节拍系列构建论

由于现有节拍符号体系不能充分反映音乐作品中复杂多样的节拍形态以满足音乐创作及记谱的需要，还需从各民族的音乐实践中，把诸如中国戏曲、曲艺音乐中的“紧打慢唱”、“整打散说”，蒙古族民族中的“长歌”等节拍形态，纳入到现有的音乐节拍体系网络之中，并创造出相应的完备的符号体系。

Discussion of skill improvement in marine ecosystem dynamic models based on parameter optimization and skill assessment

Marine ecosystem dynamic models(MEDMs) are important tools for the simulation and prediction of marine ecosystems. This article summarizes the methods and strategies used for the improvement and assessment of MEDM skill, and it attempts to establish a technical framework to inspire further ideas concerning MEDM skill improvement. The skill of MEDMs can be improved by parameter optimization(PO), which is an important step in model calibration. An effi cient approach to solve the problem of PO constrained by MEDMs is the global treatment of both sensitivity analysis and PO. Model validation is an essential step following PO, which validates the effi ciency of model calibration by analyzing and estimating the goodness-of-fi t of the optimized model. Additionally, by focusing on the degree of impact of various factors on model skill, model uncertainty analysis can supply model users with a quantitative assessment of model confi dence. Research on MEDMs is ongoing; however, improvement in model skill still lacks global treatments and its assessment is not integrated. Thus, the predictive performance of MEDMs is not strong and model uncertainties lack quantitative descriptions, limiting their application. Therefore, a large number of case studies concerning model skill should be performed to promote the development of a scientifi c and normative technical framework for the improvement of MEDM skill.

QUANTITATIVE ANALYSIS AND FRACTAL MODELING ON THE MOSAIC STRUCTURE OF LANDSCAPE IN THE CENTRAL AREA OF SHANGHAI METROPOLIS

The mosaic structure of landscape of the central area of Shanghai Metropolis is studied by quantitative methods of landscape ecology based on Remote Sensing (RS) and Geographic Information System (GIS) in this paper. Firstly, landscapes are classified into eight categories: residential quarter, industrial quarter, road, other urban landscape, farmland, village and small town, on-building area, river and other water bodies (such as lake, etc.). Secondly, a GIS is designed and set up based on the remote sensing data and field investigation, and a digital map of landscape mosaic is made. Then the indexes of diversity, dominance, fragmentation and isolation, and fractal dimension of each type of landscape in different periods are calculated by using spatial analysis method of GIS. With reference to the calculated results, a series of relative issues are discussed.

Analysis on optimal working fluid flowrate and unstable power generation for miniaturized ORC systems

For efficient utilization of a limited geothermal resource in practical projects,the cycle parameters were comprehensively analyzed by combining with the heat transfer performance of the plate heat exchanger,with a variation of flowrate of R245 fa.The influence of working fluid flowrate on a 500 W ORC system was investigated.Adjusting the working fluid flowrate to an optimal value results in the most efficient heat transfer and hence the optimal heat transfer parameters of the plate heat exchanger can be determined.Therefore,for the ORC systems,optimal working fluid flowrate should be controlled.Using different temperature hot water as the heat source,it is found that the optimal flowrate increases by 6-10 L/h with 5 ℃ increment of hot water inlet temperature.During experiment,lower degree of superheat of the working fluid at the outlet the plate heat exchanger may lead to unstable power generation.It is considered that the plate heat exchanger has a compact construction which makes its bulk so small that liquid mixture causes the unstable power generation.To avoid this phenomenon,the flow area of plate heat exchanger should be larger than the designed one.Alternatively,installing a small shell and tube heat exchanger between the outlet of plate heat exchanger and the inlet of expander can be another solution.

Strong/weak limits and strong/weak differentials of multi-variable indeterminate forms. III: Transformations

Various transforms of the indeterminate forms are presented in this part, which include simplification in spherical coordinates, origin translation, axis alteration, transformation of limit conservation and application of Xh?K0. Fundamental factors for numerical simplification are provided respectively for bi-variable indeterminate forms, tri-variable indeterminate forms and the universal extending multiplier.

An Uncertain Programming Model for Land Use Structure Optimization to Promote Effectiveness of Land Use Planning

Land use structure optimization(LUSO) is an important issue for land use planning. In order for land use planning to have reasonable flexibility, uncertain optimization should be applied for LUSO. In this paper, the researcher first expounded the uncertainties of LUSO. Based on this, an interval programming model was developed, of which interval variables were to hold land use uncertainties. To solve the model, a heuristics based on Genetic Algorithm was designed according to Pareto Optimum principle with a confidence interval under given significance level to represent LUSO result. Proposed method was applied to a real case of Yangzhou, an eastern city in China. The following conclusions were reached. 1) Different forms of uncertainties ranged from certainty to indeterminacy lay in the five steps of LUSO, indicating necessary need of comprehensive approach to quantify them. 2) With regards to trade-offs of conflicted objectives and preferences to uncertainties, our proposed model displayed good ability of making planning decision process transparent, therefore providing an effective tool for flexible land use planning compiling. 3) Under uncertain conditions, land use planning effectiveness can be primarily enhanced by flexible management with reserved space to percept and hold uncertainties in advance.

Parametric sensitivity analysis of precipitation and temperature based on multi-uncertainty quantification methods in the Weather Research and Forecasting model

Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.

The need for alternative plant species interaction models

Aims The limitations of classical Lotka–Volterra models for analyzing and interpreting competitive interactions among plant species have become increasingly clear in recent years.Three of the problems that have been identified are(i)the absence of frequency-dependence,which is important for long-term coexistence of species,(ii)the need to take unmeasured(often unmeasurable)variables influencing individual performance into account(e.g.spatial variation in soil nutrients or pathogens)and(iii)the need to separate measurement error from biological variation.Methods We modified the classical Lotka–Volterra competition models to address these limitations.We fitted eight alternative models to pin-point cover data on Festuca ovina and Agrostis capillaris over 3 years in an herbaceous plant community in Denmark.A Bayesian modeling framework was used to ascertain whether the model amendments improve the performance of the models and increase their ability to predict community dynamics and to test hypotheses.Important Findings Inclusion of frequency-dependence and measurement error,but not unmeasured variables,improved model performance greatly.Our results emphasize the importance of comparing alternative models in quantitative studies of plant community dynamics.Only by considering possible alternative models can we identify the forces driving community assembly and change,and improve our ability to predict the behavior of plant communities.

Response-surface-based structural reliability analysis with random and interval mixed uncertainties

Traditional reliability analysis requires probability distributions of all the uncertain parameters.However,in many practical applications,the variation bounds can be only determined for the parameters with limited information.A complex hybrid reliability problem then will be caused when the random and interval variables coexist in a same structure.In this paper,by introducing the response surface technique,we develop a new hybrid reliability method to efficiently compute the interval of the failure probability of the structure due to the probability-interval hybrid uncertainty.The present method consists of a sequence of iterations.At each step,a response surface model is constructed for the limit-state function by using a quadratic polynomial and a modified axial experimental design method.An approximate hybrid reliability problem is created based on the response surface model,which is subsequently solved by an efficient decoupling approach.An updating strategy is suggested to improve the quality of the response surface and whereby ensure the reliability analysis precision.A computational procedure is then summarized for the whole iterations.Four numerical examples and also a practical application are provided to demonstrate the effectiveness of the present method.

Empirical Study of Mean-entropy Model with the Transaction Costs in Portfolio Selection

Entropy can be as a measurement of the uncertainty and mean-entropy optimization model can help investors to make decisions in the imperfect securities market. In this paper, the transaction costs will be added to the mean-entropy model, which makes the model more rational and objective. The empirical study is done in twenty stocks of Shanghai Stock Exchange A Share to verify the model＇s feasibility and effectiveness.