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A New Grey Model Based on Optimizing the Grey Derivative and the background value at the Same Time

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Journal of Systems Science and Information 2009年第4期7卷 343-350页

作者： Hua Yong Yong Wei College of Mathematics and Information China West Normal University Nanchong 637002Sichuan China

Based on both white response and connotation expression are geometric progression in the most primitive grey differential equation of GM（1,1）x（k）（k）＋ ax（1）（k） = b, this paper begins with generation of the time response .function＇s grey derivative at discrete points. Through derivative＇s definition, establishing a new GM（1,1） by optimizing grey derivative and background value. Then, getting the best coefficient c by introducing criterion function and it has proved that the new expression has the whitened exponent law coincident property and the whitened coefficient coincident property in theory. Finally, some examples show the new model has higher prediction precision.

关键词： time response function grey derivative background value optimization

Soil Geochemical background value and Environmental Quality Assessment in Jinan City

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Agricultural Biotechnology 2022年第5期11卷 72-75,79页

作者： Hongjin WANG Chao YU Wenkai REN Yan GUO Shandong Institute of Geological Survey Ji'nan 250012China Shandong Engineering Research Center for Geochemistry and Pollution Prevention and Control of Land Quality Ji'nan 250012China

[Objectives]This study was conducted to accurately assess soil and environmental quality in Jinan City. [Methods] Based on the multipurpose regional geochemical survey data of 1∶250 000 in Shandong Province, the differences between the soil geochemical background values of 54 indexes in Jinan City and the soil in the whole province and the comprehensive geochemical class of soil quality were studied. [Results] The contents of C and Cao in Jinan soil was significantly higher than the background values of Shandong Province. The Cd, Cr, Cu, F, Ni, Sn, MgO, Cao and Na_(2)O contents and pH value were higher than the abundance of the A soil layer in China, but the nutrient index contents of Se, I and OrgC were lower than the national background values. The surface soil quality in the study area was generally good, with the sum of superior, good and medium accounting for 99.76% of the total area of the study area. The distribution area of poor soil was the least, accounting for only 0.24%, and it was scattered near industrial and mining enterprises in the urban area of Jinan City, Laiwu District, Gangcheng District and Zhangqiu District, which was closely related to human activities. [Conclusions] This study has practical guiding significance for improving land use efficiency.

关键词： Surface soil background value Geochemistry Land quality Assessment Jinan city

Unequal Interval Grey Verhulst Modeling based on background Re-estimated value

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Unequal Interval Grey Verhulst Modeling based on background ...

Non-equal-interval direct optimizing Verhulst model that x(n) be taken as initial value and its application

第24届中国控制与决策会议

作者： YANG Ai-ping 1 , Xiong Wei 2 , Wu zi-heng 2 ,DAI Wen-zhan 2 1. Zhejiang University of Finance and Economics, Hangzhou, 310018, China. 2. Department of Automatic Control , Zhejiang Sci-Tech University, Hangzhou , 310018, China

Based on the study of background value, it is proved that the traditional estimation method of background value will cause Verhulst model’s inaccuracy. So a novel approach for re-estimating background value is put forward by unequal integral. The approach is applied in unequal interval grey Verhulst modeling and simulation result show it is of very high precise.

关键词： grey Verhulst model background value unequal interval sequence

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Journal of Southeast University(English Edition) 2008年第S1期24卷 17-21页

作者： Luo, Youxin Chen, Mianyun Che, Xiaoyi He, Zheming School of Mechanical Engineering Hunan University of Arts and Science Changde 415000 China School of Automatic Control Engineering Huazhong University of Science and Technology Wuhan 430074 China

To overcome the deficiencies of the existing Verhulst GM(1,1) model, based on the existing grey theory, a non-equal-interval direct optimum Verhulst GM(1,1) model is built which chooses a modified n-th component x(n) of X(0) as the starting condition of the grey differential model. It optimizes a modified β value and the background value, and takes two times fitting optimization. The new model extends equal intervals to non-equal-intervals and is suitable for general data modelling and estimating parameters of the direct Verhulst GM(1,1). The new model does not need to pre-process the primitive data, nor accumulate generating operation (AGO) and inverse accumulated generating operation (IAGO). It is not only suitable for equal interval data modelling, but also for non-equal interval data modelling. As the new information is fully used and two times fitting optimization is taken, the fitting accuracy is the highest in all existing models. The example shows that the new model is simple and practical. The new model is worth expanding on and applying in data processing or on-line monitoring for tests, social sciences and other engineering sciences.

关键词： grey system data processing Verhulst GM(1,1) non-equal interval direct modelling optimum background value two times fitting

Improvement and application of GM(1,1) model based on multivariable dynamic optimization

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Journal of Systems Engineering and Electronics 2020年第3期31卷 593-601页

作者： WANG Yuhong LU Jie School of Business Jiangnan UniversityWuxi 214122China

For the classical GM(1,1)model,the prediction accuracy is not high,and the optimization of the initial and background values is *** this paper,the Lagrange mean value theorem is used to construct the background value as a variable related to *** the same time,the initial value is set as a variable,and the corresponding optimal parameter and the time response formula are determined according to the minimum value of mean relative error(MRE).Combined with the domestic natural gas annual consumption data,the classical model and the improved GM(1,1)model are applied to the calculation and error comparison *** proves that the improved model is better than any other models.

关键词： grey prediction GM(1,1)model background value grey system theory

Chrono-Sequences of Elemental Contents in Tree Ringsand Soils

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Pedosphere 1994年第1期4卷 27-33页

作者： QIANJUN－LONG KESHAN－ZHE NanjingInstituteofGeographyandLimnology AcademiaSinicaNanjing210008China DepartmentofPhysics Nanjin

There exists a logarithmic linear correlation, i. e., In C'(Z, t) = a(Z) + b(Z) ln(Z, t) where Z is the atomicnumber of element and t the year when tree ring grows between the chemical element contents in tree ringsC(Z, t) and those in the soils near the tree roots C'(Z, t).By determining the elemental contents of the annual growth rings of trees, we could establish the chrono-sequences of elemental contents in the tree rings, thus calculating that of the soil, that is, reproducing thedynamic changes of contents of elements in the soil C'(Z, t). The background values of elements in the soilunder site conditions of the tree could be estimated from the minimum C(Z, t_0) in the chrono-sequences ofelemental contents in the tree rings.

关键词： background value chroncasequences elemental contents soils tree rings

Concentration and seasonal variation of 10Be in surface aerosols of Lhasa,Tibet

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Science Bulletin 2010年第23期 2575-2581页

作者： HUANG Jie1,7,KANG ShiChang1,2,SHEN ChengDe3,CONG ZhiYuan1,LIU KeXin4,WANG Wei5 & LIU LiChao6 1 Key Laboratory of Tibetan Environment Changes and Land Surface Processes,Institute of Tibetan Plateau Research,Chinese Academy of Sciences,Beijing 100085,China 2 State Key Laboratory of Cryospheric Science,Chinese Academy of Sciences,Lanzhou 730000,China 3 Key Laboratory of Isotope Geochronology and Geochemistry,Guangzhou Institute of Geochemistry,Chinese Academy of Sciences,Guangzhou 510000,China 4 State Key Laboratory of Nuclear Physics and Technology,Peking University,Beijing 100871,China 5 Institute of Plateau Atmosphere and Environment Sciences,Tibet Meteorological Bureau,Lhasa 850000,China 6 Cold and Arid Regions Environmental & Engineering Research Institute,Chinese Academy of Sciences,Lanzhou 730000,China 7 Graduate University of the Chinese Academy of Sciences,Beijing 100049,China

Thirty samples of total suspended particles were collected at a site in western part of Lhasa,Tibet from August 2006 to July *** 10Be concentrations were determined by Accelerator Mass Spectrometer (AMS).Analysis of correlation between 10Be concentrations and meteorological factors revealed that the wet scavenging has little effect on 10Be.10Be can be used as a proxy of transport processes of the upper atmosphere over the Tibetan *** of correlation between 10Be concentrations and NCEP reanalysis data demonstrated that higher 10Be concentrations in spring were probably caused by the atmosphere exchange from stratosphere to troposphere during February to *** 10Be concentrations during August to September were consistent with the synchronous lower O3 values,suggestive of both 10Be and O3 were probably influenced by the atmosphere exchange from troposphere to stratosphere.

关键词： 10Be concentration background value seasonal variation Lhasa

Improvement on Unequal Interval Grey Forecast Model

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Improvement on Unequal Interval Grey Forecast Model

A New Method of Building Grey Forecasting Model

The Second Conference on Fuzzy Information & Engineering

作者： FENGXIAO WANG Department of Mathematics and Computer Science, Shaanxi University of Technology, Hanzhong, shaanxi, China

Unequal Interval gray forecast model is dealt with in this paper. Firstly, the new calculational formula about background value is established for unequal interval gray forecast model based on the integrating. Secondly, the improvement gray forecast model is presented to solve practical problems. It improves the unequal interval gray forecast model and enhances the prediction precision. Finally, in order to comparison the practicability and reliability of this model, some example was validated.

关键词： background value calculational formula gray forecast unequal interval

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A New Method of Building Grey Forecasting Model