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- A Study of Application of An Improved PSO Algorithm in BP Network 一种改进的粒子群算法在BP网络中的应用研究
- An improved PSO algorithm was presented and applied to optimal the PID parameters of electromotor. 为此,提出一种改进的PSO优化算法,并将该算法应用于电机控制系统的PID参数优化设计。
- To get better optimization results, an improved PSO algorithm named IPSO including variance mechanism and local updating mechanism was presented. 为提高其优化求解效果,引入变异机制及局部更新机制对粒子群优化算法进行改进。
- The typical BP algorithm and improved BP algorithm are applied to the fault diagnosis of Tennessee Eastman(TE) model. 并分别将典型的BP算法和改进后的BP算法用于TE(Tennessee Eastman)模型的故障诊断中。
- The test results based on three benchmark functions show that the improved PSO algorithm has a good performance on global convergency and convergence precision. 基于3个基准测试函数的测试结果显示改进粒子群优化算法具有较好的全局收敛性和收敛精度。
- The simulation results show that cross-validation BP algorithm improved the efficiency of learnin... 仿真结果表明,交叉验证BP算法提高了网络学习的效率。
- An improved PSO (particle swarm optimization) algorithm is presented which well addresses slow convergence speed and low calculation precision in the basic PSO algorithm. 摘要提出了一种改进的粒子群算法,很好地解决了基本粒子群算法中易陷入局部最优的缺点。
- It is shown, by derivations and calculations, that the improved BP algorithm can obviously reduce the learning time. 最后,利用实测数据进行验证。结果表明,改进的神经网络算法明显提高网络收敛速度;
- It states that the improved BP algorithm and the hybrid BP algorithm are adapted well to treating the prototype observation data of a dam. 由此表明,采用改进的BP算法和混合BP算法来处理大坝观测数据是行之有效的。
- The BP network model is established for parameters design of bolt-shotcrete support in tunnels, and the shortcomings of the BP algorithm are improved. 建立了隧道锚喷支护设计参数选择的BP网络模型,并对BP算法中的不足之处加以改进。
- We analyzed various improved methods because of the problem that conventional BP algorithm was liable to trap in local minimum value and was slow rate of convergence. 针对传统即算法易陷入局部极小和收敛速度慢的问题,分析了各种改进方法。
- Subsequently,we briefly discuss the identifiability of the parameters.Finally,in order to find the optimal parameters of the identification model,an improved PSO algorithm is constructed. 最后结合模型特点构造了一种改进的粒子群优化(PSO)算法求得最优参数,并利用所得的参数进行过程仿真。
- In order to overcome the shortcomings that standard Particle Swarm Optimization(PSO) traps into local optima easily and has a low convergence accuracy,an improved PSO algorithm is proposed. 摘要 针对标准粒子群算法容易陷入局部最优、收敛精度低的缺点,提出了一种改进的粒子群算法。
- Neural networks have been widely used in kinds of research fields. In this paper, faults of CSTR will be detected and diagnosed using an improved BP algorithm. 将BP算法和使用复合法修正初始权值的BP算法运用到CSTR模型中进行故障诊断。
- Then, the improved PSO is applied to optimization of the structure and parameters in NN (neural network). 改进的粒子群算法被用于优化神经网络的结构和参数,结果表明:不但网络的结构得到控制,而且泛化性能有了较大的提高。
- In this paper, a novel variant activation (transform) sigmoid function with three parameters is proposed, and then the improved BP algorithm based on it is educed and discussed. 摘要提出了人工神经元的一种新颖的多参数可调激活函数,推导出相应的BP学习算法。
- Experimental results indicate that the ANN based on improved PSO can reduce the times of training and MSE effectively. 仿真实验表明:基于改进型粒子群优化算法的神经网络可以有效降低训练次数和均方误差。
- The system employs a diagnosis method,which combines fuzzy neural networks with improved BP algorithm and can swiftly and accurately determine the location of a condenser fault. 系统采用了模糊神经网络与改进的BP算法相结合的故障诊断方法,能快速地、准确地判断出凝汽器故障所在。
- To solve the premature convergence problem of the Particle Swarm Optimization (PSO), an improved PSO method was proposed. 针对粒子群优化算法早熟收敛现象,提出了一种改进的粒子群优化算法。
- Last the article make the network with BP Algorithm to recognize the character, the strongpoint is great self-studying ability and fast speed. 最后,本文采用了基于反向传播算法(BP算法)的神经网络系统来识别字符,其优点是结构设计简单,自学习能力较强,识别速度快。