基于ArcGis的土地勘测定界图的研究与制作

基于ArcGis、国土二调数据库等软件,快速准确地获取勘测定界图的权属和地类面积等信息。再利用CASS软件进行处理,最后生成勘测定界图以及界址点坐标表和勘测定界报告。现详细论述了勘测定界过程中的关键技术,为土地勘测定界提供了一套切实可行的方法。     

浅析土地勘测质量影响因素及措施

土地勘测的数据准确性对于勘测成果的质量有着重要的影响,如果数据出现较大的误差,那么经济建设的过程中,就会出现较大的损失。对土地勘测质量影响因素以及措施进行分析。     

不动产分割登记的难点研究

《物权法》第十一条规定，当事人申请登记，应当根据不同登记事项提供权属证明和不动产界址、面积等必要材料。《房屋登记办法》（下称《办法》）中也明确了产权登记中房屋基本单元的概念，但目前不动产分割的界址不清往往成为房屋产权无法登记的关键问题。笔者总结目前遇到的不动产分割带来的房界址不清问题的处理经验，以供参考。     

无锡市城镇土地调查确权定界方法研究

无锡市1∶500城镇土地调查过程中,在街道、街坊划分和界址调查中依据具体问题,采用不同的划分原则,认真进行现场调查确权,依据有关确定土地权属的规定,在确定界址的实地位置时,具体问题具体分析,积极更新基础图件,建立了完善的市区城镇土地调查数据库.     

实测数据与历史数据误差原因及处理

不动产权籍调查是不动产登记的基础，是条例实施、簿册统一和信息平台建设的重要支撑。不动产权籍调查包括不动产权属调查和不动产测量。不动产权属调查主要为了查清不动产单元的权属状况、界址、用途、四至等内容，确保不动产单元权属清晰、界址清楚、空间相对位置关系明确。不动产测量应依据不动产的类型、位置和不动产单元的构成方式，因地制宜，审慎科学地选择符合本地区实际的不动产测量方法，确保不动产单元的界址清楚、面积准确。     

工程勘测中常见的问题探讨

工程勘测是规划和施工的重要保障,是工程顺利完成和质量保证的基础,对于工程勘测中常见问题的处理效率和处理质量是关乎工程勘测进度和勘测精准的重要基础,就现代工程勘测中常见的一些问题进行归纳和总结。     

浅谈提高土地勘测质量的措施

本文首先分析了土地勘测过程中存在的问题及产生这些问题的原因,针对土地勘测过程中产生问题的原因提出了提高土地勘测质量的措施。     

对勘测设计企业财务会计工作中存在的问题及对策探讨

勘测设计企业在实际的经营管理中,需要不断加强对财务会计工作的分析和解读,通过财务会计工作能够有效地提高勘测设计企业的市场竞争力和经济效益。以下本文就勘测设计企业财务会计工作中存在的问题展开探讨,结合勘测设计企业的实际情况,提出合理的对策,旨在为相关财务会计人员提供参考,提高企业的财务会计水平,实现勘测设计企业的持续健康发展。     

煤田勘测技术的研究与发展

煤质工作是煤田地质勘探工作中十分重要的环节,是煤田地质勘探中一项技术性很强的综合性工作,同时也是煤田地质报告编写的重要组成部分。本文概述了是在煤田普勘测的内容,分析了制约煤田勘测的制约因素,说明了煤田勘测的具体目标,以及勘测结果的编写程序,并提出了我国煤田勘测的发展方向。对煤田地质勘探工作提出了新的更高的要求。     

GPS-RTK技术在土地勘测定界中的应用

在现在对土地勘测的不断研究的过程中发现了一种能够对土地进行很好勘测的技术手段,这种技术手段就是现在社会上常见的GPS-RTK技术手段。这种技术手段与其他土地勘测技术手段相比,运用了相应的RTK技术就使得对土地勘测有很大的便利,进一步使得这种技术手段在对土地勘测的过程中得到广泛的应用。     

Tourism forecasting: accuracy of alternative econometric models

This study evaluates the forecasting accuracy of six alternative econometric models in the context of the demand for international tourism in Denmark. These econometric models are special cases of a general autoregressive distributed lag specification. In addition, the forecasting accuracy of two univariate time series models is evaluated for benchmark comparison purposes. The forecasting competition is based on annual data on inbound tourism to Denmark. Individual models are estimated for each of the six major origin countries over the period 1969–93 and forecasting performance is assessed using data for the period 1994–97. Rankings of these forecasting models over different time horizons are established based on mean absolute percentage error and root mean square percentage error.     

A survey technique for estimating the proportion and sensitivity in a dichotomous finite population

In this paper, a simple survey technique to measure the sensitivity of survey issues is presented. It can be applied to estimate the population proportion as well as the probability that a respondent truthfully states that he or she bears a sensitive character when experienced in a direct response survey. An unbiased estimator of mean square error for direct response survey is obtainable so as to be able to judge the effect on the accuracy in estimation. It is also found that the proposed technique is more efficient than some traditional techniques. A simple extension for polychotomous situations can be developed as well.     

A stochastic differential equation approach to the analysis of the 2017 and 2019 UK general election polls

Human dynamics and sociophysics build on statistical models that can shed light on and add to our understanding of social phenomena. We propose a generative model based on a stochastic differential equation that enables us to model the opinion polls leading up to the 2017 and 2019 UK general elections and to make predictions relating to the actual results of the elections. After a brief analysis of the time series of the poll results, we provide empirical evidence that the gamma distribution, which is often used in financial modelling, fits the marginal distribution of this time series. We demonstrate that the proposed poll-based forecasting model may improve upon predictions based solely on polls. The method uses the Euler–Maruyama method to simulate the time series, measuring the prediction error with the mean absolute error and the root mean square error, and as such could be used as part of a toolkit for forecasting elections.     

Alternative procedures for converting qualitative response data to quantitative expectations: An application to Australian manufacturing

This paper analyses and extends alternative procedures for converting qualitative expectations responses to quantitative expectations. A number of conversion procedures is investigated, including the probability model, the time-varying parameter probability model, and the regression approach. The informational content of the survey expectations is compared with simple time series models. It is found that the expectations models are superior for many series, both in terms of producing lower forecast root mean square error (RMSE) values and in detecting turning points in the actual data. Survey expectations are also tested for rational expectations in aggregate using the orthogonality test.     

On efficiency of the ratio estimator

Summary The exact mean square error for the ratio estimator of a finite population total based on simple random sampling without replacement is shown to have an expected value less than that of the variance of the ratio estimator based on Midzuno’s scheme, under a usual super-population model.     

Using forecast evaluation to improve the accuracy of the Greenbook forecast

Recently, Patton and Timmermann (2012) proposed a more powerful kind of forecast efficiency regression at multiple horizons, and showed that it provides evidence against the efficiency of the Fed’s Greenbook forecasts. I use their forecast efficiency evaluation to propose a method for adjusting the Greenbook forecasts. Using this method in a real-time out-of-sample forecasting exercise, I find that it provides modest improvements in the accuracies of the forecasts for the GDP deflator and CPI, but not for other variables. The improvements are statistically significant in some cases, with magnitudes of up to 18% in root mean square prediction error.     

Acknowledgement

This paper examines the conditions under which it is possible to make comparisons between restricted least squares estimators under a generalized mean square error criterion. Our results demonstrate the rather extreme limitations on such comparisons — in many cases it is not possible to compare two restricted least squares estimators using the generalized mean square error criterion.     

Small sample properties of the mixed regression estimator

In this paper, the small sample properties of the mixed regression estimator are examined when prior information may be biased and when the ration of the variance of the prior restriction errors to the variance of the sample errors is unknown. The mean square error of the mixed regression estimator is derived, and it is shown that the mixed regression estimator gets dominated by the ordinary least squares estimator in terms of the mean square error as the bias of prior information gets larger.     

Efficiency of iterative estimators in the regression model with AR(1) disturbances

The mean square error approximation method of Nagar is applied to the iterated Prais-Winsten and (iterated) maximum likelihood estimators of regression coefficients in the model with AR(1) disturbances. Their mean square errors are found to equal that of the two-stage Prais-Winsten estimator at the second-order level of approximation.     

The locally MIMSQE of nonnormal error variance in quadratically balanced models

Without normality assumption, an explicit form of the locally minimum mean square error translation-invariant quadratic estimator for the error variance in a quadratically balanced design is obtained. The estimator depends on the kurtosis of the random error. Under the normality the estimator becomes globally optimal.