土地定级估价的分析研究与实践——以新疆拜城县为例

近几年来,经济发展迅速,土地级别划分及地价水平已有较大的变化,原有的基准地价体系已不能适应现时经济发展的要求,地价体系也亟需修正更新。该文结合拜城县的具体情况,并遵循所选因子与土地的相关性,确定拜城县城区土地定级因素,在分析各定级因素权重的基础上,计算各因素的分值,划分土地等级。通过对拜城县城区的土地进行定级估价作出修正和更新,将对土地的监督管理工作起到良好的促进作用。     

征地区片综合价政策制定工作探讨——以鄞州区为例

一、征地区片综合价概念、特点和作用 征地区片综合地价又称征地区片价,是指在县（市）级行政区土地利用总体规划确定的建设用地范围内,在农用地定级的基础上,按照农用地质量状况、土地区位、人均耕地水平、农村社会经济发展水平等划分征地区片,并在标准耕作制度和现实农田基本设施状况条件下,根据区片农用地条件和社会保障水平等评估确定的某一估价基准日的农用地平均征收价格。     

不同权重条件下降雨对边坡稳定性影响的二级模糊综合评判

边坡稳定性影响因素众多,其中一部分具有明显的不确定性,用经典数学理论及力学模型很难描述。采用二级模糊综合评判法,对影响边坡稳定的离散型和连续型因素采用不同方法确定隶属度,并利用二元对比分析法给出各因素权重值;同时考虑降雨对边坡稳定的重要影响,对降雨后各影响因素的权重进行修正,建立边坡稳定的二级模糊综合评判计算模型,评价降雨前后边坡稳定性的变化。研究结果表明：模型所采用的隶属函数,充分考虑了各个因素的不同特点和分布规律;考虑降雨前后权重的变化,能使评判结果更趋合理。以实际工程为例,模糊综合评判结果显示：降雨前边坡处于基本稳定状态,降雨后处于欠稳定状态,与经典极限平衡法计算结果一致。     

农用地质量的综合评价

分析了影响农用地质量的主要因素，利用模糊综合评价的方法对农用地质量进行综合评价，较好地反映农用地质量的差异，为农用地价格评估提供依据。     

水库边坡稳定性评价的改进云模型

水库边坡的稳定性受诸多因素的影响,以致其准确评价仍存在一定的困难。为克服传统的正态云模型方法在实际应用中存在的云模型特征值取值不统一以及使用期望隶属度而非实际隶属度两个问题,提出了改进型正态云模型,并在MATLAB软件平台上开发了便于模型应用的程序。选取影响水库边坡稳定性的12个主要因素作为评价指标,应用程序生成各评价指标在各稳定性等级的综合隶属度云模型,接着使用改进的熵权层次分析法确定各评价指标的相应权重,最后将平均综合隶属度最高值所在的级别确定为边坡的稳定性等级。将该方法应用于34个水电边坡工程稳定性评价实例,并将结果与现行国家规范推荐的CSMR法及这些边坡的实际状态进行了比对。结果表明该方法的准确度比CSMR法高,具有较好的可靠性和实用性,也可供公路、铁路或建筑等其他岩质边坡在进行稳定性评价时参考。     

澜沧江某水电站泄洪洞出口边坡稳定性评价

岩土质边坡是一种自然地质体，其稳定性在很大程度上具有不确定性、模糊性。模糊分析是边坡稳定性分析的有效途径之一。文章采用模糊数学分析法，构建了二次模糊综合评判模型，对影响边坡稳定性的诸多因素进行了分类归纳，并根据不同的稳定状态，将边坡划分为5个等级，再结合某水电站右岸泄洪洞出口开挖边坡稳定性的实际问题，利用梯形函数构建了与该边坡稳定性分析相关因素的隶属函数、运用专家评分法确定了各因素的权重，最终对该边坡的稳定性进行了评价。结果表明该评价分析结果与实际相吻合，评价效果较好。     

模糊综合评判在拉萨地温开发地质环境评价中的应用

影响拉萨市浅层地温能地质环境质量的因素主要有地质环境背景、第四系及含水层因素、水量环境因素、水质环境因素等四大类,对四大类影响因素及其下一级因子进行层次分析和模糊数学模型的构建,确定其隶属度函数,计算各因子的权重值。利用GIS的属性赋值与空间分析,对地质环境质量评价区进行网格划分,计算出各网格单元的模糊质量指数值,绘制了模糊质量指数等值线,在此基础上对拉萨市浅层地温能地质环境质量进行了评价。     

模糊数学在水质评价分级中的应用

本文用模糊数学的方法，把水质的污染程度看作是水质污染这一论域Ｕ的模糊子集Ａ，构造出一个多元隶属函数，提出一种模糊模型，然后对各种污染参数进行水质污染程度评价。     

基于突变理论的底板突水危险性模糊综合评判研究

根据底板突水影响因素的多样性、模糊性以及隔水层破坏的突发特点,引入突变理论,建立了底板突水危险性评判层次结构模型;基于专家评分法和梯形模糊分布解决了初始模糊隶属函数构造和取值问题,使取值更合理、可行;根据归一化公式量化递归运算和互补原则,计算总突变隶属函数值并确定底板突水危险性等级,从而对底板突水危险性做出评判;研究表明,将本方法应用于工程实践是可行的、合理的。     

基于投影寻踪的水质评价模型

基于投影寻踪技术的基本原理和求解过程，建立了水质评价模型。大样本数据应用到模型中，使模型的精度大大提高。该模型既能根据样本本身寻求出各因子的重要程度，即客观权重．又能根据决策者对某个（些）影响因子的偏好，对样本进行分类。将遗传算法和传统优化方法相结合，以解决遗传算法求解带约束问题能力差的问题，并将其用于本文建立的模型的目标函数优化中．解决了高维数据全局寻优的难题。实例分析表明，该模型能够很好地对水质进行评价。能有效地解决多因素带来的高维复杂性，是一种处理多因素复杂评价问题的有效途径。     

Causal models as multiple working hypotheses about environmental processes

The environmental modeller faces a dilemma. Science often demands that more and more process representations are incorporated into models (particularly to avoid the possibility of making missing process errors in predicting future response). Testing the causal representations in environmental models (as multiple working hypotheses about the functioning of environmental systems) then depends on specifying boundary conditions and model parameters adequately. This will always be difficult in applications to a real system because of the heterogeneities, non-stationarities, complexities and epistemic uncertainties inherent in environmental prediction. Thus, it can be difficult to define the information content of a data set used in model evaluation and any consequent measures of belief or verisimilitude. A limit of acceptability approach to model evaluation is suggested as a way of testing models, implying that thought is required to define critical experiments that will allow models as hypotheses to be adequately differentiated.     

Artificial Neural Networks: A Solution to the Ambiguity in Prediction of Engineering Properties of Fine-Grained Soils

Determination of soaked california bearing ratio (CBR) and compaction characteristics of soils in the laboratory require considerable time and effort. To make a preliminary assessment of the suitability of soils required for a project, prediction models for these engineering properties on the basis of laboratory tests—which are quick to perform, less time consuming and cheap—such as the tests for index properties of soils, are preferable. Nevertheless researchers hold divergent views regarding the most influential parameters to be taken into account for prediction of soaked CBR and compaction characteristics of fine-grained soils. This could be due to the complex behaviour of soils—which, by their very nature, exhibit extreme variability. However this disagreement is a matter of concern as it affects the dependability of prediction models. This study therefore analyses the ability of artificial neural networks and multiple regression to handle different influential parameters simultaneously so as to make accurate predictions on soaked CBR and compaction characteristics of fine-grained soils. The results of simple regression analyses included in this study indicate that optimum moisture content (OMC) and maximum dry density (MDD) of fine-grained soils bear better correlation with soaked CBR of fine-grained soils than plastic limit and liquid limit. Simple regression analyses also indicate that plastic limit has stronger correlation with compaction characteristics of fine-grained soils than liquid limit. On the basis of these correlations obtained using simple regression analyses, neural network prediction models and multiple regression prediction models—with varying number of input parameters are developed. The results reveal that neural network models have more ability to utilize relatively less influential parameters than multiple regression models. The study establishes that in the case of neural network models, the relatively less powerful parameters—liquid limit and plastic limit can also be used effectively along with MDD and OMC for better prediction of soaked CBR of fine-grained soils. Also with the inclusion of less significant parameter—liquid limit along with plastic limit the predictions on compaction characteristics of fine-grained soils using neural network analysis improves considerably. Thus in the case of neural network analysis, the use of relatively less influential input parameters along with stronger parameters is definitely beneficial, unlike conventional statistical methods—for which, the consequence of this approach is unpredictable—giving sometimes not so favourable results. Very weak input parameters alone need to be avoided for neural network analysis. Consequently, when there is ambiguity regarding the most influential input parameters, neural network analysis is quite useful as all such influential parameters can be taken to consideration simultaneously, which will only improve the performance of neural network models. As soils by their very nature, exhibit extreme complexity, it is necessary to include maximum number of influential parameters—as can be determined easily using simple laboratory tests—in the prediction models for soil properties, so as to improve the reliability of these models—for which, use of neural networks is more desirable.     

农用地转用生态补偿价格评估实证研究

农用地价值是农用地功能与效益的综合体现,但由于对农用地价值缺乏完整认识,导致我国农用地大量被低价转为建设用地。以吉林省四平市为例,从完全资源价格角度出发,探讨了农用地生态价值构成,并利用资源环境经济学的影子价格法、市场替代法、碳税法对其生态价值进行评估。     

水资源价值模型评价研究

水资源价值是指水资源使用者为了获得水资源使用权需要支付给水资源所有者的货币额,它与水价是不同的概念,合理的水价应包括水资源价值。目前可以用来求算水资源价值的模型不同程度地存在各种问题,必须加以完善和发展。影子价格模型只反映水资源的稀缺程度和水资源与总体经济效益之间的关系,其结果不能代替水资源价值;边际机会成本模型存在着应用困难较大、替代选择多样性、结论缺乏可比性、忽略了水质等问题;供求价格模型仅仅通过水资源量决定水资源价值是不科学的;模糊数学模型是潜力较大的最新模型,其缺点是影响水资源的各项因素的模糊评价较复杂,权重的确定是多样的。     

基于田间试验的土壤水分运动模型选择

基于不同形式Richards方程可建立不同适用范围和计算精度的数值模型,针对具体情况下如何选择合适模型的问题,以武汉大学农田水利试验场田间入渗试验为例,选用6种模型(Picard-h模型、Picard-θ模型、Picard-mix模型、Ross模型、动力波模型和水均衡模型),运用贝叶斯模型平均(BMA)方法进行了模型选择的计算;针对BMA方法无法考虑模型计算效率的缺点,进一步提出了可同时考虑模型计算精度与计算效率的改进BMA方法。计算结果表明,在本田间尺度问题中,Ross模型排序最高,说明其兼具高精度与高效率,改进BMA方法可增加高计算效率模型被选中的概率,使模型选择更加全面合理。     

Land use change modelling: current practice and research priorities

Land use change models are tools to support the analysis of the causes and consequences of land use dynamics. Scenario analysis with land use models can support land use planning and policy. Numerous land use models are available, developed from different disciplinary backgrounds. This paper reviews current models to identify priority issues for future land use change modelling research. This discussion is based on six concepts important to land use modelling: (1) Level of analysis; (2) Cross-scale dynamics; (3) Driving forces; (4) Spatial interaction and neighbourhood effects; (5) Temporal dynamics; and (6) Level of integration. For each of these concepts an overview is given of the variety of methods used to implement these concepts in operational models. It is concluded that a lot of progress has been made in building land use change models. However, in order to incorporate more aspects important to land use modelling it is needed to develop a new generation of land use models that better address the multi-scale characteristics of the land use system, implement new techniques to quantify neighbourhood effects, explicitly deal with temporal dynamics and achieve a higher level of integration between disciplinary approaches and between models studying urban and rural land use changes. If these requirements are fulfilled models will better support the analysis of land use dynamics and land use policy formulation.     

A novel approach to estimate the variations in stresses and fault state due to depletion of reservoirs

Geomechanical changes may occur in reservoirs due to production from reservoirs. Study of these changes has an important role in upcoming operations. Frictional equilibrium is one of the items that should be determined during the depletion as it may vary with respect to time. Pre-existing faults and fractures will slide in regions where there is no frictional equilibrium. Hence, it may be concluded that reduction in pore pressure can initiate the sliding of faults. Whereas, it is also possible that faults will not exist after a certain time as production recovers the equilibrium. Casing shearing or lost circulation may be occurred due to faulting. In reservoirs which depletion leads to frictional equilibrium, decrease of fractures and faults leads to some variations in permeability. Hence, predicting the effect of depletion on frictional equilibrium is required in dealing with casing shearing or lost circulation in drilling of new wells. In addition, permeability modeling will be more precise during the life of reservoirs. Estimation of necessary time to create or vanish faults is vital to be successful in production from wells or drilling new wells. Achieving or loosing of equilibrium mainly depends on in situ stresses and rate of production. Estimation of the in situ stresses at the initiation state of reservoir is the key to study the state of faults. The next step is to predict the effects of depletion on in situ stresses. Different models are suggested in which decrease of horizontal stresses is predicted as function of pore pressure variation. In these models, different assumptions are made such as simplifying the poroelastic theory, ignoring the passing time, and considering the geometry of reservoir. In this article, a new model is proposed based on theory of inclusions and boundary element method. This state-of-the-art model considers the geometry of reservoir. In addition, changes of in situ are obtained as a function of time to reach to a more precise model capable of applying during the reservoir life. Finally, the model is imposed on real cases. The effect of depletion on faults is studied in reservoirs of normal and strike-slip stress regimes, and conventional and proposed models are compared. For this aim, in the first step, mechanical earth models of these two reservoirs are built using logging and coring data. Stress polygon method and poroelastic horizontal strain model are used for strike-slip and normal regimes, respectively. In reservoir 1 which is in a strike-slip stress regime, a fault is distinguished in formation microimaging (FMI) log. For this reservoir, the required time to achieve to frictional equilibrium is calculated. In the reservoir 2, the potential depth of fault sliding is analyzed and required time for faulting in that depth is predicted. The predicted time for satisfaction of frictional equilibrium using the proposed model has a significant difference with the predicted time using the previous methods. In addition, the proposed model predicts that different parts of reservoir 2 are willing for faulting during depletion. The previous model determines only one point that faulting may happen. It is necessary to use this new model to consider different important factors such as geometry and time to gain more accurate predictions.     

The geochemical environment

Much of the assessment of high-level radioactive waste repositories will be accomplished through the application of geochemical models. Such models will be used to understand geochemical processes in the repository and the surrounding environment. The purpose of this paper is to review the nature of the currently available geochemical models. The kinds of calculations that a number of these models perform include aqueous speciation, mineral solubility, and mass transfer reactions. Presently, there are limitations on the success of calculation of adsorption reactions and rate-limited reactions. Ongoing development of geochemical models requires that more work be done to compile thermodynamic and kinetic data, incorporate additional geochemical processes and parameters into existing codes, and assess the accuracy of all simulations through validation studies and sensitivity analyses.     

基于广义位势理论的弹塑性模型的修正方法

广义位势理论为岩土材料的本构关系研究指出了更开阔的数学背景。基于广义位势理论可以构造出基于应力空间的模型,也可构造出基于应变空间的模型,利用两者之间的对称关系,把常规基于应力空间的模型直接转换到应变空间中,对本构模型自身无需做任何改动。基于广义位势理论也可以对已有的本构模型进行修正,比如,可基于广义位势理论对剑桥模型进行修正,这种修正可使模型利用三轴试验的部分成果,比单纯使用压缩试验的成果要好一些。另外,也初步探讨了模型的三维化问题。