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Neurocomputing

作者： Appolloni, Bruno Bassis, Simone Malchiodi, Dario Pedrycz, Witold Department of Computer Science University of Milan Via Comelico 39/41 20135 Milano Italy Department of Electrical and Computer Engineering University of Alberta ECERF 9107 - 116 Street Edmonton AL T6G 2V4 Canada

We introduce a regression method that fully exploits both global and local information about a set of points in search of a suitable function explaining their mutual relationships. The points are assumed to form a repository of information granules. At a global level, statistical methods discriminate between regular points and outliers. Then the local component of the information embedded in the former is used to draw an optimal regression curve. We address the challenge of using a variety of standard machine learning tools such as support vector machine (SVM) or slight variants of them within the unifying hat of Granular Computing realm to obtain a definitely new featured nonlinear regression method. The performance of the proposed approach is illustrated with the aid of three well-known benchmarks and ad hoc featured datasets. © 2008 Elsevier B.V. All rights reserved.

关键词： Information granules Benchmarking Granular computing Granulation regression analysis Support vector machines Algorithmic Inference Global and local informations Kernel methods linear regression confidence region Modified SVM Non linear regression method regression method Standard machines

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Storing characteristics and main controlling factors of connate water in lower Paleozoic shales in southeast Chongqing, China

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JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2022年第PartB期215卷

作者： Xu, Liangwei Wei, Hao Chen, Lei Liu, Luofu Jiang, Zhenxue Yang, Keji Li, Xiao Peking Univ Sch Earth & Space Sci MOE Key Lab Orogen Belt & Crustal Evolut Beijing 100781 Peoples R China Hebei GEO Univ Hebei Key Lab Strateg Crit Mineral Resources Shijiazhuang 050031 Peoples R China Univ Sci & Technol Dept Resource Engn Beijing 100083 Peoples R China China Univ Petr East China Shandong Prov Key Lab Deep Oil & Gas Qingdao 266580 Peoples R China China Univ Petr State Key Lab Petr Resources & Prospecting Beijing 102249 Peoples R China

Recent studies show that the shale gas content and storage space are influenced by connate water, while it is unclear how connate water occurs in different nanoscale pores in high and overmature shales, and research concerning the occurrence characteristics and factors controlling connate water in overmature shale gas formations is scarce. In this research, overmature lower Paleozoic shale samples from southeastern Chongqing were selected for connate water distribution and factor analysis. The results show that connate water in the lower Paleozoic shale occurs in organic matter and clay minerals, mainly occurs in clay minerals and tends to form clay-bound water in clay minerals. The effect of the connate water content (C-IW) on the inorganic nonmicropore (mesopore + macropore) surface area (SA) is greater than that on the organic nonmicropore SA. The CIW mainly affects the micropore structure parameters of clay minerals, and the total organic carbon (TOC) content is the main factor controlling the shale micropore structure. Connate water occurs in shale micropores and nonmicropores, and adsorption and filling states simultaneously exist and are distributed in < 10 nm mesopores and 0.4-0.6 nm micropores;this distribution reduces the pore structure parameters of inorganic matter in shale, especially the nonmicropore SA. The effect of the CIW on nonmicropore SA and micropore pore volume (PV) in inorganic minerals is significantly greater than that of organic matter. Connate water mainly occurs in inorganic mineral pores and mainly occupies the mineral nonmicropore SA. Connate water significantly reduces the inorganic pore structure parameters, while its effect on organic pores is limited.

关键词： Connate water content Equilibrium water saturation linear regression method Pore structure parameters Organic pores

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EVALUATION OF A regression PREDICTION MODEL FOR SURFACE ROUGHNESS OF WOOD-POLYETHYLENE COMPOSITE (WPC)

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SURFACE REVIEW AND LETTERS 2017年第Sup2期24卷 1850033-1850033页

作者： Shi, Wenyong Ma, Yan Yang, Chunmei Jiang, Bin Li, Zhe Harbin Univ Sci & Technol Div Grad Harbin 150080 Heilongjiang Peoples R China Harbin Engn Univ Minist Educ Key Lab Superlight Mat & Surface Technol Harbin 150001 Heilongjiang Peoples R China Northeast Forestry Univ Forest Woodworking Machinery Res & Dev Ctr Harbin 150040 Heilongjiang Peoples R China Harbin Univ Sci & Technol Sch Mech Engn Harbin 150080 Heilongjiang Peoples R China

Milling processing is an important way to obtain wood-polyethylene composite (WPC) end products. In order to improve the processing efficiency and surface quality of WPC and meet the practical application requirements, this paper focussed on morphology and roughness of the WPC-milled surface and studied surface quality changes under different cutting parameters and milling methods through multi-parameters milling experiments. The milling surface morphology and roughness of WPC were analyzed and measured during cut-in, cutting and cut-out sections. It also revealed the affect rule of different cutting parameters and milling methods on milled surface morphology and roughness. The results show that the milling surface roughness of WPC products with wood powder content of 70% is significantly larger than the one whose wood powder content is 60%, and defects such as holes are also relatively more. Finally, a surface roughness prediction model was established based on the mathematical regression method and its multi-factor simulation was carried out. A comparative analysis of predictive and experimental values was performed to verify the reliability of the model. It could also provide theoretical guidance and technical guarantee for high processing quality of WPC milling and cutting.

关键词： Wood-polyethylene composite (WPC) milling surface roughness linear regression method

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Variability of Spatially Grid-Distributed Precipitation over the Huaihe River Basin in China

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WATER 2017年第7期9卷 489-489页

作者： Yu, Zhi-Lei Yan, Deng-Hua Ni, Guang-Heng Do, Pierre Yan, Deng-Ming Cai, Si-Yu Qin, Tian-Ling Weng, Bai-Sha Yang, Mei-Jian Tsinghua Univ THU Dept Hydraul Engn Beijing 100084 Peoples R China China Inst Water Resources & Hydropower Res IWHR State Key Lab Simulat & Regulat Water Cycle River Beijing 100038 Peoples R China IWHR Dept Water Resources Beijing 100038 Peoples R China Donghua Univ Coll Environm Sci & Engn Shanghai 201620 Peoples R China Univ Connecticut Dept Civil & Environm Engn Storrs CT 06269 USA

This study investigates spatial characteristics of annual and decadal precipitation in the Huaihe River basin. Daily precipitation data, obtained from meteorological gauges, are analyzed for a 51-year period, from 1961 to 2011. Precipitation is analyzed in grids (5 km(2)) with respect to temporal variability. The spatial distribution and intensity of annual rainfall (mm/10 year), determined by the linear regression method, reveals a slight increase of 3 mm/10 year over the basin. However, the trend did not present a significant change at 95% significance level in the most of basin. Precipitation is mostly increasing for each ten-year periods during the total 51 years. The annual precipitation randomicity was calculated from the non-uniform coefficient Cv (coefficient of variation) test and showed a significant non-uniform spatial distribution, indicating that randomicity of annual rainfall was the moderate variability. The Pettitt test determined that the abrupt change points occurred mainly in 1965, 1975 and 2002. Wavelet analysis showed that cyclic variations appeared almost every 5 to 10 years, accounting for 36% of the basin area. Meanwhile, these cycles tended to be delimited by the abrupt change points. This study aims to provide insights for water resources management, mitigation of climate change effects and water supply in the Huaihe River basin and surrounding watersheds.

关键词： wtershed hydrology grid-distributed precipitation Huaihe River basin linear regression method coefficient of variation Pettitt test wavelet analysis

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Uncertainty in the mutual calibration method for the traceable thickness measurement of ultra-thin oxide films

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METROLOGIA 2021年第3期58卷 034002-034002页

作者： Lee, Seung Mi Woo, Jin Chun Kim, Tae Gun Kim, Kyung Joong Korea Res Inst Sci & Stand Surface Anal Team Daejeon 34113 South Korea Measurement Assurance Tech Inst Sejong 30130 South Korea

Mutual calibration by a combination of a zero-offset method and a length-unit traceable method has been suggested as a promising approach to determine the traceable thickness of ultra-thin oxide films. However, the measurement uncertainty is somewhat complicated to calculate because the standard uncertainties from the two measurement methods and the linear regression process should be combined. In this study, the mutual calibration method to evaluate the film thickness and uncertainty of ultra-thin oxide films was investigated. The algorithm of the linear regression equation in the mutual calibration method was studied and the uncertainty calculation program for the thickness measurement by mutual calibration was developed. The result will provide an effective and useful guideline to certify the thickness of the ultra-thin oxide film on Si(100) substrate which is used as the gate oxide in the semiconductor devices. The magnitude of the relative expanded uncertainty in the thickness measurement by mutual calibration is in the range from 8.6% to 9.3%.

关键词： uncertainty ultra-thin oxide mutual calibration thickness measurement linear regression method

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Comparison of some linear regression methods – available in R – for a QSPR problem

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BMC Chemistry 2009年第1期3卷 1-1页

作者： K Varmuza P Filzmoser Vienna University of Technology Institute of Chemical Engineering Getreidemarkt 9/166 A-1060 Vienna Austria Vienna University of Technology Institute of Statistics and Probability Theory Wiedner Hauptstrasse 8-10 A-1040 Vienna Austria

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Precipitation variability and its trend detection for monitoring of drought hazard in northern mountainous region of Pakistan

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ARABIAN JOURNAL OF GEOSCIENCES 2020年第15期13卷 698-698页

作者： Khan, Imran Waqas, Tahir Samiullah Ullah, Safi Univ Peshawar Ctr Disaster Preparedness & Management CDPM Peshawar Pakistan Univ Peshawar Natl Ctr Excellence Geol Peshawar Pakistan Univ Peshawar Dept Geog Peshawar Pakistan Nanjing Univ Informat Sci & Technol NUIST Sch Atmospher Sci Nanjing 210044 Peoples R China

The Standardized Precipitation Index (SPI) is a powerful tool, requiring only precipitation data for calculating the intensity, duration, magnitude, severity and frequency of drought. Moreover, it provides helpful coverage of drought impacts on multi time scales. In this study, the SPI technique was applied to the dataset of 30 years (1986-2015) to detect drought condition in Northern Pakistan, which is a frequent drought-hit area. The coefficient of variability (CV) was used to analyze precipitation trend, while linear regression model was adopted to detect trend. The detected precipitation variability was spatially interpolated by applying the Inverse Distance Weighted (IDW) technique. It is evident from the analysis that there is great variability in precipitation pattern and trend in the study area. During the winter season, a positive trend in the precipitation variability was detected in the Himalaya and Karakorum region. In the Hindukush region, only Pattan weather station has observed a positive variability trend. In contrast to winter variability, pre-monsoon season has observed an increased variability in the Hindukush region, while the Karakorum and Himalayas regions observed a negative trend. The monsoon season has observed a decreased variation in precipitation throughout the study area except for Pattan. In post-monsoon, Skardu weather station of Himalayas, Gupis and Bunji of Karakorum region and Pattan of Hindukush region have witnessed increased precipitation variability. The meteorological stations of Karakoram and Himalaya have noticed a negative trend of precipitation variability, while in the Hindukush region, all the meteorological stations have witnessed a positive trend of variability except Saidu Sharif and Dir stations. The results of SPI also indicated a drought condition in the study area. Similarly, the SPI results of all return periods have shown a significant drought condition in the Himalayas followed by-in terms of frequency and magni

关键词： SPI linear regression method Drought hazard MRP Pakistan

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Dissecting estimation of conductances in subthreshold regimes

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BMC Neurosci 2014年第SUPPL 1期15卷 P151-P151页

作者： Catalina Vich Antoni Guillamon Dept. of Mathematics and Computer Science Universitat de les Illes Balears Palma 07122 Spain Dept. of Applied Mathematics I EPSEB Universitat Politècnica de Catalunya 08028 Barcelona Spain

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Investigating the persistence of accuracy of genomic predictions over time in broilers

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JOURNAL OF ANIMAL SCIENCE 2021年第9期99卷 skab239页

作者： Hidalgo, Jorge Lourenco, Daniela Tsuruta, Shogo Masuda, Yutaka Breen, Vivian Hawken, Rachel Bermann, Matias Misztal, Ignacy Univ Georgia Dept Anim & Dairy Sci Athens GA 30602 USA Cobb Vantress Inc Siloam Springs AR 72761 USA

Accuracy of genomic predictions is an important component of the selection response. The objectives of this research were: 1) to investigate trends for prediction accuracies over time in a broiler population of accumulated phenotypes, genotypes, and pedigrees and 2) to test if data from distant generations are useful to maintain prediction accuracies in selection candidates. The data contained 820K phenotypes for a growth trait (GT), 200K for two feed efficiency traits (FE1 and FE2), and 42K for a carcass yield trait (CY). The pedigree included 1,252,619 birds hatched over 7 years, of which 154,318 from the last 4 years were genotyped. Training populations were constructed adding 1 year of data sequentially, persistency of accuracy over time was evaluated using predictions from birds hatched in the three generations following or in the years after the training populations. In the first generation, before genotypes became available for the training populations (first 3 years of data), accuracies remained almost stable with successive additions of phenotypes and pedigree to the accumulated dataset. The inclusion of 1 year of genotypes in addition to 4 years of phenotypes and pedigree in the training population led to increases in accuracy of 54% for GT, 76% for FE1, 110% for CY, and 38% for FE2;on average, 74% of the increase was due to genomics. Prediction accuracies declined faster without than with genomic information in the training populations. When genotypes were unavailable, the average decline in prediction accuracy across traits was 41% from the first to the second generation of validation, and 51% from the second to the third generation of validation. When genotypes were available, the average decline across traits was 14% from the first to the second generation of validation, and 3% from the second to the third generation of validation. Prediction accuracies in the last three generations were the same when the training population included 5 or 2 years of da

关键词： independent chromosome segments linear regression method persistence of accuracy prediction accuracy single-step GBLUP

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Optimal Operation Study of Qing River Cascade Reservoirs Based on GA with Uncertainty and Flow Transmission Considered

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Procedia Engineering 2012年 28卷 448-452页

作者： Ran Zhou Kan Yang College of Hydrology and Water Resources Hohai UniversityNo.1Xikang RoadGulou District Nanjing 210098China

This paper presented a simulation method which considers the uncertainty and flow transmission in optimal operation of Qing River cascade reservoirs. Latin hypercube method was applied to simulate the uncertain inflow, and its sampling frequency and accuracy were very satisfied. linear regression method was used to deal with the damping and deformation in the process of flow transmission. And Genetic algorithm(GA) was found application for solving the optimal operation model of Qing River cascade reservoirs. According to the method presented we could obtain the scheduling scheme of cascade reservoirs under different risk rates which were helpful to the decision-making. The result showed that the method is practical.

关键词： Qing River cascade reservoirs Latin hypercube Flow transmission linear regression method Genetic algorithm

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