共查询到18条相似文献,搜索用时 62 毫秒
1.
2.
提出了一种可以减小网络规模的故障表示方法,并将Alopex算法引入神经网络模型的训练过程,将人工神经网络与规则推理相结合,建立了旋转机械故障诊断的神经网络专家系统。该系统充分利用了神经网络与规则推理的优点,采用正反向混合推理方式调用知识库中的各种知识进行诊断。采用二进制数码表示机械的各种故障,基于Alopex算法训练神经网络。建立的专家系统克服了基于规则专家系统的自学习困难问题和基于神经网络诊断系统的系统控制能力弱的缺点,具有较强的诊断能力。 相似文献
3.
蚁群算法在复合材料层合板优化设计中的应用 总被引:2,自引:0,他引:2
对含有2N层的对称层合板铺层优化,采用多层城市的思想,即将每层备选角度设为一层城市,共同组成具有相同特征的N层城市,优化的过程就是在N层城市中每层选择一座城市,组成N维铺层角度向量.文中采用含有变异操作的蚁群算法,按照求解旅行商问题(traveling salesman problem ,TSP)的方法和过程,对已知铺层总数复合材料层合板的某个参数进行优化设计,最终确定各角度的铺层数及铺层顺序.算例结果表明,经过有限次数的循环,即能收敛到满意的结果,优化过程显示蚁群算法的良好鲁棒性,同时该方法为解决复合材料结构优化及其他组合优化问题提供一种新的思路. 相似文献
4.
5.
智能优化算法在机械优化设计中的应用 总被引:3,自引:0,他引:3
针对传统机械优化设计算法存在的问题,分析介绍了近年来兴起的智能优化算法,主要是几种神经网络模型和进化计算等智能化算法用于机械优化设计的基本思想和应用方法。 相似文献
6.
7.
8.
针对机械优化设计中变量多、目标函数和约束条件复杂而难以求解的问题,建立了基于微粒群算法的机械优化设计的数学模型;并针对传统罚函数法处理约束条件而引起的病态问题,提出一种利用混沌变量来更新产生违约解个体的方式来改进微粒群算法,增加了个体的多样性、避免微粒群算法出现早熟,从而加快算法的收敛速度.实例计算表明该算法能较好地解决机械优化设计问题. 相似文献
9.
遗传算法在机械优化设计中的应用 总被引:7,自引:0,他引:7
针对遗传算法的特点对其进行了改进,在种群初始化中提出引用Hamming距离作为控制依据,在判断终止条件时提出了局部最优徘徊策略,使得改进后的GA在解决有约束非线性问题表现出良好的速度和有效性。 相似文献
10.
广义简约梯度算法在机械优化设计的应用 总被引:1,自引:0,他引:1
分析了广义简约梯度算法的原理及其实现形式,并结合一单级直齿圆柱齿轮减速器设计为例分析了其应用。利用Vissim软件完成了广义简约梯度算法设计,基于该实例的优化数学模型,在Vissim环境下完成了对单级直齿圆柱齿轮减速器优化的仿真建模,仿真结果表明该算法迭代次数少,求解精度高,非常适合于机械优化设计应用。 相似文献
11.
基于变异粒子群算法的过程挖掘 总被引:1,自引:0,他引:1
为实现过程挖掘,克服标准粒子群算法易陷入局部极值的缺点,提出基于变异操作的粒子群过程挖掘方法。在标准粒子群算法进化中,所有粒子追随最优粒子在解空间搜索,导致种群多样性迅速下降,出现早熟收敛。受遗传算法启发,通过对进化中的粒子增加变异操作,使算法摆脱易于陷入局部极值点的束缚,增强算法跳出局部最优的能力。仿真结果表明,基于变异粒子群算法的过程挖掘在求解的精度和速度方面都得到了好的效果。 相似文献
12.
13.
14.
15.
Particle swarm optimization(PSO) algorithm is an effective bio-inspired algorithm but it has shortage of premature convergence. Researchers have made some improvements especially in force rules and population topologies. However, the current algorithms only consider a single kind of force rules and lack consideration of comprehensive improvement in both multi force rules and population topologies. In this paper, a dynamic topology multi force particle swarm optimization(DTMFPSO) algorithm is proposed in order to get better search performance. First of all, the principle of the presented multi force particle swarm optimization(MFPSO) algorithm is that different force rules are used in different search stages, which can balance the ability of global and local search. Secondly, a fitness-driven edge-changing(FE) topology based on the probability selection mechanism of roulette method is designed to cut and add edges between the particles, and the DTMFPSO algorithm is proposed by combining the FE topology with the MFPSO algorithm through concurrent evolution of both algorithm and structure in order to further improve the search accuracy. Thirdly, Benchmark functions are employed to evaluate the performance of the DTMFPSO algorithm, and test results show that the proposed algorithm is better than the well-known PSO algorithms, such as μPSO, MPSO, and EPSO algorithms. Finally, the proposed algorithm is applied to optimize the process parameters for ultrasonic vibration cutting on Si C wafer, and the surface quality of the Si C wafer is improved by 12.8% compared with the PSO algorithm in Ref. [25]. This research proposes a DTMFPSO algorithm with multi force rules and dynamic population topologies evolved simultaneously, and it has better search performance. 相似文献
16.
Young-Mo Kong Su-Hyun Choi Bo-Suk Yang Byeong-Keun Choi 《Journal of Mechanical Science and Technology》2008,22(7):1313-1322
This paper proposes an integrated evolutionary optimization algorithm (IEOA) which is combined with genetic algorithm (GA),
random tabu search method (TS) and response surface methodology (RSM). This algorithm, in order to improve the convergent
speed that is thought to be the demerit of GA, uses RSM and the simplex method. Though mutation of GA offers random variety,
systematic variety can be secured through the use of tabu-list. Efficiency of this method has been proven by applying traditional
test functions and comparing the results to GA. And it is an evidence that the newly suggested algorithm can effectively find
the global optimum solution by applying it to minimize the weight of fresh water tank that is placed in the rear of ship designed
to avoid resonance. According to the results, GA’s convergent speed in initial phase has been improved by using RSM. An optimized
solution was calculated without the evaluation of additional actual objective function. Finally, it can be concluded that
IEOA is a very useful global optimization algorithm from the viewpoint of convergent speed and global search ability. 相似文献
17.
18.
一种新的变步长LMS自适应滤波算法研究及其应用 总被引:3,自引:0,他引:3
变步长LMS自适应滤波算法克服了传统自适应滤波算法的不足,通过构造合适的变步长因子,在提高收敛速度的同时保证了较小的稳态误差,在实际中得到了广泛应用。为进一步改善算法性能,首先对传统的和现有改进的变步长LMS算法机理进行了深入分析,在此基础上,提出了一种新的变步长LMS自适应滤波算法。该算法通过建立一个新的步长因子与误差的非线性函数模型,使得算法在不失精度的情况下,具有较快的收敛速度。论文对新算法的机理进行了较为详尽的阐述,对算法中关键参数的选取对滤波性能的影响进行了深入分析,并给出了算法中关键参数的自适应确定方法。仿真实验表明,相对于其他自适应滤波算法,该算法在收敛速度方面有了很大的提高。将新算法应用于对实际龙口水位监测数据的滤波中,取得了良好效果。 相似文献