煤体注水湿润半径预测的神经网络模型

合理的注水半径一直是煤体注水防尘技术中难以确定的参数。笔者基于对影响煤体注水半径因素的分析和神经网络理论的原理之上 ,设计网络模型为 3层 ,输入层为 7个节点 ,应用BP网络算法 ,建立了煤体注水湿润半径的预测模型 ,并对其参数进行了讨论。然后 ,用平顶山矿务局和水城矿务局 13个矿 19个回采工作面的统计资料对BP网络进行自适应学习 ,并取η =0 .9,α =0 .82 ,控制网络总误差E≤ 10 6。经过 2 12 34次迭代后 ,网络趋于稳定。用训练好的网络对平顶山矿务局的某矿的 3层煤的注水湿润半径进行预测 ,预测结果与实测值很接近。其误差分别为 0 .5 %,0 .6 %和 0 .7%。     

京沪高速铁路地震预警系统的方案及关键参数研究

京沪高速铁路及沿线区域跨越 4个主要的地震带 ,带内地震活动活跃 ,地震是对高速列车行车安全危害最大的自然灾害。在对京沪高速铁路及沿线区域地震危险性调查的基础上 ,对地震预警系统的构成、监测设备的设置方案及报警模式等一些关键问题进行了研究。通过对京沪高速铁路各类典型构筑物的大量的地震响应统计分析 ,给出了机械式地震仪的预警水平 ,并提出了适于P波检测的M -R判别标准 ,为京沪高速铁路安全监控系统中地震预警系统的建设提供理论依据。     

降低企业库存风险问题研究

大多数企业都面临着库存风险问题 ,库存过多 ,造成积压 ,不仅占用大量资金和场地 ,加重企业的利息负担 ,而且长期存放会使物品陈旧过时 ,失去原有的价值和使用价值。如何降低库存风险 ,使库存经常处于合理水平 ,是每个企业都十分关心的问题。笔者分析了库存管理中存在的问题 ,提出需求预测和安全库存的确定 ,是降低库存风险的两个重要前提 ,同时讨论了安全库存的计算方法 ,以及降低库存风险的主要措施     

提高交通安全——实现智能汽车的研究

主要介绍了通过智能汽车的研究 ,提高城市交通安全的必要性 ;综述了发达国家关于智能汽车研究的现状与趋势 ,并通过国外智能汽车发展的趋势 ;进一步论证智能汽车的研究是汽车工业发展的方向 ,也是提高交通安全的重要手段之一。此外 ,论文提出利用模式识别技术的智能汽车的结构框架 ;指出神经网络方法应用与模式识别技术结合的优势。最后 ,论文在阐述我国需要发展智能汽车的同时 ,提出应结合中国国情相应研究相关理论 ,为今后的实施奠定基础的近期目标 ,并提出展望     

A comparative study of risk perception in small and large communities where chemical industries are present

Opinion polls were conducted to assess the level of risk perceived by the citizens in communities of different sizes where chemical industries were present. The aim of the study was to relate the risk perceived to variables such as the nature of risks, the specific information received regarding the industrial activity and the economic impact of this activity in the community.     

SOIL SALINITY PREDICTION USING ARTIFICIAL NEURAL NETWORKS1

ABSTRACT: This study explores the applicability of Artificial Neural Networks (ANNs) for predicting salt build‐up in the crop root zone. ANN models were developed with salinity data from field lysimeters subirrigated with brackish water. Different ANN architectures were explored by varying the number of processing elements (PEs) (from 1 to 30) for replicate data from a 0.4 m water table, 0.8 m water table, and both 0.4 and 0.8 m water table lysimeters. Different ANN models were developed by using individual replicate treatment values as well as the mean value for each treatment. For replicate data, the models with twenty, seven, and six PEs were found to be the best for the water tables at 0.4 m, 0.8 m and both water tables combined, respectively. The correlation coefficients between observed salinity and ANN predicted salinity of the test data with these models were 0.89, 0.91, and 0.89, respectively. The performance of the ANNs developed using mean salinity values of the replicates was found to be similar to those with replicate data. Not only was there agreement between observed and ANN predicted salinity values, the results clearly indicated the potential use of ANN models for predicting salt build‐up in soil profile at a specific site.     

Interaction effect of sewage and duration of consumption on the production response of pullets

A study was carried out to evaluate the interaction effect of sewage and duration of consumption on the production traits of pullets. Intake of the test waters was a function of their degree of acceptability when intake was voluntary at periods of low ambient temperatures. The intiation of egg production in all groups began after five weeks of treatment and differences in egg weight of the groups was slight and not significant (P > 0.05). The effect of the sewage waters on growth was pronounced only when the birds were in lay and the alum-treated sewage promoted higher body weight gain. The feed conversion ratio and the feed intake were not affected significantly (P > 0.05) by the interaction, and both had the same trend. The eggshell thickness was sensitive to changes in ambient temperature.     

DETERMINATION OF BEST TIMING FOR POULTRY WASTE DISPOSAL: A MODELING APPROACH1

ABSTRACT: Confined production of poultry results in significant volumes of waste material which are typically disposed of by land application. Concerns over the potential environmental impacts of poultry waste disposal have resulted in ongoing efforts to develop management practices which maintain high quality of water downstream of disposal areas. The timing of application to minimize waste constituent losses is a management practice with the potential to ensure high quality of streams, rivers, and lakes downstream of receiving areas. This paper describes the development and application of a method to identify which time of year is best, from the standpoint of surface water quality, for land application of poultry waste. The procedure consists of using a mathematical simulation model to estimate average nitrogen and phosphorus losses resulting from different application timings, and then identifying the timings which minimize losses of these nutrients. The procedure was applied to three locations in Arkansas, and three different criteria for optimality of application timing were investigated. One criterion was oriented strictly to water quality, one was oriented only to crop production, and the last was a combination. The criteria resulted in different windows of time being identified as optimal. Optimal windows also varied with location of the receiving area. The results indicate that it is possible to land-apply poultry waste at times which both minimize nutrient losses and maximize crop yield.     

IMPROVED RIVER BASIN UTILIZATION THROUGH SYSTEMS ANALYSIS1

ABSTRACT. Theoretical and practical results are summarized for a study to determine optimal water resource allocation in a proposed water conservancy district. The area of this district, which covers several river basins, contains a large number of existing and proposed facilities such as reservoirs and diversions. The operation of all of these facilities was to be determined along with the sizing of the proposed facilities in order to optimize given objective functions. Related efforts in optimal river basin utilization were surveyed, and linear programming was selected as an expedient optimization technique. The problem is formulated by identifying time stages which together constitute a repetitive cycle such as a year. With these stages, it is possible to associate operational and capacity variables with network components, which are branches and nodes. Objective functions are assembled for the component variables. Constraint equations are written in terms of the variables to reflect network nodal continuity, capacity restrictions, and adjudications such as water rights. A numerical example is considered in which the existing and proposed facilities are aggregated to produce a small, tractable number of facilities. This paper examines the example results and suggests future improvements for models of this type.