我国宏观经济物价模型与“九五”物价走势分析

通过分析与我国宏观经济物价变动密切相关的主要经济变量以及变量与物价之间的关系 ,建立我国宏观经济物价模型 ,得出“高增长、低通胀”的结论 ,并在此基础上对我国未来的物价水平走势做出大胆预测 ,对指导我国经济稳定、健康。

一类具有时滞的非线性物价模型的稳定性与Hopf分支

结合市场经济实际情况,对一类关于物价的非线性微分方程模型进行了修正,并研究了时滞对该模型动力学行为的影响。利用泛函微分方程稳定性理论和HOPF分支理论得到正平衡点局部稳定的条件,给出了出现HOPF分支存在的充分条件,并通过数值模拟,验证理论分析的结果。

一类物价瑞利模型在小周期扰动下的Hopf分支

研究具有扰动项的时滞物价瑞利模型的周期解分支问题.基于中心流形定理和平均法,讨论了Hopf分支产生周期解的稳定性,证明了在特定参数区域小周期扰动可以导致系统出现5种不同形式的周期解分支:调和解分支、次调和解分支、超调和解分支、超次调和解分支、拟周期解分支.

双物价指数模型的改进

物价变动会计是一个相当普遍的世界性会计难题,针对目前我国市场上存在的物价上涨问题,推行物价变动会计是我国目前亟待解决的问题。文章分析了我国物价变动会计的现状,提出了我国传统会计中减轻物价变动影响的做法,改进了双物价指数模型。

物价水平、物价水平预期与经济增长——来自江苏的实证检验

在保持经济持续快速增长的同时,有效稳定物价水平是政府的一项重要工作。本文以江苏省为样本,实证研究了物价水平、物价水平预期与经济增长之间的关系。基于江苏省物价水平的自相关性,建立了附加预期的"产出—物价"模型,使用江苏省1985-2010年的CPI指数和GDP增长率数据对模型进行检验,检验结果证明了模型的有效性,并据此进行实证测算,基于测算结果提出物价水平与经济增长均衡发展的对策建议。

经济增长与物价波动的关系研究——基于“产出-物价”Phillips曲线的实证分析

在保持经济持续健康快速增长的同时,有效稳定物价水平是政府宏观调控的重要目标。本文基于"产出-物价"Phillips曲线,结合广西1979-2012年CPI指数和GDP增长率数据,对经济增长与物价波动的关系进行了实证研究。通过构建"产出-物价"拟合模型,进一步分析了二者之间的关系,并就政府如何在保证经济快速发展的同时保持物价水平的稳定提出了相关建议。

Application of Matter-element Model in Soil Nutrient Evaluation of Ecological Fragile Region

On the basis of the soil environment investigation in Da＇an City, Jilin Province, China, 40 soil samples from main land use types were obtained and tested by standard method. Soil organic matter （SOM）, total N （TN）, total P （TP）, total K （TK）, available N （AN）, available P （AP） and available K （AK） were chosen as the evaluation factors. A regional soil nutrient evaluation model was developed based on the matter-element model. The results show that the soil samples with nutrient grade Ⅱ-Ⅴ respectively account for 10%, 30%, 32.5% and 27.5%, and those with grade Ⅳ and Ⅴ account for 60% in all samples. The relationship between soil nutrients and land types indicates that the nutrients of farmland are relatively good, with 41.7% of soil samples with the nutrient grade Ⅳ and Ⅴ. The nutrients of saline-alkali land and sandy land are the worst, with 100% of soil samples with the nutrient grade IV and V. And the ratios of soil samples grade IV and V in grassland and wasteland are respectively 62.5 % and 54.55%. Generally speaking, the soil nutrients status in Da＇an City is poor, 60% of soil samples are in poor and extremely poor conditions, indicating that the soil has been severely eroded. Being a relatively superior evaluation method with more accurate resuits and spatial distribution consistency, matter-element analysis is more suitable for regional soil nutrient evaluation than previous models.

Financial Rogue Waves

We analytically give the financial rogue waves in the nonlinear option pricing model due to Ivancevic,which is nonlinear wave alternative of the Black-Scholes model.These rogue wave solutions may be used to describe thepossible physical mechanisms for rogue wave phenomenon in financial markets and related fields.

Effects of coal prices on merchandise prices in China

Coal is the principal form of energy used in China. Hence, coal price variations are expected to have some influence on merchandise prices. Monthly data from January, 2002, to October, 2010, were used to construct a varying-parameter state space model, and an error correction model, to estimate the influence of coat prices on Chinese merchandise prices. The time lag and the dynamic relationship were determined from the data. A long term equilibrium relationship between coal price and the PPI, and the CPI, can be observed. The long term influence of coal price fluctuations on the PPI is 0.263%. The corresponding value for the CPI is 0.157%. The PPI shows an influence from coal price change in the first period of observation： by eight periods the influence is obvious, after which it diminishes. The effect of coal price change on the CPI is rather weak and has no long term memory. Analysis of variance shows a similar situation. The elas- ticity coefficient of coal prices on the CPI, or the PPI, fluctuates over the 2002-2004 period. From 2002 to 2007 the influence elasticity on the CPI declined and subsequently levelled off after 2009.

Evaluation of Surface Air Temperature Change over China and the Globe during the Twentieth Century in IAP AGCM4.0

Based on time series and linear trend analysis, the authors evaluated the performance of the fourth gen- eration atmospheric general circulation model developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences （IAP AGCM4.0）, in simulating surface air temperature （SAT） during the twentieth century over China and the globe. The numerical experiment is con- ducted by driving the model with the observed sea surface temperature and sea ice. It is shown that IAP AGCM4.0 can simulate the warming trend of the global SAT, with the major wanning regions in the high latitudes of the Northern Hemisphere and the mid-latitudes of the South- ern Hemisphere. While the simulated trend over the whole globe is close to the observation, the model trader- estimates the observed trend over the continents. More- over, the model simulates the spatial distribution of SAT in China, with a bias of approximately -2℃ in eastern China, but with a more serious bias in western China. Compared with the global mean, however, the correlation coefficient between the simulation and observation in China is significantly lower, indicating that there is large uncertainty in simulating regional climate change.

Research on Energy Consumption Evaluation Combined with Endogenous Pollutants of China Based on Entropy-Topsis

The traditional evaluation of energy consumption mostly introduces pollutants as a negative economic output into evaluating model,ignoring the configuration relationship among the energy input,pollutants as well as economic output.This paper considers the overall process of energy consumption and constructs an evaluation indication system of energy consumption level combined with endogenous pollutants based on entropytopsis method,then makes empirical research.The results show that China's energy consumption level presents a fluctuant rise in the premise of emission.Energy consumption level depends on the relationship among energy input,pollutants and economic output.The raise of energy consumption level should not increase economic output and reduce pollutant emission at the expense of environment.Finally,the whole paper puts forward the countermeasures to improve the overall level of energy consumption.

Cumulative gain and lift charts for model performance assessment in mineral potential mapping

Model performance assessment is a key procedure for mineral potential mapping, but the correspond-ing research achievements are seldom reported in literature. Cumulative gain and lift charts are well known in the data mining community specialized in marketing and sales applications and widely used in customer chum prediction for model performance assessment. In this paper, they are introduced into the field of mineral poten-tial mapping for model performance assessment. These two charts can be viewed as a graphic representation of the advantage of using a predictive model to choose mineral targets. A cumulative gain curve can represent how much a predictive model is superior to a random guess in mineral target prediction. A lift chart can express how much more likely the mineral targets predicted by a model are deposit-bearing ones than those by a random se-lection. As an illustration, the cumulative gain and lift charts are applied to measure the performance of weights of evidence, logistic regression,restricted Boltzmann machine, and multilayer perceptron in mineral potential mapping in the Altay district in northern Xinjiang in China. The results show that the cumulative gain and lift charts can visually reveal that the first three models perform well while the last one performs poorly. Thus, the cumulative gain and lift charts can serve as a graphic tool for model performance assessment in mineral potential mapping.

Economic Evaluation of Grain Amaranth Production in Kamuli District, Uganda

In Uganda, grain amaranth is relatively new and has generally not been considered as an important crop compared to other grain crops and legumes. This study was therefore conducted to determine factors affecting adoption of grain amaranth growing, factors affecting production, and economic returns on investment of its production. The study was carried out in Kamuli district where a total of 174 grain amaranth farmers and 90 non-grain amaranth farmers were randomly selected and interviewed. Using descriptive statistics, regression analysis （logit model and a Cobb-Douglas type production function） and profitability ratios, it was found that grain amaranth is produced on a small scale and yields are low. Farmer adoption of the crop was favoured by age, gender （female）, education of the farmer, and source of income. The output was positively affected by the amount of labour and manure used in production, while a negative relationship existed between output and male farmers. The crop was most viable under small acreages （0.02-0.04 ha） with positive returns to investment of 0.016. Its production should therefore be encouraged because of its income generation potential and since it requires small land.

Evaluation of Social Environment Impact of Highway Construction Using Gray Matter-Element Information Entropy Model

Due to the importance of the social environment impact of highway construction project, an advanced evaluation is required to incorporate situations such as uncertainty, incompatibility and less information. This paper proposes a gray matter-element evaluation model based on the information entropy. The model is developed by combining both quantitative and qualitative methods, using probability theory to convert quantitative index to qualitative index, and the weight of those indexes were determined through synthesised integral weighting method, integrating matter-element theory, grey theory, and information theory. The model is then applied to evaluate the impact of the social environmental impact of highway construction project which will provide support for decision makers. Cheng-Yu highway and Shen-Da highway were selected for model application, and good results were achieved similar to the real situation.

Comprehensive Suitability Evaluation of Tea Crops Using GIS and a Modified Land Ecological Suitability Evaluation Model

Tea （Camellia sinensis） is one of the most valuable cash crops in southern China; however, the planting distribution of tea crops is not optimal and the production and cultivation regions of tea crops are restricted by law and custom. In order to evaluate the suitability of tea crops in Zhejiang Province, the annual mean temperature, the annual accumulated temperature above 10 ℃, the frequency of extremely low temperature below -13 ℃, the mean humidity from April to October, slope, aspect, altitude, soil type, and soil texture were selected from climate, topography, and soil factors as factors for land ecological evaluation by the Delphi method based on the ecological characteristics of tea crops. These nine factors were quantitatively analyzed using a geographic information system （GIS）. The grey relational analysis （GRA） was combined with the analytic hierarchy process （AHP） to address the uncertainties during the process of evaluating the traditional land ecological suitability, and a modified land ecological suitability evaluation （LESE） model was built. Based on the land-use map of Zhejiang Province, the regions that were completely unsuitable for tea cultivation in the province were eliminated and then the spatial distribution of the ecological suitability of tea crops was generated using the modified LESE model and GIS. The results demonstrated that the highly, moderately, and non-suitable regions for the cultivation of tea crops in Zhejiang Province were 27552.66, 42 724.64, and 26507.97 km2, and accounted for 28.47%, 44.14%, and 27.39% of the total evaluation area, respectively. Validation of the method showed a high degree of coincidence with the current planting distribution of tea crops in Zhejiang Province. The modified LESE model combined with GIS could be useful in quickly and accurately evaluating the land ecological suitability of tea crops, providing a scientific basis for the rational distribution of tea crops and acting as a reference to land policy makers and land use planners.

Risk Assessment of Heavy Metal Pollution in Sediments of the Fenghe River by the Fuzzy Synthetic Evaluation Model and Multivariate Statistical Methods

Concentrations of heavy metals in 74 sediment samples from the Fenghe River, which originates from the north of the Qinling Mountains and flows through Xi'an, Shaanxi Province, China, were characterized by employing geographic information system(GIS)mapping, fuzzy synthetic assessment, and multivariate statistical analysis to determine the enrichment characteristics of heavy metals as well as their potential risks of pollution to sediments. Al, Cd, and Co were the major pollutants, with a high enrichment factor(EF) value. Heavy metal concentrations from samples near the paper plant were maintained at a high level. Significant enrichment of Al, Ba, Cr, Ni, Pb, and Co was found in the midstream and downstream, while high concentration of Cu occurred in the headwater stream. Based on the cluster and principal component analyses, sediment metals mainly came from the paper plants, agronomic practices, natural sources, and tourism, with a contribution of 51.59%, 23.01%, 14.21%, and 9.88%, respectively. Sediment pollution assessment explored using fuzzy theory based on the entropy method and toxicity coefficient showed that 26, 32, and 11 sites fell into Class III(slightly polluted), Class IV(moderately polluted), and Class V(heavily polluted), respectively, and their scores of membership degree in the polluted level were on the rise, suggesting a relatively high degree of sediment metal pollution in the study area. Closely related to the excessive industrial and agricultural applications, metal pollution in sediment is necessary to be addressed in the Fenghe River.

Development of a mathematical model to evaluate the rate of aggregate risk of invasive alien plant species： Fuzzy risk assessment approach

This study presents a novel approach to evaluate the rate of aggregate risk of Invasive Alien Plant Species. Using risk values and grade of importance of weights of risk factors which may reflect invasiveness of plant species are considered. We use Linguistic Ordered Weighted Averaging operator to evaluate the grade of important of weights. Since the risk values and important weights are identified from two different linguistic term sets, fuzzy set theory techniques were used to combine the two sets. The rates obtained from the model were compared with NRA risk levels and the model was validated with data from known and non-invasive species. The model is improved by weighting the risk values of risk factors. The improved model produced significant results and resulted a better tracking system for identifying potential invaders than the conventional risk assessment.