In view of the fact that the traditional model such as statistical model,deterministic model and mixed model in the dam safety forecast is insufficient,the paper combined the genetic algorithm(GA)with BP algorithm which based on error back propagation,the dam slope deformation prediction model of genetic optimization of neural networks(GA-BP model) is established.GA-BP model uses neural network misalignment mapping ability,network inference and forecast function,and the genetic algorithm global optimization characteristic to overcome BP algorithm is prone to local minimum.Using the model to forecast some dam's actual observation data,the forecasting result indicated that the GA-BP forecast model has the high precision,the quick convergence rate merit,and it is valuable to dam forecast aspect.

The side slope distortion has the complexity,randomness,the uncertainty,the localization time-limitedly,and so on characteristic,it is a difficult problem to carry on the precise forecast to the side slope.Aiming at this question,this article established the prediction model based on the wavelet analysis neural network to the side slope distortion to conduct the research,finally it indicated that the wavelet neural network forecast model had the more nimble effective approximation of function ability,the forecast precision is high,and has confirmed the wavelet neural network forecast model high accuracy through the example.

The technology of deformation monitoring in open-pit mines has been a crucial job on the mine safety production.In recent years,it is an important direction on studies of the microwave remote sensing to monitor the slope deformation by using synthetic aperture radar interferometry(INSAR) measurement technology.This paper analyzes the technical advantages and the research progress on INSAR technology to monitor the slope deformation;compare the measured data of monitoring Haizhou open-pit mine by traditional technology with the monitoring data of INSAR measure.The result shows the INSAR technology can achieve an effective monitoring on the slope of the large-scale open-pit,which has certain technical advantages and broad prospects.

Aiming at the increasingly serious pollution and ecological damage in mining cites, environmental information urgently are urgently needed to provide basis and decision-making for the economic transition of mining cites. This article describes main environmental problems existing in mining cites, as well as ways of monitoring these major environmental problems, such as the Landsat TM images are used in Land use dynamic monitoring, High Spectrum Images are used in the extracted vegetation monitoring, and the water quality change is monitored by the way of NOAA / AVHRR. Particularly, the effectual way of the Interferometric Synthetic Aperture Radar (InSAR) landslides monitoring is introduced, which is well applied to the opencast mine of Haizhou and Fushun in China with this technology. Differential interferometry using Synthetic Aperture Radar (SAR) is a powerful technology for detecting surface deformation of ground. Surface deformation can be analyzed from different phase of micro-wave between two observed data by SAR. The accuracy of measurement is less than plus-and-minus 1 cm. Achieved research results will provide early warning of environment disasters, rapid & real-time information and interpretation means for the mining cites.

如何利用先进的超市信息导航系统提高大型超市的自动化服务质量是当今大型家电超市面临的一个重大课题。本文利用VB和MO开发出一个小型的家电超市信息导航系统，使顾客可以轻松自如浏览所有商品的最新动态，该系统的灵活性、快捷性、详细性为顾客购物时提供了很大方便，同时为超市带来了经济效益。

在测量数据处理中,最小二乘原理一直是被广泛采用的平差处理方法，然而当模型病态时,虽然用最小二乘解算的结果是无偏的,但方差较大。若观测数据含有误差,参数估值与真值就相差很大,而且估值表现出不稳定性。本文采用遗传算法对带有误差的观测值进行处理，得到了比较好的结果，也说明了该方法的可行性。

针对超市选址的重要性和复杂性，讨论了影响超市选址的主要因子及其内容的确定和量化的方法，针对现有选址方法的不足，提出以地理信息系统（GIS）可视化为分析平台，将神经网络分析方法引入到超市选址中，具有一定的可行性和有效性。

地理信息系统（GIS）作为一种应用工具已经在多个领域得到越来越广泛的应用。本文主要结合近几年来GIS在矿山开采沉陷中的应用情况，并从技术方面阐述GIS在矿山开采沉陷中的应用现状，并最终对GIS在矿山开采沉陷中的应用前景作下展望。

本文分析了校园信息的特点，探讨了基于GIS的校园信息系统的系统组成、结构和特点，结合高校校园管理信息系统应用实际，阐明GIS应用于校园信息综合管理的必要性和可行性，并重点对各功能模块进行了研究。