用灰色系统理论对新疆主要河流水质进行预测和分析

在对新疆河流水质现状进行分析评价的基础上,用GM(1,1)模型对今后五年内的河流水质进行了预测。     

A REVIEW OF APPLICATION ISSUES OF THE METROPOLITAN WATER DISTRICT-MAIN WATER FORECASTING SYSTEM1

ABSTRACT: This paper reviews the processes that occurred during an application of the Metropolitan Water District (MWD)-MAIN water use forecasting system for the City of Salinas, California. The review includes an analysis of sources of available data, methods for estimating input data, calibration, and verification of the MWD-MAIN System, and an evaluation of the reliability of system output. We found that inexperienced users can have difficulty understanding the level of skill, knowledge, and amount of data that are required to produce reliable forecasts. Some of the issues associated with application of the MWD-MAIN System include the following:

• ? All input data needed for accurate forecasts simply are not available for many cities and towns.
• ? The data requirements are more extensive than many users anticipate.
• ? Substantial requirements for manipulation of input data produces opportunity for error that creates major time demands in troubleshooting.
• ? Calibration and verification for specific uses can be substantially more difficult than is readily apparent from the guidance manual.
• ? Independent validity checks need to be done to validate system output.
• ? If specified calibrating procedures do not produce reasonable results, reestimating slope coefficients is an option, but this requires resources and expertise that can easily exceed the limits of most users.

These are problems typical of most complex models. Reviews such as this can help users to appreciate the level of data required, and to use the MWD-MAIN System in a more effective and efficient manner.     

高邮地磁台加卸载响应比与江苏及邻近地区的地震预测

研究分析了高邮地磁台1980～2001年观测资料的加卸载响应比异常与江苏及邻近地区ML5.0以上地震之间的关系,提出了适用于高邮地磁台的地震分析预报参数,并对其内检预报效能进行了评价。     

灾变预测在火灾预测中的应用

简述了灰色理论中灾变预测的特点及其建模过程，并将其应用于湖南省和山东省火灾预测之中。经检验，模型的精度等级为好，模型的预测结果可靠，对于消防部门火灾的预测有一定帮助。     

Uncertainty Reduction of the Flood Stage Forecasting Using Neural Networks Model1

Abstract: The Elman Discrete Recurrent Neural Networks Model (EDRNNM), which is one of the special types of neural networks model, is developed and applied for the flood stage forecasting at the Musung station (No. 1) of the Wi‐stream catchment, which is one of the International Hydrological Program representative basins, Korea. A total of 135 different training patterns, which involve hidden nodes, standardization process, data length, and lead‐time, are selected for the minimization of the architectural uncertainty. The model parameters, such as optimal connection weights and biases, are estimated during the training performance of the EDRNNM, and we apply them to evaluate the validation performance of the EDRNNM. Sensitivity analysis is used to reduce the uncertainty of input data information of the EDRNNM. As the results of sensitivity analysis, the Improved EDRNNM consists of four input nodes resulting from the exclusion of Dongkok station (No.5) in initial five input nodes group of the EDRNNM. The accuracy of flood stage forecasting during the training and validation performances of the Improved EDRNNM remains the same as that of the EDRNNM. The Improved EDRNNM, therefore, gives highly reliable flood stage forecasting. The best optimal EDRNNM, so called the Improved EDRNNM, is determined by elimination of the uncertainties of architectural and input data information in this study. Consequently, we can avoid unnecessary data collection and operate the flood stage forecasting system economically.     

福建省台湾入境游客市场预测模型分析

随着海峡两岸旅游区的发展,对台湾旅游市场进行预测可以更好地帮助福建省制定对台旅游发展战略和市场开发模式。通过对目前较为实用的两种预测模式——回归分析和灰色预测进行分析比较得出指数模型在游客预测中的优越性,从而得出相应的预测模型。对未来几年游客量进行预测,从定量分析的角度对福建省开展对台旅游提出依据。     

枣庄市水体污染现状及治理对策研究

对枣庄市水体环境污染现状进行了简要分析，对7条主要河流水质现状进行比较，运用指数平滑预测模型、灰色预测模型以及组合预测模型等三种预测分析方法对2010年枣庄市水环境污染状况进行了预测，在借鉴国外水污染治理成功经验的基础上，根据枣庄市水污染现状和成因，按照系统性、可持续发展、统一规划、分期实施的原则，研究了枣庄市水环境污染综合治理对策，提出从观念技术创新（发展循环经济等）、体制机制改革（进行水资源管理体制改革等）、公共财政投入（工程设施、资金保障等）等方面进行枣庄市的城市水环境污染的治理工作。     

中国火灾最佳灰色回归组合预测模型

火灾现象具有随机性、模糊性,是个复杂的灰色系统行为。研究火灾发生的规律及发展趋势,具有实用价值。笔者给出最小二乘估计意义下的最佳组合预测模型的定义,并求得其权的公式和证明权的惟一性;用回归分析方法建立多个回归模型,并按3条标准即①回归指数大、②系统误差小、③模型精度高,选定最佳非线性回归模型;用灰色理论建立多个灰色模型,并按3条标准即①后验差比值小、②小误差概率大、③预测关联度大,选定最佳灰色模型;再将最佳回归模型与最佳灰色模型有机地结合起来建立中国火灾最佳灰色回归组合预测模型。组合预测模型综合利用前两者提供的不同的有用信息,改善了单一模型的局限性,提高了预测精度,减少了预测误差。组合模型预测中国年火灾起数处于动态增长过程。     

MULTITEMPORAL SCALE HYDROGRAPH PREDICTION USING ARTIFICIAL NEURAL NETWORKS1

Abstract: An artificial neural network (ANN) provides a mathematically flexible structure to identify complex nonlinear relationship between inputs and outputs. A multilayer perceptron ANN technique with an error back propagation algorithm was applied to a multitime-scale prediction of the stage of a hydro-logically closed lake, Devils Lake (DL), and discharge of the Red River of the North at Grand Forks station (RR-GF) in North Dakota. The modeling exercise used 1 year (2002), 5 years (1998–2002), and 27 years (1975–2002) of data for the daily, weekly, and monthly predictions, respectively. The hydrometeorological data (precipitations P_(t), P_(t-1), P_(t-2), P_(t-3), antecedent runoff/lake stage R_(t-1) and air temperature T_(t) were partitioned for training and for testing to predict the current hydro-graph at the selected DL and RR-GF stations. Performance of ANN was evaluated using three combinations of daily datasets (Input I = P_(t)), P_(t-l), P_(t-2), P_(t-3), T_(t) and R_(t-l); Input II = Input-l less P_(t) P_(t-l), P_(t-2), P_(t-3); and Input III = Input-II less T_(t)). Comparison of the model output using Input I data with the observed values showed average testing prediction efficiency (E) of 86 percent for DL basin and 46 percent for RR-GF basin, and higher efficiency for the daily than monthly simulations.     

我国城市O3污染的数值预报试验研究

为在我国开展城市O₃污染预报,新近发展了一个O₃污染数值预报模式系统.它由物理、生态过程模式(包括污染源模型,下垫面参数化模型,中尺度-α气象模式,中尺度-β气象模式,湍流统计量参数化模式和干湿沉积模式)和高分辨O₃化学模式(HROM)组成.用该系统对重庆、广州和济南市的O₃污染作了24 h实际预报试验,结果表明:预报与实测O₃质量浓度之间有相当好的一致性,API指数平均预报准确率超过85%;城市O₃质量浓度表现出明显的日变化、空间分布的非均匀性和地区差异;NO₂是O₃的一个重要前体污染物,它们之间呈好的负相关.