| 1. | Anticipation : increases tiger effect regeneration rate :增加老虎效应量的回复速度。 |
| 2. | Actually , head teacher style ' s effects on eight respects of pupil ' s self - concept do not be equal 对于小学生自我概念的8个维度来讲,班主任的互动风格有不同的效应量。 |
| 3. | Discussed are the basic principle and method of establishing mathematical models of main observation variables of concrete gravity dam 阐述了混凝土重力坝监测效应量数学模型建立的基本原理和方法。 |
| 4. | A case illustrates that this method is simple in practice and successful in determining the component proportion of effect quantity 实例分析表明,该方法简捷实用,可定量分析影响因素对效应量的影响程度。 |
| 5. | The rough set method is studied in this paper in order to evaluate the behaviors of a dam and the comprehensive influence of affecting factors on the effect - quantity 摘要为了评价各因素对大坝监测效应量的综合影响程度,研究了确定大坝监测效应量各分量比例的粗糙集方法。 |
| 6. | With the development of sensor , computer , network , and communication , it ' s possible now to build up an on - line monitoring system to obtain the information such as the loads and deformation reliably 随着传感器技术、计算机网络技术和通讯技术的发展,目前已经可以比较稳定、可靠和实时地获得结构所承受的多种荷载信息和结构效应量。 |
| 7. | Both parameters and observed values are considered as grey in dam safety monitoring models . grey parameters are identified by the means of the grey system theory and then forecasting values are given hi the format of grey interval . 4 将大坝安全监控模型中的参数和实测数据均视为灰色,利用灰色系统方法对灰参数进行了辨识,并对大坝的监测效应量给出了灰色区间预报值。 |
| 8. | For the combined action of inner and external factors , the high nonlinearity of the effective variables appears in dam safety monitoring such as jump - gradualness - jump phenomena , which brings about much trouble in analysis 摘要大坝监测效应量在工作过程中受内部和外部因素的共同作用,经常出现跳跃、渐变、再跳跃等复杂周期变化,表现出高度的非线性,为建立常规的大坝安全监控预测模型带来了不少麻烦。 |
| 9. | ( 3 ) based on the study of several kinds of neural network , several phase space models of dam observation time series using neural network are established . the validity of the models is proved by an example . a neural network method for determining the component percentage is given ( 3 )在总结分析时间序列预测中的几种有代表性的神经网络的基础上,将混沌理论和神经网络相结合,提出了几种基于神经网络的大坝观测时间序列相空间预测和监控模型,经工程实例验证,预测和监控效果较好;同时,提出了确定分量占效应量比例的神经网络方法。 |
| 10. | Firstly , the original monitoring data are discretized to a decision making table , then the attributions are reduced from the decision making table so as to eliminate the factors having no or less effect on the effect - quantity , and , lastly , the proportion of affecting factors on the effect - quantity is calculated with rough membership 首先对原始监测信息进行数据离散化得到决策表,然后对决策表进行属性约简以去除影响极小的影响因素,最后用粗糙隶属度分析各主要因素的重要性指标及其在效应量中所占的分量比例。 |