初二期末英语测试

听力部分Ⅰ 听句子选出句中所含单词（５分）（）１．ＡｃａｔｃｈＢｗｉｆｅＣａｄｄｒｅｓｓＤｐｌａｙ（）２．ＡｙｏｕｒｓｅｌｆＢｙｏｕＣｙｏｕｒｓｅｌｖｅｓＤｙｏｕｒａｐｐｌｅｓ（）３．ＡｃｌａｓｓｍａｔｅＢｃｌａｓｓｍａｔｅｓＣｃｌａｓｓｅｓＤｇｌａｓｓｅｓ（）４．Ａｎｏｂｏｄｙ Ｂｓｏｍｅｂｏｄｙ Ｃａｎｙｂｏｄｙ Ｄｅｖｅｒｙｂｏｄｙ（）５．ＡｓｕｍｍｅｒＢｗｅａｔｈｅｒＣｗｉｎｔｅｒＤｐｌｅａｓｕｒｅⅡ 根据所听句子选出一个意思与其相同或相近的答案（１０分）（）１．ＡＪｉｍ＇ｓｆａｔｈｅｒｉ…     

初二英语期末测试题

Ⅰ 单词辨音 ,从下列每组单词中找出划线部分与其他几个不同的那一个（１０分）（）１ Ａ．ｂｕｒｔＢ．ｔｅｒｍＣ．ｆｉｒｓｔＤ．ｗａｌｋ（）２ Ａ．ｍｅａｌＢ．ｐｏｌｉｃｅＣ．ｈｉｔＤ．ｆｒｅｅ（）３ Ａ．ｇｌａｓｓＢ．ｐａｓｓＣ．ｃｌａｓｓＤ．ｈａｔ（）４ Ａ．ｃａｒｅＢ．ｈｅａｒｄＣ．ｃｈａｉｒＤ．ｐｅａｒ（）５ Ａ．ｔｏｕｃｈＢ．ｙｏｕｎｇ Ｃ．ｈｏｕｓｅＤ．ｃｏｕｎｔｒｙ（）６ Ａ．ｐａｓｓｅｄＢ．ｍｅｎｄｅｄＣ．ｗａｎｔｅｄＤ．ｌａｓｔｅｄ（）７ Ａ．ｆｏｏｄＢ．ｌｏｏｋＣ．ｇｏｏｄＤ．ｂｏｏｋ（…     

初一英语水平测试

Ｉ．语音：找出下列每组单词中划线部分发音与众不同的选项（５分）（）１，Ａ．ｃａｋｅ　Ｂ．ｂａｂｙ　Ｃ　ｃｌａｓｓ　Ｄ．ｓａｍｅ（）２．Ａ．ｖｅｒｙ Ｂ．ｈｅｌｐ Ｃ．ｓｅｖｅｎ Ｄ．ｂａｓｋｅｔ（）３，Ａ．ｗｏｒｒｙ　Ｂ．ｏｖｅｒ　Ｃ．ｃｏｍｅ　Ｄ．ｍｏｔｈｅｒ（）４．Ａ．ｔｈｉｎｇ Ｂ．ｗｉｔｈ Ｃ．ｒｉｖｅｒ Ｄ．ｆｉｎｅ（）５．Ａ．ｆｕｌｌ　Ｂ．ｊｕｍｐ Ｃ．ｂｕｓ Ｄ．ｎｕｍｂｅｒ（）６． Ａ． ｂｏｏｋ Ｂ、ｒｏｏｍ Ｃ． ｂｒｏｏｍ　Ｄ．ｓｃｈｏｏｌ （）７． Ａ． ｐｌｅａｓｅ Ｂ．ｓｗｅａｔｅｒ …     

A method to eliminate effect of phase noise in OFDM synchronization system

１　Ｉｎｔｒｏｄｕｃｔｉｏｎ　ＴｈｅＯＦＤＭｔｅｃｈｎｏｌｏｇｙｉｓｗｉｄｅｌｙｕｓｅｄｉｎｔｈｅｍｏｄｅｒｎｈｉｇｈｓｐｅｅｄｄａｔａｃｏｍｍｕｎｉｃａｔｉｏｎａｐｐｌｉｃａｔｉｏｎｓ,ｓｕｃｈａｓｔｈｅｄｉｇｉｔａｌｂｒｏａｄｃａｓｔｉｎｇｓｙｓｔｅｍｉｎｃｌｕｄｉｎｇＤＶＢ（ｔｈｅｄｉｇｉｔａｌｖｉｄｅｏｂｒｏａｄｃａｓｔｉｎｇ）ａｎｄＤＡＢ（ｔｈｅｄｉｇｉｔａｌａｕｄｉｏｂｒｏａｄｃａｓｔｉｎｇ）,ｔｈｅｂｒｏａｄｂａｎｄａｃｃｅｓｓｎｅｔｗｏｒｋｉｎｃｌｕｄｉｎｇＡＤＳＬ（ｔｈｅａｓ…     

初三英语水平测试

Ａ卷 １．在所给单词中找出划线部分读音不同的词（５分） （）１．Ａ．ｐｌａｃｅ Ｂ．ｓａｆｅ Ｃ．ｗａｋｅ Ｄ．ｈａｖｅ （）２．Ａ．ｓｈｅ Ｂ．ｔｈｅｓｅ Ｃ．ｌｅｔｔｅｒ Ｄ．ｍｅｔｒｅ （）３． Ａ． ｗｉｄｅ Ｂ， ｎｉｃｅ Ｃ． ｌｉｖｅ Ｄ． ｗｈｉｔｅ （）４．Ａ．ｄｏｇ Ｂ，ｔｈｏｓｅ Ｃ．ｓｈｏｐ Ｄ．ｆｏｒｇｏｔ （）５．Ａ．ｅｘｃｕｓｅ Ｂ．ｎｕｍｂｅｒ Ｃ．ｓｔｕｄｅｎｔ Ｄ．Ｔｕｅｓｄａｙ （）６．Ａ．ｆａｒｍ Ｂ．ｈａｒｄ Ｃ．ｗａｒｍ Ｄ．ｃａｒｄ （）７．Ａ．ｗｈｏｓｅ Ｂ．ｗｈｏｌｅ Ｃ．ｗｈ…     

A Random Multi-Access Method for Data Services in CDMA Cellular System

ＡＲａｎｄｏｍＭｕｌｔｉＡｃｃｅｓｓＭｅｔｈｏｄｆｏｒＤａｔａＳｅｒｖｉｃｅｓｉｎＣＤＭＡＣｅｌｕｌａｒＳｙｓｔｅｍＬｉＺｈｅｎ（李振）ＹｏｕＸｉａｏｈｕ（尤肖虎）（ＮａｔｉｏｎａｌＭｏｂｉｌｅＣｏｍｍｕｎｉｃａｔｉｏｎｓＲｅｓｅａｒｃｈＬａｂｏｒ...     

初二英语水平测试

１．语音（５分）从Ａ、Ｂ、Ｃ、Ｄ中找出读音不同于其他三个的选项：（）１．Ａ．ｕｓｕａｌｌｙ Ｂ．ｍｕｃｈ Ｃ．ｕｓｅ Ｄ．ｄｕｔｙ（）２．Ａ．ｔｈａｎ Ｂ．ｎｏｔｈｉｎｇ　Ｃ．ｆｉｆｔｈ Ｄ．ｔｈｒｏｗ（）３．Ａ．ｓｉｎｇｉｎｇ Ｂ．ｌｏｎｇ Ｃ．ｂｒｉｎｇ Ｄ．Ｅｎｇｌｉｓｈ（）４．Ａ．ｒｏａｄ Ｂ．ｃｏａｔ Ｃ．ａｂｏｕｔ Ｄ．ｂｏａｔ（）５．Ａ．ｐｅａｒ Ｂ．ｄｅａｒ Ｃ．ｗｈｅｒｅ Ｄ．ｗｅａｒ（）６．Ａ．ｍａｃｈｉｎｅ Ｂ．ｆｉｓｈ Ｃ．ｕｓｕａｌｌｙ Ｄ．ｓｕｒｅ（）７．Ａ．ｓｃｏｒｅ　Ｂ．ｓｐｏｒ…     

初一英语期末试题

（时间９０分钟 ,满分１００分）Ⅰ 语音Ａ 找出下列每组划线部分读音不同的单词（）１ Ａ．ｒｉｇｈｔＢ．ｄｒｉｖｅｒＣ．ｄｒｉｎｋＤ．ｈｉｇｈ（）２．Ａ．Ｔｕｅｓｄａｙ Ｂ．ｓｕｐｐｅｒＣ．ｓｔｕｄｅｎｔＤ．ｅｘｃｕｓｅ（）３．Ａ．ｗａｔｃｈＢ．ｗａｎｔＣ．ｗａｔｅｒＤ．ｏｒａｎｇｅ（）４．Ａ．ｃｌｏｓｅＢ．ｓｏｍｅｔｈｉｎｇ Ｃ．ｍｉｓｓＤ．ｈｏｕｓｅ（）５．Ａ．ｗｈｏＢ．ｗｈａｔＣ．ｗｈｉｃｈＤ．ｗｈｅｒｅＢ 请写出以下每组单词中有几种读音（）１．Ａ．ｈｏｕｓｅＢ．ｙｏｕｎｇＣ．ｗｏｕｌｄＤ．ｔｒ…     

Transient analysis of steam generator in PWR nuclear power plant

ＮｏｍｅｎｃｌａｔｕｒｅＡＡｒｅａ（ｍ２）ＤｈＨｙｄｒａｕｌｉｃＤｉａｍｅｔｅｒ（ｍ）ＥＥｎｅｒｇｙＣｏｎｔｅｎｔ（Ｊ）ｆＰｒｅｓｓｕｒｅＬｏｓｓＣｏｅｆｉｃｉｅｎｔαＶｏｉｄＦｒａｃｔｉｏｎＨＳｐｅｃｉｆｉｃＥｎｔｈａｌｐｙ（Ｊ／ｋｇ）ＩＩｎｅｒｔ...     

成人高考英语模拟试题(三)

一、语音知识（共８小题 ;每题１．５分 ,共１２分）在下列每组单词中 ,有一个单词的划线部分与其他单词的划线部分的读音不同。找出这个单词。１．（）Ａ．ｍｅａｓｕｒｅＢ．ｐｌｅａｓｕｒｅＣ．ｕｓｕａｌｌｙ Ｄ．ｓｕｇａｒ２．（）Ａ．ｑｕａｒｒｅｌＢ．ｄａｎｇｅｒｏｕｓＣ．ｃｏｎｇｒａｔｕｌａｔｉｏｎＤ．ｏｐｅｒａｔｅ３．（）Ａ．ｓａｔｅｌｌｉｔｅＢ．ｓｅｃｒｅｔａｒｙＣ．ｓｅｖｅｒａｌＤ．ｓｅｎｔｅｎｃｅ４．（）Ａ．ｓｔｏｍａｃｈＢ．ｏｔｈｅｒｗｉｓｅＣ．ｗｏｎｄｅｒＤ．ｃｏｎｔｉｎｅｎｔ５．（）Ａ．ｆ…     

THE GA-ANN METHOD FOR DETERMINING CALCULATION PARAMETERS FOR DEEP EXCAVATION

ＩＮＴＲＯＤＵＣＴＩＯＮＩｎｅｘｃａｖａｔｉｏｎ ,ｎｏｒｍａｌａｎａｌｙｓｉｓｉｓｎｏｔｇｏｏｄｅｎｏｕｇｈｔｏｍｅｅｔｅｎｇｉｎｅｅｒｉｎｇｎｅｅｄｓｄｕｅｔｏｔｈｅｕｎ ｃｅｒｔａｉｎｔｙｏｆｆｏｒｃｅｓａｐｐｌｉｅｄｏｎｂｒａｃｅｓｔｒｕｃｔｕｒｅｓ,ｓｏｉｌｃｈａｒａｃｔｅｒｉｓｔｉｃｓ,ａｎｄｓｏｉｌｍｏｄｅｌｕｓｅｄ .Ｔｏｇｕａｒａｎｔｅｅｔｈａｔｔｈｅｃｏｎｓｔｒｕｃｔｉｏｎｐｒｏｃｅｓｓｃａｎｂｅｓｍｏｏｔｈｌｙｐｅｒｆｏｒｍｅｄ ,ｍｅａｓｕｒｅｍｅｎｔｓｉｎｓｉｔｕａｒｅｕｓｕａ…     

基于神经网络的模拟电路故障诊断研究

对BP型ANN网络用于模拟电路故障诊断的特点进行了介绍,探讨了利用遗传算法确定BP型ANN网络参数的方法,并给出了遗传算法与BP型ANN相结合实现模拟电路故障诊断的应用.实践表明,该方法的诊断精度、诊断速度以及建立诊断模型的自动化程度都有了较大的提高．     

Parameter optimization model in electrical discharge machining process

Electrical discharge machining （EDM） process, at present is still an experience process, wherein selected parameters are often far from the optimum, and at the same time selecting optimization parameters is costly and time consuming. In this paper, artificial neural network （ANN） and genetic algorithm （GA） are used together to establish the parameter optimization model. An ANN model which adapts Levenberg-Marquardt algorithm has been set up to represent the relationship between material removal rate （MRR） and input parameters, and GA is used to optimize parameters, so that optimization results are obtained. The model is shown to be effective, and MRR is improved using optimized machining parameters.     

Parameters optimization and nonlinearity analysis of grating eddy current displacement sensor using neural network and genetic algorithm

A grating eddy current displacement sensor （GECDS） can be used in a watertight electronic transducer to realize long range displacement or position measurement with high accuracy in difficult industry conditions. The parameters optimization of the sensor is essential for economic and efficient production. This paper proposes a method to combine an artificial neural network （ANN） and a genetic algorithm （GA） for the sensor parameters optimization. A neural network model is developed to map the complex relationship between design parameters and the nonlinearity error of the GECDS, and then a GA is used in the optimization process to determine the design parameter values, resulting in a desired minimal nonlinearity error of about 0.11%. The calculated nonlinearity error is 0.25%. These results show that the proposed method performs well for the parameters optimization of the GECDS.     

The GA-ANN method for determining calculation parameters for deep excavation

This paper presents a new method (GA-ANN) developed by combining genetic algorithm (GA) and artificial neural networks (ANN) for determining parameters of soils and retaining walls of deep excavation. This method has the advantages of nonlinear projection of neural networks, networks reasoning, prediction and good overall characteristics. it was first used for back analysis of the problem of mechanics parameters for excavation. Case studies showed that the GA-ANN method is effective and practical for back analysis of determining parameters. Project supported by NSFC(5973860) and National Civil Defence fund of China     

Multi-objective process parameter optimization for energy saving in injection molding process

This paper deals with a multi-objective parameter optimization framework for energy saving in injection molding process. It combines an experimental design by Taguchi’s method, a process analysis by analysis of variance (ANOVA), a process modeling algorithm by artificial neural network (ANN), and a multi-objective parameter optimization algorithm by genetic algorithm (GA)-based lexicographic method. Local and global Pareto analyses show the trade-off between product quality and energy consumption. The implementation of the proposed framework can reduce the energy consumption significantly in laboratory scale tests, and at the same time, the product quality can meet the pre-determined requirements.     

Regression-Based Artificial Neural Network Methodology In Response Surface Methodology

Response surface methodology (RSM) is an important tool for process parameter optimization, robust design and other quality improvement efforts. When the relationship between influential input variables and output response is very complex, it‘ s hard to find the real response surface using RSM. In recent years artificial neural network (ANN) has been used in RSM. But the classical ANN does not work well under the constraints of real applications. An algorithm of regression-based ANN(R-ANN) is proposed in this paper, which is a supplement to the classical ANN methodology. It makes network closer to the response surface, so that training time is reduced and robustness is strengthened. The procedure of improving ANN by regressions is described and the comparisons among R-ANN, RSM and classical ANN are computed graphically in three examples. Our research shows that the R-ANN methodology is a good supplement to the RSM and classical ANN methodology, which can yield lower standard error of prediction under conditions that the scope of experiment is rigidly restricted.     

人工神经网络模型在水文地质学中的应用

介绍了人工神经网络的生理基础以及算法的基本结构,对其在水文地质学中进行反求参数的应用进行了阐述,并就应用的具体步骤及所建立的网络模型进行讨论。     

人工神经网络模型在水文地质学中的应用

介绍了人工神经网络的生理基础以及算法的基本结构,对其在水文地质学中进行反求参数的应用进行了阐述,并就应用的具体步骤及所建立的网络模型进行讨论。     

心电图检测与辨识的人工神经网络方法

应用人工神经网络（Artificial Neural Network，ANN）算法对MIT-BIH心电数据库中的数据进行检测，对波形辨识算法做初步研究。设计三层神经网络结构：输入层、隐含层和输出层。从心电信号中提取4项特征参数作为输入层的输入量，并对MIT-BIH心电数据库中的15例心电数据进行了检测。表明该算法对QRS波总体检测灵敏度为98．96％，检测真阳性率为99．93％，对室性异位博动检测灵敏度为94．97％，检测真阳性率为98．72％。实验证实该神经几乎络算法对心电波形辨识非常有效。