| 1. | Predication of wastewater treatment plant effluent quality using radial basis function neural network
径向基函数人工神经网络预测污水处理厂出水水质 |
| 2. | Microorganisms living in the water of wastewater treatment plants are responsible for the effluent quality
污水处理厂的处理效果主要取决于水中的微生物。 |
| 3. | Protozoa could be used to improve the effluent quality , evaluate and assess the operating and function of the wastewater treatment plant
原生动物能用来改善水质、评价和指示污水厂的运行和处理效果。 |
| 4. | The goal of this research is to develop a suit of software system for realizing the forecast of effluent quality based on soft - sensing technique
研究目标是设计基于软测量技术的计算机软件系统，实现污水处理出水水质的预测预报。 |
| 5. | These enforcement activities typically involved the epd issuing discharge licences and checking effluent quality against the limits specified by the licences
环保署的执法行动主要是通过发放排污牌照和检查污水排放是否符合牌照所订的标准。 |
| 6. | The thesis developed on an existing problem for forecasting the effluent quality parameters of urban sewage treatment factories , which are usually difficult to measure with conventional online apparatus , through applying soft - sensing technique
本论文是围绕如何采用软测量技术解决目前城市污水处理出水水质参数难以用硬仪表在线测量这一现实问题而展开的。 |
| 7. | Two main research results of the thesis are as follows . ( 1 ) the obtainment of soft - sensing models for effluent quality parameters forecasting . firstly , a sewage database is designed with history data of a sewage treatment factory for years
二、成功开发了基于软测量技术的污水处理出水水质预测预报软件系统本系统的前端应用软件采用visualc + + 6 . 0开发；软预测器由matlab实现；数据由microsoftsqlserver2000或access管理。 |
| 8. | With the increasing municipal wastewater loads , people pay more attentions to the municipal wastewater treatment , so it is the requirement that we develop more efficient procedures for wastewater treatment plants to meet the stricter requirements on effluent quality and economics
随着城市生活污水的不断增加，人们也越来越重视对城市生活污水的处理，这就要求我们采用更有效污水处理控制方案来满足日益严格的出水水质及经济效益的要求。 |
| 9. | Research methods applied in the thesis are as follows . the first method is to construct the soft - sensing models of effluent quality parameters with history data of a sewage treatment factory for years . another method is to plant the models into the application system to develop the computer forecasting system for effluent quality parameters of sewage treatment factories
本论文的研究方法是：首先，借助于污水处理过程历史数据，建立出水水质参数的软测量模型；然后将该模型嵌入应用系统中，开发出基于软测量技术的污水处理过程出水水质参数的计算机预测预报系统。 |
| 10. | Based on 28 months pilot test data , some treatment units ’ ( including pre - treatment , enhanced coagulation , enhanced flotation , enhanced filtration , advanced treatment and sequeutial chlorinatio disinfection ) efficiency is evaluated to seek optimal running parameters . the results show that pre - treatment technology could reduce coagulation dosing rate , enhance the traditional treatment ( coagulation + daf + filtration ) effluent quality , accelerate destab . ilization of organic matter , increase water quality guarantee ratio of traditional treatment
在为期28个月的中试试验研究中,通过对预处理技术、强化混凝技术、强化气浮技术、强化过滤技术、深度处理技术、安全消毒技术等单元工艺技术的处理效能进行了系统评价,确定了各单元工艺的最佳运行参数。 |
