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6th International Conference on Environmental Science and Civil Engineering (ESCE)

作者： Zhang, Bo Qiu, Lijun Zhou, Zhanxue Hebei Univ Architecture Zhang Jiakou 075000 Peoples R China Hebei Key Lab Diag Reconstruct & Antidisaster Civ Zhang Jiakou 075000 Peoples R China

The settlement deformation of high-rise buildings is related to many factors, which are mainly about floor load and time. Based on the measured data of building settlement deformation in 16 periods, in this paper, the number of floors and accumulated settlement time are selected as the independent variables, and the accumulated settlement is used as the dependent variable. The data in the previous 11 periods are used as the modeling sequence to establish a multiple linear regression model and predict the deformation in the last 5 periods. The results show that if there is no fluctuation in the original sequence, the fitting and prediction results are good and meet the actual engineering requirements. It is of practical value and significance for the prediction of building deformation.

关键词： multiple linear regression model deformation monitoring settlement deformation floor loads

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Research on Influencing Factors of Chinese Mechanical and Electrical Products Exporting to Thailand Market——Based on multiple linear regression model

Research on Influencing Factors of Chinese Mechanical and El...

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作者： Yin Luyu Yu Jing School of Economics and Management Nanjing University of Science and Technology

Due to some developed countries limitation in technical barriers and frequent trade friction,China's exports of mechanical and electrical products to its key markets such as the United States,Japan,South Korea,and Germany have declined,which has dragged down the overall decline in exports of domestic mechanical and electrical products,and impelledChina's mechanical and electrical export companies actively exploring and developing emerging markets and diversify risks,such as ASEAN *** the establishment of the China-ASEAN Free Trade Area in 2010,favorable policy conditions have led to the rapid development of bilateral trade between China and ASEAN *** and electrical products,as the pillar products in China's export trade,have also developed ***,in recent years,the growth of exports of mechanical and electrical products to ASEAN countries has encountered a ***,this article takes Thailand as an example,based on relevant trade data from 2010 to 2019,and uses a multiple regression model to analyze the impact of the gap in GDP per capita between the two countries,Thailand's GDP,technology R&D investment,foreign direct investment and exchange rate on China's export of mechanical and electrical products to the Thai *** put forward relevant countermeasures and suggestions based on the empirical results.

关键词： Mechanical and Electrical Products Export Competitiveness multiple linear regression model Influencing Factors

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The Hourly Simulation of PM2.5 Particle Concentrations Using the multiple linear regression (MLR) model for Sea Breeze in Split, Croatia

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WATER AIR AND SOIL POLLUTION 2021年第7期232卷 1-9页

作者： Lesar, Tanja Trosic Filipcic, Anita Croatian Meteorol & Hydrol Serv Zagreb Croatia Univ Zagreb Dept Geog Fac Sci Zagreb Croatia

The main objective of this study is to simulate the hourly concentrations of the PM2.5 concentrations using the multiple linear regression (MLR) model for the selected sea breeze days in Split, Croatia. Stepwise adjustment is used for the selection of predictors. A predictor characteristic to the daily and nightly part of the coastal circulation, calculated as hourly temperature change to the temperature at the time of the sea breeze lulls, was found to be significant for PM2.5 particles during sea breeze. The mean monthly values of the MLR model simulated and measured PM2.5 hourly concentrations for the selected sea breeze cases were simulated relatively well. The hourly simulations also show a very good fit with the hourly measurements, and the index of agreement (IA) is 0.9 for the daily and 0.8 for the nightly part of the coastal circulation.

关键词： Coastal circulation multiple linear regression model PM2 5 concentrations Sea breeze

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Spatial distribution of soil moisture estimates using a multiple linear regression model and Korean geostationary satellite (COMS) data

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AGRICULTURAL WATER MANAGEMENT 2019年 213卷 580-593页

作者： Lee, Yonggwan Jung, Chunggil Kim, Seongjoon Konkuk Univ Dept Civil Environm & Plant Engn 1 Hwayang Dong Seoul 05029 South Korea

This study attempts to estimate the spatial distribution of the soil moisture (SM) in South Korea (99,260 km(2)) from January 2013 to May 2015 using a multiple linear regression (MLR) model with data from the Korean multipurpose geostationary Communication, Ocean and Meteorological Satellite (COMS), and land surface temperature (LST) data. The normalized distribution vegetation index (NDVI) from the moderate-resolution imaging spectroradiometer (MODIS) on board the Terra satellite was used to reflect the vegetation variations. Observed precipitation data measured by automatic weather stations (AWSs) operated by the Korea Meteorological Administration (KMA) were collected, and SM data were collected from 38 stations operated by various institutions. The regression coefficients of the MLR model were estimated seasonally considering five days of preceding precipitation. The p-values of all regression coefficients were below 0.05, and all coefficients of determination (R-2) ranged from 0.17 to 0.63. Specifically, the R-2 of loam in the summer was the highest at 0.63, and most of the R-2 values were 0.4 or higher. The results of the SM regression showed that the overall R-2 was higher than 0.4 and that the root mean square error (RMSE) was less than 5% at all but a few stations. A time series analysis of the simulated SM revealed that the observed SM data ranged from 0 to 20% for sand, 10 to 30% for loam, 20 to 40% for clay and 30 to 50% for silt. The simulated SM followed the volatility of the observed data in most of the soils. The spatial distribution of the simulated SM showed the same trends with the observed data on the monthly spatial precipitation map. Consequently, the estimated map of the soil moisture index (SMI) can be used to better understand the severity of drought and the variability in the SM.

关键词： COMS MODIS NDVI multiple linear regression model Spatial distribution of soil moisture Remote sensing

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Correlation Analysis of Fiscal Revenue and Housing Sales Price Based on multiple linear regression model

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数学计算（中英文版） 2020年第1期9卷 3-12页

作者： Wei Zheng Xinyi Li Nanxing Guan Kun Zhang School of Mathematics and Statistics Chuxiong Normal UniversityChuxiong675000China

This paper selects seven indicators of financial revenue and housing sales price in recent 19 years in China,and uses SPSS and Excel to carry out descriptive statistics,independent sample t-test,correlation analysis and regression analysis to comprehensively study the correlation between financial revenue and housing sales price in China,and establishes the relationship between financial revenue and housing sales price When the average selling price of commercial housing increases by one unit,the fiscal revenue will increase by 27.855 points.

关键词： Financial Revenue Housing Sales Price Correlation Analysis multiple linear regression model

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Prediction Analysis for Building Deformation Based on multiple linear regression model

Prediction Analysis for Building Deformation Based on Multip...

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作者： Bo Zhang Lijun Qiu Zhanxue Zhou Hebei University of Architecture Hebei Key Laboratory of Diagnosis Reconstruction and Anti-disaster of Civil Engineering

The settlement deformation of high-rise buildings is related to many factors,which are mainly about floor load and *** on the measured data of building settlement deformation in 16 periods,in this paper,the number of floors and accumulated settlement time are selected as the independent variables,and the accumulated settlement is used as the dependent *** data in the previous 11 periods are used as the modeling sequence to establish a multiple linear regression model and predict the deformation in the last 5 *** results show that if there is no fluctuation in the original sequence,the fitting and prediction results are good and meet the actual engineering *** is of practical value and significance for the prediction of building deformation.

关键词： multiple linear regression model deformation monitoring settlement deformation floor loads

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Association between resting-state brain network topological organization and creative ability: Evidence from a multiple linear regression model

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BIOLOGICAL PSYCHOLOGY 2017年 129卷 165-177页

作者： Jiao, Bingqing Zhang, Delong Liang, Aiying Liang, Bishan Wang, Zengjian Li, Junchao Cai, Yuxuan Gao, Mengxia Gao, Zhenni Chang, Song Huang, Ruiwang Liu, Ming South China Normal Univ Sch Psychol Ctr Study Appl Psychol Key Lab Mental Hlth & Cognit Sci Guangdong Prov Guangzhou Guangdong Peoples R China Guangdong Sci Ctr Guangzhou Guangdong Peoples R China Guangdong Polytech Normal Univ Coll Educ Guangzhou Guangdong Peoples R China

Previous studies have indicated a tight linkage between resting-state functional connectivity of the human brain and creative ability. This study aimed to further investigate the association between the topological organization of resting-state brain networks and creativity. Therefore, we acquired resting-state fMRI data from 22 high-creativity participants and 22 low-creativity participants (as determined by their Torrance Tests of Creative Thinking scores). We then constructed functional brain networks for each participant and assessed group differences in network topological properties before exploring the relationships between respective network topological properties and creative ability. We identified an optimized organization of intrinsic brain networks in both groups. However, compared with low-creativity participants, high-creativity participants exhibited increased global efficiency and substantially decreased path length, suggesting increased efficiency of information transmission across brain networks in creative individuals. Using a multiple linear regression model, we further demonstrated that regional functional integration properties (i.e., the betweenness centrality and global efficiency) of brain networks, particularly the default mode network (DMN) and sensorimotor network (SMN), significantly predicted the individual differences in creative ability. Furthermore, the associations between network regional properties and creative performance were creativity-level dependent, where the difference in the resource control component may be important in explaining individual difference in creative performance. These findings provide novel insights into the neural substrate of creativity and may facilitate objective identification of creative ability.

关键词： Creativity Resting-state fMRI Connectome multiple linear regression model Individual difference

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Using multiple linear regression model to estimate thunderstorm activity 1

Using multiple linear regression model to estimate thunderst...

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Annual International Conference on Information Technology and Digital Applications (ICITDA)

作者： Suparta, W. Putro, W. S. Univ Kebangsaan Malaysia Space Sci Ctr ANGKASA Inst Climate Change Bangi 43600 Selangor Darul Malaysia

This paper is aimed to develop a numerical model with the use of a nonlinear model to estimate the thunderstorm activity. Meteorological data such as Pressure (P), Temperature (T), Relative Humidity (H), cloud (C), Precipitable Water Vapor (PWV), and precipitation on a daily basis were used in the proposed method. The model was constructed with six configurations of input and one target output. The output tested in this work is the thunderstorm event when one-year data is used. Results showed that the model works well in estimating thunderstorm activities with the maximum epoch reaching 1000 iterations and the percent error was found below 50%. The model also found that the thunderstorm activities in May and October are detected higher than the other months due to the inter-monsoon season.

关键词： multiple linear regression model Meteorology data Thunderstorm estimation

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A Study of Spatial Soil Moisture Estimation Using a multiple linear regression model and MODIS Land Surface Temperature Data Corrected by Conditional Merging

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REMOTE SENSING 2017年第8期9卷

作者： Jung, Chunggil Lee, Yonggwan Cho, Younghyun Kim, Seongjoon Konkuk Univ Dept Civil Environm & Plant Engneering 120 Neungdong Ro Seoul 05029 South Korea Korea Water Resources Corp Hydrometeorol Cooperat Ctr 11 Gyoyookwon Ro Gwacheon Si 13841 Gyeonggi Do South Korea

This study attempts to estimate spatial soil moisture in South Korea (99,000 km(2)) from January 2013 to December 2015 using a multiple linear regression (MLR) model and the Terra moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (LST) and normalized distribution vegetation index (NDVI) data. The MODIS NDVI was used to reflect vegetation variations. Observed precipitation was measured using the automatic weather stations (AWSs) of the Korea Meteorological Administration (KMA), and soil moisture data were recorded at 58 stations operated by various institutions. Prior to MLR analysis, satellite LST data were corrected by applying the conditional merging (CM) technique and observed LST data from 71 KMA stations. The coefficient of determination (R-2) of the original LST and observed LST was 0.71, and the R-2 of corrected LST and observed LST was 0.95 for 3 selected LST stations. The R-2 values of all corrected LSTs were greater than 0.83 for total 71 LST stations. The regression coefficients of the MLR model were estimated seasonally considering the five-day antecedent precipitation. The p-values of all the regression coefficients were less than 0.05, and the R-2 values were between 0.28 and 0.67. The reason for R-2 values less than 0.5 is that the soil classification at each observation site was not completely accurate. Additionally, the observations at most of the soil moisture monitoring stations used in this study started in December 2014, and the soil moisture measurements did not stabilize. Notably, R-2 and root mean square error (RMSE) in winter were poor, as reflected by the many missing values, and uncertainty existed in observations due to freezing and mechanical errors in the soil. Thus, the prediction accuracy is low in winter due to the difficulty of establishing an appropriate regression model. Specifically, the estimated map of the soil moisture index (SMI) can be used to better understand the severity of droughts with the v

关键词： spatial soil moisture MODIS LST MODIS NDVI conditional merging multiple linear regression model

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Recovering defective Landsat 7 Enhanced Thematic Mapper Plus images via multiple linear regression model

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IET COMPUTER VISION 2016年第8期10卷 788-797页

作者： Sadiq, Asmaa Sulong, Ghazali Edwar, Loay Univ Technol Malaysia Fac Comp MaGIC X UTM IRDA Digital Media Ctr Utm Skudia Johor Takzin 81310 Malaysia Univ Al Mustansiriyah Coll Sci Dept Comp Baghdad Iraq Univ Baghdad Coll Sci Dept Comp Baghdad Iraq

Since 2003, the scan line corrector (SLC) of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor has failed permanently, inhibiting the retrieval or scanning of 22% of the pixels in each Landsat 7 SLC-off image. This utter failure has seriously limited the scientific applications and usability of ETM+ data. Precise and complete recovery of the missing pixels for the Landsat 7 SLC-off images is a challenging issue and developing an efficient gap-fill algorithm with improved ETM+ data usability has been ever-demanding. In this study, a new gap filling method has been introduced to reconstruct the SLC-off images via multi-temporal SLC-off auxiliary fill images. A correlation is established between the corresponding pixels in the target SLC-off image and two auxiliary fill images in parallel using the multiple linear regressions model. Both simulated and actual defective Landsat 7 images were tested to assess the performance of the proposed model by comparing with two multi-temporal data based methods, the local linear histogram matching method and Neighbourhood Similar Pixel Interpolator method. The quantitative evaluations indicate that the proposed method makes an accurate estimate of the missing values even for more temporally distant fill images.

关键词： remote sensing geophysical image processing image resolution image enhancement regression analysis infrared imaging image sensors image reconstruction artificial satellites defective Landsat 7 enhanced thematic mapper plus images recovery multiple linear regression model scan line corrector Landsat 7 SLC-off image Landsat 7 enhanced thematic mapper plus sensor ETM+ data usability gap filling method missing value estimation

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