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混合智能算法
相关语句
  hybrid intelligent algorithm
    Combined with fast convergence and high accuracy, a hybrid intelligent algorithm was proprosed to solve the parameter calibration of the nonlinear system.
    针对非线性系统的多参数定标问题,结合最小二乘法和遗传算法各自的优点,提出了一种收敛速度较快、精度较高的混合智能算法
短句来源
    Based on the different activities of user intention in Web initiative services,a hybrid intelligent algorithm to discover and distinguish user intention was presented.
    针对用户意图在主动服务各个环节中的不同作用,采用混合智能算法在主动服务中对用户意图进行辨识。
短句来源
  hybrid intelligence algorithm
    Therefore,the hybrid intelligence algorithm is effective to solve 0-1 knapsack problems.
    因此,应用该混合智能算法求解0-1背包问题是比较有效的.
短句来源
    Aimed at the 0-1 knapsack problems,the article proposes a kind of hybrid intelligence algorithm combining with the adjusting strategy,the greedy algorithm and the binary particle swarm optimization algorithm.
    针对0-1背包问题,提出一种具有修复策略的、贪心算法与二进制粒子群算法相结合的混合智能算法.
短句来源
  “混合智能算法”译为未确定词的双语例句
    We solve the model using a mixed intelligent algorithm which is a combination of fuzzy simulation, Artificial Neural Network and Genetic Algorithm (GA).
    对此模型的求解,采用了模糊模拟、神经元网络和遗传算法相结合的混合智能算法
短句来源
    This paper shows a new hybrid neural network for image compression, in which the hybrid genetic algorithm and BP algorithm approach are used to train the weight vector. So its convergent speed and precision are improved greatly.
    讨论了一种混合神经网络,该网络使用遗传算法与BP算法相结合的混合智能算法进行权值训练,明显地提高了神经网络的收敛速度和精度。
短句来源
    In this paper, we propose a new optimization method combining input-output analysis with fuzzy dependant-chance goal programming, and built a fuzzy optimization model of production planning. A fuzzy simulation, neural networks and genetic algorithm-based integrated intellective algorithm is presented to solve the problem.
    提出了一种新的流程企业生产计划的优化方法,将投入产出分析与模糊相关机会目标规划结合,建立流程企业生产计划的模糊优化模型,并使用基于模糊模拟、神经元网络和遗传算法的混合智能算法进行求解。
短句来源
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  hybrid intelligent algorithm
The designed hybrid intelligent algorithm by embedding the trained neural network into genetic algorithm can optimize the general grey fuzzy programming problems.
      
Finally, one numerical example is provided to illustrate the effectiveness of the model and the hybrid intelligent algorithm.
      
In order to solve general fuzzy programming models, a hybrid intelligent algorithm is also documented.
      
The hybrid intelligent algorithm described in Section 3 was then applied.
      


This paper shows a new hybrid neural network for image compression, in which the hybrid genetic algorithm and BP algorithm approach are used to train the weight vector. So its convergent speed and precision are improved greatly. The results of test with this method show high compression ratio, high ratio of signal vs noise, low errors of coding, high decoding speed and fine resuming effect on subject.

讨论了一种混合神经网络,该网络使用遗传算法与BP算法相结合的混合智能算法进行权值训练,明显地提高了神经网络的收敛速度和精度。实验证明,利用混合神经网络进行图像压缩,不仅压缩比高、信道误码率低、解码速度快,而且图像恢复质量主观效果好。

Combined with fast convergence and high accuracy, a hybrid intelligent algorithm was proprosed to solve the parameter calibration of the nonlinear system. The results that computed by the improved least-square algorithm became the the original values of the genetic algorithm where gene range could be dynamically changed. The experiment shows that the hybrid algorithm is valid in practical application.

针对非线性系统的多参数定标问题,结合最小二乘法和遗传算法各自的优点,提出了一种收敛速度较快、精度较高的混合智能算法。首先通过改进的最小二乘法计算得到问题的次优解,以此作为遗传算法的基因中心值,并将基因范围动态缩小进行进化计算,从而获得最优解。实验结果证明混合算法在工程应用中是有效的。

The traditional research on the production planning in process manufacturing is lack of modeling method for complicated system, and most of the production methods are single-objective and certain optimization method, so current production planning system is lack of flexibility. In this paper, we propose a new optimization method combining input-output analysis with fuzzy dependant-chance goal programming, and built a fuzzy optimization model of production planning. A fuzzy simulation, neural networks and genetic...

The traditional research on the production planning in process manufacturing is lack of modeling method for complicated system, and most of the production methods are single-objective and certain optimization method, so current production planning system is lack of flexibility. In this paper, we propose a new optimization method combining input-output analysis with fuzzy dependant-chance goal programming, and built a fuzzy optimization model of production planning. A fuzzy simulation, neural networks and genetic algorithm-based integrated intellective algorithm is presented to solve the problem.

传统的流程企业生产计划研究缺少大系统建模方法和相应的优化算法,而且多为单目标、确定性模型,使生产计划缺乏应有的灵活性。提出了一种新的流程企业生产计划的优化方法,将投入产出分析与模糊相关机会目标规划结合,建立流程企业生产计划的模糊优化模型,并使用基于模糊模拟、神经元网络和遗传算法的混合智能算法进行求解。

 
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