It is shown that the wavelet network structure with hidden layer decided by experience is not the optimization. 通过仿真实验发现凭经验选取小波神经网络隐层小波基,所得结构并不最优。
The study shows that the contract can lead to the optimal investment, conquer hidden information with moral hazard, and realize social efficiency optimization for construction work, through the determination of reasonable working condition, time, price and the rule of contract variation. 研究表明,通过确定合理的施工条件、工期、承包价及合同变更规则,承包合同可以引导承发包双方投资,避免隐藏信息的道德风险,实现社会福利最优。
Under the asymmetry information condition, i.e. the distribution-cost information of distributor is hidden, this is a converse selection problem, thus the production-distribution strategy is converted into the optimization control problem. 在非对称信息条件下,即营销商销售成本信息隐匿的情况,这是一种逆向选择问题,从而,生产营销决策被转化为最优控制问题。
In recent years, GA has functioned so well with robustness and interoperability, hidden parallelity and adaptability in the settlement of problems such as function optimization of successive variable and combinatorial optimization of discrete variable that it becomes an increasingly widespread application of smart optimization algorithms. 近年来,遗传算法在解决连续变量的函数最优化问题和离散变量的组合最优化问题时表现出的鲁棒性、全局性、隐并行性和自适应性使其成为一种应用日益广泛的智能优化算法。
Then the shortcomings of particle swarm optimization in solving the training of the hidden Markov model are conducted and a "premature" phenomenon in particle swarm optimization is described. 接着对粒子群优化算法在解决隐马尔可夫模型训练问题上的不足进行研究,阐述了粒子群优化算法中普遍存在的早熟现象。
After comparing BP networks 'performance with different train algorithms, transfer functions between hidden layer and output layer, and hidden layer neural cell numbers. Construction of BP network determined was used in process optimization and process control. 通过对具有不同学习算法、不同传递函数及不同隐含层神经元个数的BP网络性能进行比较,确定出本文优化和控制中采用的BP网络结构及参数,对注塑成型过程的工艺参数进行预测。
First of all, we use nearest neighbor clustering algorithm to determine the hidden layer nodes of neural network; secondly, we propose a genetic-improved particle swarm optimization algorithm to tune all the parameters of the neural network, which means activate function and weights between layers. 我们先用最近邻聚类算法确定径向基函数神经网络的隐含层所包含的神经元个数,然后提出一种遗传-加强粒子群算法来调整径向基函数神经网络的各个参数:作用函数及权重。
At the same time, combined with genetic algorithm crossover and mutation factor to optimize the hidden layer and output layer connection weights in each step of the genetic algorithm to optimize operations and combined with the elite preservation strategy can play a very good optimization result. 同时,结合遗传算法交叉变异因子来优化隐层与输出层的连接权值,在每一步的遗传算法优化操作中,结合了精英保存策略,可以起到很好的优化效果。