Sch Environm & Life Sci Discipline Chem Callaghan NSW 2308 Australia Flinders Univ AtTonsley Sch Comp Sci Engn & Math Discipline Stat Bedford Pk SA 5042 Australia Univ Newcastle Sch Math & Phys Sci Discipline Stat Callaghan NSW 2308 Australia

This paper presents a comprehensive statistical evaluation of the conductivity performance of PEDOT/PSS films generated at various spin coating speeds (1000 to 5000 rpm) by correspondence analysis (CA), regression and ANOVA models. Poly(3,4-ethylenedioxythiophene) (PEDOT) is a highly conducting insoluble polymer which, when doped with poly(styrene sulfonic acid) (PSS) in water, results in a dispersion with good film forming properties. Our interest in PEDOT/PSS is in its application as an interfacial layer and gate electrode in organic photovoltaic and organic field effect transistor devices, respectively. The generation of a homogeneous spun-cast layer of PEDOT/PSS over the entire substrate for these intended applications is a function of the spin-coating speed which, in turn, affects the thickness of the film and, consequently, its conductivity measured by the four point probe. From correspondence analysis, we find that only the 1000 rpm spin-coating speed is strongly associated with high thickness and high resistivity (i.e. low conductivity), although further analysis of speeds 2000-5000 rpm shows that the spin-coating speed is still associated with the thickness of the films, and subsequently, their conductivities, such that the thinnest and most conductive films result from the highest spin-coating speed (5000 rpm). We also observed the phenomenon of the horseshoe effect from the CA displays and discussed the reasons for not resorting to detrending solutions for dealing with its presence. From multiple and nonlinear regression models, spin-coating speeds 1000 and 2000 rpm were found to produce films of less precise conductivity values as reflected in the absolute value of mean of residuals of nonlinear regression models while more precise and optimal conductivity values are obtained when the films are generated between 3000 and 5000 rpm. The ANOVA models showed that the means of conductivity of films obtained at 1000 rpm is statistically significantly different

关键词： Correspondence analysis multiple linear regression model nonlinear regression model one way ANOVA model PEDOT/PSS conductivity measurements

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