神经网络与遗传算法的英文

• neural networks & genetic algorithms

• "神经"英文翻译    nerve; nervus
• "网络"英文翻译    network; electric network me ...
• "与"英文翻译    take part in; participate in
• "遗传"英文翻译    heredity; hereditary; inheri ...
• "算法"英文翻译    algorithm
• "神经网络算法" 英文翻译 :    neural-net algorithms; nna neural net algorithms
• "遗传算法" 英文翻译 :    genetic algorithms （ga）; genetic analysis
• "元遗传算法" 英文翻译 :    meta genetic algorithm
• "并行遗传算法" 英文翻译 :    parallel genetic algorithm pga; parallelgeneticalgorithm,pga; pga
• "很乱遗传算法" 英文翻译 :    messyga,mga
• "混合遗传算法" 英文翻译 :    hybrid genetic algorithm hga
• "基本遗传算法" 英文翻译 :    simple genetic algorithm sga
• "凌乱遗传算法" 英文翻译 :    messy ga mga
• "模糊遗传算法" 英文翻译 :    fuzzy genetic algorithm
• "mp神经网络" 英文翻译 :    mp neural network
• "光神经网络" 英文翻译 :    optical neural network
• "类神经网络" 英文翻译 :    articificial neural network; artificial neural network (ann)
• "神经网络" 英文翻译 :    biological neural network; nerve network; neural network, nn; neural networks; neuron network; neuronic network; neutral networks; nn neural network; radial basis function
• "神经网络的" 英文翻译 :    neural net
• "巨并行遗传算法" 英文翻译 :    massively pga; massivelypga
• "模糊控制遗传算法" 英文翻译 :    fcga
• "伪并行遗传算法" 英文翻译 :    ppga
• "遗传算法欺骗问题" 英文翻译 :    ga deceptive problem
• "是一种很有潜力的神经网络算法" 英文翻译 :    pso
• "倒转神经网络" 英文翻译 :    back-propagation neutral network

• Application of bp artificial neural network and genetic algorithm to the parameters optimization of profile extrusion die
  人工神经网络与遗传算法在型材挤压模具参数优化中的应用
• From the point of the combination of both nn and ga , to research the intelligent identification technology for concrete structures is conducive to the practical application of engineering
  本文从神经网络与遗传算法的结合出发，研究结构损伤智能识别技术，具有较强的工程背景和实际应用价值。
• The data mining model combined with neural networks algorithm and genetic algorithm make the mf nodes arrangement and establishment location predictable and auto - adaptive under the future conditions
  采用神经网络与遗传算法相结合的数据挖掘模型，能够使整个物流网络布局和设施选址对于未来的情况具有预测性和自适应性。
• In this paper , a set of composites liquid - solid extrusion application software is complied by using of the visual c + + , matlab and access software . the visualization and interaction are realized through this software , what ' s more , the functions of fuzzy neural model setting up , parameter prediction , parameter optimization , figure exporting and database accessing are included . the composite liquid - solid extrusion process parameters can be predicted and optimized by use of the software
  本文利用microsoftvc6 . 0 、 matlab以及microsoftaccess等软件，自行编制了一套基于模糊神经网络与遗传算法的集工艺建模、参数预测、参数优化、图形输出及数据库访问为一体的液-固挤压成形工艺应用软件，实现了该软件的可视化及良好的交互性。
• The paper discuss the way to this question and want to explain the question by neural networks and ga with the help of projection arithmetic . the algorithm uses complexion model to detect karst object . first , the paper introduce the important of the research . then the paper understand the algorithm of patterm recognition and apply it to the images of remote sensing in jinping karst area
  因此，本文先归纳和分析了当前遥感图象处理与模式识别的典型算法，然后利用目前流行的神经网络与遗传算法结合高斯-克吕格投影等平差分析算法进行遥感图象中的岩溶地物信息模式识别。
• The main contents are following : ( 1 ) from the methodology of nn , the basic theories on nn are discussed , with the emphasis on the mechanism of nn and its study rules . then the bp nn is concerned , because it is the comparatively most widely used nn type in the field of structure ' s damage identification ; ( 2 ) from the angle of system identification theories , the method and process of establishing the identification system model are demonstrated . also , how to implement a structural damage identification system of concrete architecture , based on bp neural network is demonstrated in the thesis ; ( 3 ) in order to find a more effective training algorithm of global approach , the way of optimizing network ' s weights using ga is demonstrated
  论文的主要内容包括： ( 1 )从神经网络理论出发，探讨了神经网络的基本理论，并重点论述了神经网络的工作机制和学习规则，及在结构损伤识别领域中广泛应用的前向神经网络模型- - - - bp神经网络模型； ( 2 )从系统识别论的角度，提出了利用神经网络建立混凝土结构损伤识别反问题的思路、方法和步骤，并在此基础上研究了基于bp神经网络的结构损伤识别系统对单处梁结构进行识别的方法； ( 3 )为了寻找一种更有效的全局逼近学习算法，本论文从神经网络与遗传算法相结合的角度，阐述了遗传算法结合bp算法优化神经网络权值的方法，实验证明，遗传算法和神经网络相结合不仅具有神经网络泛化的映射能力，而且具有遗传算法快速和全局逼近的优点，是一种较好的解决混凝土结构损伤识别问题的方法； ( 4 )基于java语言设计并实现了结构损伤识别系统。
• A combined neural network and genetic algorithm with solving stability safety of homogeneous slope was proposed and the finite element method is applied to analysis the progressive failure process of the slope and the maximum equilibrium theory , requests out stability safety of homogeneous slope with the smooth arc radius of difference with the difference below the level coordinate of arc peak , utilizing the neural network algorithm to establish slidng the nonlinear mapping relationship between level coordinate of arc radious and arc peak , being adapted the neural network algorithm to look for along the minimal stability safety of homogeneous slope and corresponding arc radious and arc peak
  提出了求解边坡稳定性安全系数的神经网络与遗传算法。该方法采用有限元分析和极限平衡理论，求出不同的滑弧半径和不同的弧顶水平坐标下的边坡稳定性安全系数，利用神经网络算法建立滑弧半径和弧顶水平坐标与安全系数之间的非线性映射关系，采用遗传算法搜索边坡的最小稳定性安全系数及相应的滑弧半径和滑弧中心坐标。
• With the precondition that neural network model can accurately reflect the operation situation of the systems , the paper discusses how to effectively integrate the neural network and genetic algorithm , by utilizing the comprehensive searching ability , to minimize the energy consumption of the system under a specific load . the controlling state parameters of the system and the calculation results indicate the optimization result of a steady state is satisfactory
  在神经网络模型能准确的反应系统运用工况的前提下，本文讨论了如何将神经网络与遗传算法有效的结合起来，利用遗传算法的全局搜索能力，寻找在特定负荷下为使系统的能耗最小，系统中各控制参数的状态，计算表明系统稳态优化结果令人满意。
• The research mentioned above shows that : the system of structural damage identification based on the combination of nn and ga has acquired relatively high accuracy and rapid convergence . as concerned as the ban with a single damage , the beam with one , two and three damages , the system works comparatively effective . meanwhile , the research mentioned above also shows that method based on the combination of nn and ga , which is used to identify the structural damage , is valuable and worthy of further concern
  上述内容的研究表明：基于bp神经网络与遗传算法的结构损伤识别系统的识别效果较好，收敛速度较快；针对单处、二处、三处损伤梁结构，以及单处损伤板结构的损伤识别效果较好，同时也表明，基于神经网络与遗传算法的结构损伤识别方法是解决混凝土结构损伤识别问题的较为有效的途径之一，具有较大的工程应用价值和进一步深入研究的意义。