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Development and application of ergodicity model with FRCM and FLAR for hydrological process

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science China(Technological sciences) 2009年第2期52卷 379-386页

作者： WANG HongRui1, FENG QiLei2. LIN Xin3.& ZENG WenYi4 1 College of Water science, Key Laboratory for Water and Sediment sciences of the Ministry of Education,{2.,{3., China 2.School of science, beijing institute of Education, beijing 100011, China 3.School of Mathematical sciences,{2.,{3., China 4 College of Information science and Technology,{2.,{3., China 1. College of Water science Key Laboratory for Water and Sediment Sciences of the Ministry of Education Beijing Normal University Beijing 100875 China 2. School of science Beijing Institute of Education Beijing 100011 China 3. School of Mathematical sciences Beijing Normal University Beijing 100875 China 4. College of Information science and Technology Beijing Normal University Beijing 100875 China

In this paper, a new ergodic property analysis model of hydrological process is proposed based on fuzzy-rough c-means clustering (FRCM), autocorrelogram, and fuzzy least absolute regression (FLAR). A precipitation time series (1951―2.04) from Shanghai Hydrology Station is then analyzed with the model. The results show that the precipitation time series of April, May, June, and September has er-godic property. We conclude that in the long run, the precipitation of April, May, June, and September will not keep decreasing; it will converge to its mean value in some period.

关键词： hydrological process ergodic autocorrelogram fuzzy-rough c-means clustering fuzzy least absolute regression

Implementation of a multiple round quantum dense coding using nuclear magnetic resonance

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science China(Physics,Mechanics & Astronomy) 2005年第6期48卷 706-715页

作者： ZHANG Jingfu1, XIE Jingyi2. WANG Chuan1, DENG Zhiwei3. LU Zhiheng4, & LONG Guilu1,5 1. Key Laboratory For Quantum Information and Measurements of MOE, Department of Physics, Tsinghua university, {2. 100084,China 2. Department of Materials {2. and Engineering,{3., beijing 100875, China 3. Testing and Analytical Center,{3., beijing 100875,China 4. Department of Physics,{3., beijing 100875, China 5. Key Laboratory For atomic and Molecular Nano{2.s, Tsinghua university, {2. 100084,China 1. Key Laboratory For Quantum Information and Measurements of MOE Department of Physics Tsinghua University 100084 Beijing China 2. Department of Materials science and Engineering Beijing Normal University 100875 Beijing China 3. Testing and Analytical Center Beijing Normal University 100875 Beijing China 4. Department of Physics Beijing Normal University 100875 Beijing China 5. Key Laboratory For Atomic and Molecular Nanosciences Tsinghua University 100084 Beijing China

A multiple round quantum dense coding scheme based on the quantum phase estimation algorithm is proposed and implemented in a three qubit nuclear magnetic resonance (NMR) quantum computer. Using an m + 1 qubit system, Bob can transmit one of 2.+1 messages to Alice, through manipulating only one qubit and exchanging it between Alice and Bob for m rounds. The information capacity is enhanced to m + 1 bits as compared to m bits in a classical scheme. The scheme has been demonstrated in NMR system, and the experimental results show a good agreement between theory and experiment.

关键词： quantum dense coding, multiple round, nuclear magnetic resorance

A trust region algorithm for bilevel programing problems

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Chinese science Bulletin 1998年第10期43卷 820-824页

作者： LIU Guoshan 1, HAN Jiye 2.and WANG Shouyang 3.1. Department of Mathematics, beijing normal university,{2., China 2. {2. of Applied Mathematics, Chinese Academy of {3.s, beijing 100080, China 3. {2. of Systems {3., Chi Department of Mathematics Beijing Normal University Beijing China institute of Applied Mathematics Chinese Academy of Sciences Beijing China institute of Systems science Chinese Academy of Sciences Beijing China

A trust region algorithm is proposed for solving bilevel programming problems where the lower level programming problem is a strongly convex programming problem with linear constraints. This algorithm is based on a tr... 详细信息

关键词： bilevel programming problem trust region algorithm global convergence.

A distributed hydrological model with its application to the Jinghe watershed in the Yellow River Basin

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science China(Technological sciences) 2004年第z1期47卷 60-71页

作者： WANG Zhonggen1, ZHENG Hongxing1, LIU Changming1, , WU Xianfeng2.2.& ZHAO Weimin3.1. Key Laboratory of Water Cycle & Related Land Surface Processes, institute of Geographic {2. and Natural Resources Research, Chinese Academy of {2.s, {3. 100101, China 2. institute of Environmental {2., beijing normal university, beijing 100875, China 3. Water Resources Conservation Committee of Yellow River, Zhengzhou 450003. China Chinese Acad Sci Key Lab Water Cycle & Related Land Surface Proc Inst Geog Sci & Nat Resources Res Beijing 100101 Peoples R China beijing normal Univ Inst Environm Sci Beijing 100875 Peoples R China Water Resources Conservat Comm Yellow River Zhengzhou 450003 Peoples R China

For the purpose of water resources management in the Yellow River Basin with highly spatial difference, a daily distributed hydrological model was proposed, of which the determination of spatially-distributed parameters and model inputs processing were performed by means of GIS/RS. In the model, the computation of runoff yield was based on the topography index method and flow routing was modeled by Maskingum method. The operation of the model is followed by means of “command structure” technique based upon the topography of river network. A case study using the model was conducted for the Jinghe watershed, which locates at the middle Yellow River Basin. The simulation of the hydrological processes in 1996 has shown that water quantity balance errors were less than 5% and the Nash-Sutcliffe coefficient arrived at 0.7, indicating that the model structure is justifiable, and the precision of the model can satisfy the purpose of water resources management.

关键词： distributed hydrological model, structure and equation, GIS and RS, Jinghe Basin, Yellow River Basin.

Exotic structure of the third excited state in^(2.)Na

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Chinese science Bulletin 2005年第23期50卷 2677-2680页

作者： LI Xihan1,2.3. LIANG Yujie1,2.3. DENG Fuguo1,2.3. LIU Zuhua1,4 & ZHOU Hongyu1,2.3.1. Key Laboratory of Beam Technology and Material Modification of Minister of Education, beijing normal university, beijing 100875, China 2. {2. of Low Energy Nuclear Physics, and Department of Material {3. and Engineering, beijing normal university, beijing 100875, China 3. beijing Radiation Center, beijing 100875, China 4. China {2. of Atomic Energy, beijing 102.13. China Key Laboratory of Beam Technology and Material Modification of Minister of Education Beijing Normal University Beijing 100875 China institute of Low Energy Nuclear Physics and Department of Material Science and Engineering Beijing Normal University Beijing 100875 China beijing Radiation Center Beijing 100875 China China institute of Atomic Energy Beijing 102413 China

The probability of the last proton being out of the binding potential, P and the root-mean-square (rms) ra- dius (1/2. of the third excited state in 2.Na are calcu- lated by means of asymptotic normalization coefficie... 详细信息

The probability of the last proton being out of the binding potential, P and the root-mean-square (rms) ra- dius (2.1/2. of the third excited state in 2.Na are calcu- lated by means of asymptotic normalization coefficient (ANC) method with the experimental date existing. The results are P=54.73. and 2.1/2.5.2. fm respectively. The P value and the contribution of the asymptotic part to the 2.1/2.are compared with those of several other low energy states in 2.Na. It is found that the valence particle in the third excited state has an obvious larger P than those of other states. The density distribution of the valence proton in this state is also compared with the nucleons in the nuclear core 2.Ne, and a far extended tail can be seen clearly. These results show that the third ex- cited state in 2.Na is a proton halo state.

关键词：钠第三激发态外部结构有效半径密度分布渐近标准化系数

Calculating soil moisture by remote sensing and analyzing hydrologic cycle process in the Yellow River basin

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science China(Technological sciences) 2004年第z1期47卷 1-13页

作者： YANG Shengtian1 & LIU Changming1, 2.1. School of Environmental sciences, beijing normal university,{2., China 2. {3. of Geographic science and Natural Resources Research, beijing 100101, China beijing normal Univ Sch Environm Sci Beijing 100875 Peoples R China Inst Geog Sci & Nat Resources Beijing 100101 Peoples R China

Based on the AVHRR pathfinder remote sensing data, soil moisture, precipitation and evaporation during the period of 1982.1998, soil moisture of all layers of soil-profile (0—1 m) in the Yellow River basin over the 17 years are calculated by the remote sensing model of calculating soil water. The Yellow River basin is divided into seven subcatchments as control sections at the location of six hydrologic stations (Lanzhou, Toudaoguai, Longmen, Sanmenxia, Huayuankou and Lijin). After calculating soil moisture and obtaining runoff data and precipitation data, the dynamical features of hydrological cycle in the Yellow River basin are analyzed for the period from 1982.to 1988 using water balance method. The conclusions are as follows: It is feasible to calculate the soil water on the macro-scale, in the soil profile with temporal continuity by means of remote sensing and survey in land. Some values of the key water cycle factors in the Yellow River are obtained, which include the annual precipitation of 4000 km3. the evapotranspiration of 3.00-3.00 km3. and the soil moisture transformation of ?500- 500 km3. Consequently, we analyzed the process of the water cycle in the Yellow River over the 17 years, and the results show that the segment upstream of Lanzhou city is a relatively humid region, and the area of internal waters and the reaches of Shanshan is the most desiccated region. Therefore, the runoff in the depth process is intensive and the runoff-generating process is weak in more arid regions.

关键词： the Yellow River, soil moisture, remote sensing, hydrologic cycle.

ENERGY FLOWS IN COMPLEX ECOLOGICAL SYSTEMS:A REVIEW

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Journal of Systems science & Complexity 2009年第3期22卷 345-359页

作者： Jiang ZHANG Department of Systems science,School of Management,beijing {2. {3.,beijing 100875,China. Department of Systems science School of Management Beijing Normal University Beijing 100875 China

Energy flow drives the complex systems to *** allometric scaling as the universalenergy flow pattern has been found in different scales of ecological *** reflects the generalpower law relationship between flow and *** underlying mechanisms of energy flow patterns areexplained as the branching transportation networks which can be regarded as the result of systematicoptimization of a biological target under *** flows in the ecological system may bemodelled by the food web model and population dynamics on the *** paper reviews thelatest progress on the energy flow patterns,explanatory models for the allometric scaling and modellingapproach of flow and network evolution dynamics in ***,the possibility of generalizingthese flow patterns,modelling approaches to other complex systems is discussed.

关键词： Allometric scaling energy flow flows in complex systems food web.

The study on Sanmenxia annual flow forecasting in the Yellow River with mix regression model

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science China(Technological sciences) 2004年第z1期47卷 118-126页

作者： JIANG Xiaohui1, LIU Changming1,2. WANG Yu3.& WANG Hongrui1 1. beijing normal university,{2., China 2. {2. of Geographic {3. and Natural Resources, Chinese Academy of {3.s, beijing 100101, China 3. Reconnaissance, Planning, Design and Research {2., YRCC, Zhengzhou 450003. China beijing normal Univ Beijing 100875 Peoples R China Chinese Acad Sci Inst Geog Sci & Nat Resources Beijing 100101 Peoples R China YRCC Reconnaissance Planning Design & Res Inst Zhengzhou 450003 Peoples R China

This paper established mix regression model for simulating annual flow, in which annual runoff is auto-regression factor, precipitation, air temperature and water consumption are regression factors; we adopted 9 hypothesis climate change schemes to forecast the change of annual flow of Sanmenxia Station. The results show : (1) When temperature is steady, the average annual runoff will increase by 8.3. if precipitation increases by 10%; when precipitation decreases by 10%, the average annual runoff will decrease by 8.2.; when precipitation is steady, the average annual runoff will decrease by 2.4% if temperature increases 1℃; if temperature decreases 1℃, runoff will increase by 1.2.. The mix regression model can well simulate annual runoff. (2. As to 9 different temperature and precipitation scenarios, scenario 9 is the most adverse to the runoff of Sanmenxia Station of Yellow River; i.e. temperature increases 1℃ and precipitation decreases by 10%. Under this condition, the simulated average annual runoff decreases by 10.8%. On the contrary, scenario 1 is the best to the enhancement of runoff; i.e. when temperature decreases 1 ℃ precipitation will increase by 10%, which will make the annual runoff of Sanmenxia increase by 10.6%.

关键词： forecast annual flow, mix regression model, Sanmenxia Station

Node ordinal encoded genetic algorithm for the optimal allocation of water resources

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Progress in Natural science:Materials International 2005年第5期15卷 448-452页

作者： YANG Xiaohua1*, YANG Zhifeng 1,2. SHEN Zhenyao1 and LI Jianqiang3.1. State Key Laboratory of Water Environment Simulation, School of Environment, beijing normal university,{2., China 2. Key Laboratory for Water and Sediment {2.s Ministry of Education, School of Environment, beijing normal university,{2., China 3. Water Resources and Hydropower Planning and Design General institute, MWR, beijing 100011, China) State Key Laboratory of Water Environment Simulation School of Environment Beijing Normal University Beijing 100875 China Key Laboratory for Water and Sediment sciences Ministry of Education School of Environment Beijing Normal University Beijing 100875 China Water Resources and Hydropower Planning and Design General institute MWR Beijing 100011 China

A new method, node ordinal encoded genetic algorithm (NOEGA), is proposed for solving water resources optimal allocation problems, in which the capacity of water resources is split into a number of smaller parts so that successive operations can be overlapped. Our objective is to maximize the whole benefit function. To overcome the “dimensionality and algorithm complexity curse” while searching for solutions and looking for an optimal solution, the operations of one-point crossover operator, gene exchange operator, gene random operator, gene shift operator and node ordinal strings are established. It is proved to be an effective optimal method in searching for global solutions. The NOEGA does not need a diversity of initial population, and it does not have the problem of immature convergence. The results of two cases show that using NOEGA to solve the optimal allocation model is very efficient and robust. In addition, the algorithm complexity of NOEGA is discussed.

关键词： water resources optimal allocation node ordinal code genetic algorithm.