神经网络遗传算法值寻优

1 BP神经网络简介1.1 BP神经网络原理人工神经网络（ANN）是在人类对其大脑神经网络认识理解的基础上人工构造的能够实现某种功能的神经网络。它是理论化的人脑神经网络模型，基于模仿大脑神经网络结构和功能而建立的一种信息处理系统。人工神经网络是由许多并行互联的相同神经元模型组成的，网络的信号处理由神经之间的相互作用来实现。神经网络实际上描述了网络输入与输出之间一种函数关系。只要由足够的实验或工业数据集，通常可以用来预测不同输入变量下的结果。在化学工程中还可以运用于故障诊断和特征分类、预测和优化、时变系统的过程预测、模型化和控制、混合使用神经网络和专家系统对复杂过程的优化与设计。图1生物体单个神经元图2有一向量输入的神经元模拟图3人脑神经细胞图4人工神经网络模拟BP神经网络是一种多层前馈神经网络，该网络的主要特点是信号向前传递，误差反向传播。在向前传递中，输入信号从输入层经隐含层逐层处理，直至输出层。每一层的神经元状态只影响下一层神经元状态。如果输出层得不到期望输出，则反向传播，根据预测误差调整BP神经网络的权值和阈值，从而使BP神经网络预测不断逼近期望输出。1.2 BP神经网络拓扑结构jkij图5 BP神经网络的拓扑结构图图3中，X1，X2，Xn是BP神经网络的输入值，O1,，Oj是BP神经网络的预测值，ij和jk为BP神经网络权值。BP神经网络可以看作一个非线性函数，网络输入值和预测输出值分别为该函数的自变量和因变量。当输入节点数为n、输出节点数为j时，BP神经网络就表达了从n个自变量到就j个因变量的函数映射关系。1.3 BP神经网络实现步骤BP神经网络预测前首先需要训练网咯，通过训练使网络具有联想记忆和预测能力。实现步骤如下：Step1：网络初始化。根据系统输入序列（X,Y）确定网络输入层节点数n，隐含层节点数l，输出层节点数m。初始化输入层、隐含层和输出神经元之间的连接权值ij和jk，隐含层阈值a和输出层阈值b，给定学习速率和神经元激励函数。Step2：隐含层输出计算。根据输入自变量X，输入层与隐含层间连接权值ij以及隐含层阈值a计算出H。Step3：输出层输出计算。根据H、隐含层与输出层间连接权值jk以及阈值b计算出BP神经网络输出O。Step4：误差计算。根据网络预测输出O和期望输出Y，计算网络预测误差e。Step5：权值更新。根据网络预测误差e更新网络连接权值ij和jk。Step6：阈值更新。根据网络预测误差e更新网络节点阈值a和b。Step7：判断算法迭代是否结束，若没有结束，返回Step2。1.4 BP神经网络实现流程图6 算法流程2 遗传算法简介2.1 遗传算法原理遗传算法（GA）是1962年由美国Michigan大学Holland教授提出的模拟自然界遗传机制和生物进化论而形成的一种并行随机搜索最优化方法。它把自然界“优胜劣汰，适者生存”的生物进化眼里引入优化参数形成的编码串联群体中，按照所选择的适应度函数并通过遗传中的选择、交叉和变异对个体进行筛选，使适应度值好的个体被保留，适应度值差的个体被淘汰。新的群体既继承了上一代的信息，又优于上一代。这样反复循环，直至满足条件。2.2 遗传算法拓扑结构2.3 遗传算法实现步骤Step1：随机初始化种群；Step2：计算机种群适应度值，从中找出最优个体；Step3：选择操作；Step4：交叉操作；Step5：变异操作；Step6：判断进化是否结束，若否，则返回Step2。2.4 遗传算法流程3 编程简介对于用于吸收烟气中二氧化硫的吸收塔，存在许多变量，其中对于吸收液亚硫酸钠溶液，可以调节和控制吸收液的浓度、吸收液的进料量、吸收液的温度；对于吸收塔进口处的烟道气，存在烟气流量波动、烟气温度、烟气组分（特别是二氧化硫的含量），但这些变量受生产任务、燃料品质、燃烧状况等的影响，比较复杂，不便于控制；对于出口处的吸收液中亚硫酸钠含量受吸收效果（与温度、压力、化学反应平衡、物理溶解平衡）、烟气中二氧化硫含量、吸收液的浓度、吸收液的用量等有关；从吸收塔中排放的烟气的变化量有排放烟气温度、排放量、排放烟气中二氧化硫含量的变化。经过前期的分析和流程模拟，我们发现吸收塔进入的烟气量和烟气中二氧化硫的浓度难以改变和控制。对于烟气温度的控制，第一种方法是通过选择烟道气的出口位置，因为烟道不同的阶段的烟气温度不同，但一旦建设成功就难以改变，不方便调节；第二种方法是加大喷淋塔的喷液量以及改善传质、传热，但是这会影响系统的水平衡，容易因小失大，得不偿失。第三种方法是在烟道气进入吸收塔之前利用冷却水进行换热，但是这样会使吸收塔外围设备增加。经过模拟发现，对于整个系统来说，吸收液的温度控制在40比较合理，因此不再设法利用加热或冷却设备来调节吸收液的温度。对于亚硫酸钠吸收液的浓度调节比较繁琐和成本较大，若直接添加溶解可能造成滞后效应，若配置不同浓度的吸收液然后进行不同配比来调节浓度，需要储罐和场地较多以及控制系统设计较为复杂。因此为了使出口烟气中二氧化硫含量达到排放标准，我们通过宏观上来控制亚硫酸钠吸收液的进液量来改变吸收塔的吸收效果，使烟气中的二氧化硫排放达到较高的标准。而吸收液的用量与烟气的状态密切相关。通过Aspen模拟从众多的变量中筛选出自变量为：（1）经过吸收塔后烟道气中二氧化硫含量。（2）吸收塔处理烟气量；（3）进口烟气组分二氧化硫含量；（4）进口烟气温度；因变量为：（1）吸收液的进液量。3.1 编程思路我们的目的是希望通过编程实现对这个体系进行模拟，在达到深度脱硫标准的前提下，以便能够及时自动调节吸收液的进液量来，减少吸收液的消耗量以及电渗析反应器单位时间内的处理任务。编程思路：首先用BP网络来仿真拟合这个系统，把被拟合的系统看成是一个黑箱，先取出若干组系统的输入输出数据对BP网络进行训练，训练后的BP网络就可以表达这个系统，已知系统输入值的情况下，可以用它来预测系统的输出值。然后把BP网络的输出值看成是个体的适应度值，用遗传算法来寻找系统的最佳输入值，使对应的适应度值最优。即用遗传算法来寻找标准测试函数的极值，表明该算法在未知系统极值寻优中的作用。具体内容如下：先利用Aspen以吸收塔进气量GI和进气温度TEM，进气的二氧化硫含量GS，进液的量LQ为自变量进行模拟，收集其模拟得到的出口烟气二氧化硫含量。然后以吸收塔进气量GI和进气温度TEM，进气的二氧化硫含量GS，吸收后二氧化硫含量自变量作为输入数据，以进液的量LQ作为输出数据训练出BP神经网络，然后利用训练好的BP神经网络对烟气的以各个变量发生变动后进行预测，然后将BP神经网络对吸收液的用量预测值作为遗传算法的个体适应度值，通过选择交叉和变异操作寻找函数全局最优值（最小值），并返回对应的输入值吸收塔出口烟气二氧化硫的含量，烟气的进气量，烟气中二氧化硫的含量和烟气的温度。然后依此为依据调节LQ吸收液的进入量并对二氧化硫排放情况进行评估。3.2算法流程整个算法主要分为神经网络和遗传算法两大模块，其中神经网络模块的作用是根据寻优系统的结构构建合适的神经网络，用系统的输入输出数据训练后来表达这个系统。神经网络模块又可以分为BP神经网络构建，BP神经网络训练和BP神经网络预测是三个子模块。其中BP网络构建根据被拟合系统的输入输出参数构建合适的BP网络，该网络的输入节点和系统输入参数对应，输出节点和系统输出参数对应。BP神经网络训练用系统输入输出数据对BP网络进行训练，BP神经网络拟合，用训练好的BP网络根据系统输入预测系统输出，遗传算法模块用训练好的BP网络构建适应度函数，采用选择、交叉、变异等遗传算子寻找系统最佳输出。3.3编程实现3.3.1BP神经网络（1）数据准备利用已经完善的流程对未来可变情况进行模拟，以烟气的进气量、烟气中二氧化硫含量、烟气的温度为自变量，然后通过不断地改变吸收液的进液量，使烟气达到我们深度脱硫的排放标准。根据吸收塔的物料衡算方程和Aspen的灵敏度分析的结果，可知出口烟气二氧化硫的含量与吸收液的含量成负相关，当其他条件不变时， 吸收液的量越大，出口二氧化硫的含量越小，越容易达到深度脱硫排放标准。但吸收液并不是越多越好，吸收液消耗得越多，则经济成本越高。因此对实际情况来说，我们希望找到二氧化硫含量变化随吸收液变化的突变点或其达标的临界值，得到对应的临界亚硫酸钠溶液的临界体积。我们将各个自变量变化的组合情况输入到流程完整的Aspen进行case study，经过数据筛选得到了如下的原始数据表：表1 BP神经网络输入输出训练数据烟气进量（kg/h）烟气温度（）Gasin中SO2的浓度（kg/m3）LIQIN流量（kg/h)GASOUT二氧化硫的质量（kg/h) 1920190650.004292673136116.4714.99229083192019067.50.004324509136566.4545.000558421920190700.00435634137012.6955.01548405192019072.50.004388177137457.7395.015096141920190750.00442137895.6695.04064501192019077.50.004451832138331.9395.04382531920190800.004483654138760.5865.065778761920190800.004483653138760.5865.06611856192019082.50.004515481139185.395.073393051920190850.004547302139601.9915.09052867192019087.50.004579126140012.4365.100313841920190900.004610946140413.6025.11543801192019092.50.004642766140806.4145.126378461920190950.004674584141188.4475.140154551881786.2650.004292675133392.3094.889431721881786.267.50.004324509133832.884.900918531881786.2700.00435634134270.2924.915169581881786.272.50.004388177134706.4814.914799231881786.2750.00442135135.7084.939828411881786.277.50.004451832135563.3154.942929851881786.2800.004483654135983.4564.964459221881786.2800.004483653135983.4564.964791951881786.282.50.004515481136399.8414.971911441881786.2850.004547302136808.1944.988712451881786.287.50.004579126137210.5254.998296071881786.2900.004610946137603.7695.013124111881786.292.50.004642766137988.8395.023842421881786.2950.004674584138363.3565.037346581843382.4650.004292675130667.7574.789572321843382.467.50.004324508131099.0444.802444231843382.4700.004356341131528.2524.813026981843382.472.50.004388176131954.9684.816606791843382.4750.00442132375.7414.839028381843382.477.50.004451832132794.6954.842003071843382.4800.004483654133206.3254.863139371843382.4800.004483654133206.3254.863464651843382.482.50.004515481133614.2924.870430091843382.4850.004547302134014.3964.886896211843382.487.50.004579126134408.6124.896278291843382.4900.004610946134793.9354.910810211843382.492.50.004642766135171.2634.921306511843382.4950.004674584135538.2624.934538641804978.6650.00429268127944.254.680850051804978.667.50.004324513128366.764.692534781804978.6700.00435634128785.5134.714517681804978.672.50.004388177129204.0174.71377171804978.6750.00442129615.7854.738190191804978.677.50.004451832130026.0644.74115091804978.6800.004483654130429.1934.761820261804978.6800.004483654130429.1934.762139041804978.682.50.004515481130828.7414.768948111804978.6850.004547302131220.5964.785079961804978.687.50.004579126131606.6984.794260481804978.6900.004610946131984.14.80849631804978.692.50.004642766132353.6854.818768851804978.6950.004674584132713.1674.831731851766574.8650.004292675125218.5714.590362461766574.867.50.004324509125632.334.600799891766574.8700.00435634126043.0794.614229611766574.872.50.004388177126452.7154.613820451766574.8750.00442126855.824.637377651766574.877.50.004451832127257.4384.640245731766574.8800.004483654127652.064.660500651766574.8800.004483654127652.064.660812231766574.882.50.004515481128043.1894.667466591766574.8850.004547302128426.7954.68326371766574.887.50.004579126128804.7824.692242661766574.8900.004610946129174.2634.706182581766574.892.50.004642766129536.1054.716232911766574.8950.004674584129888.074.72892345172817167.50.004324517122900.2554.487008461728171700.004356341123300.944.51244853172817172.50.004388171123699.9544.525400451728171750.004420005124097.0254.52738701172817177.50.004451827124487.7084.547786941728171800.004483657124875.8434.553284791728171800.004483658124875.8434.55235614172817182.50.004515479125256.9244.570310651728171850.004547304125633.5594.57821182172817187.50.004579125126002.4074.592678121728171900.004610947126364.7874.60206061172817192.50.004642765126718.2324.615018341728171950.004674585127063.2044.625163361689767.267.50.004324504120164.3134.408909351689767.2700.004356347120559.754.401633711689767.272.50.004388171120948.7534.424796071689767.2750.004420005121337.0384.426732421689767.277.50.004451827121719.1014.446719681689767.2800.004483657122098.6884.452083211689767.2800.004483658122098.6884.451174251689767.282.50.004515479122471.3824.468748691689767.2850.004547304122839.7444.476455861689767.287.50.004579125123200.4974.490612741689767.2900.004610947123554.9394.499781731689767.292.50.004642765123900.6544.512456841689767.2950.004674585124238.0984.522373781651363.467.50.004324506117431.2074.305226171651363.4700.004356344117816.8034.305847651651363.472.50.004388171118197.5134.324260711651363.4750.004420005118577.0534.326057011651363.477.50.004451827118950.4944.345652691651363.4800.004483657119321.5324.350881331651363.4800.004483658119321.5324.349992041651363.482.50.004515479119685.844.367181281651363.4850.004547304120045.9274.374703941651363.487.50.004579125120398.5854.388549651651363.4900.004610947120745.0894.397503011651363.492.50.004642765121083.0744.409895341651363.4950.004674585121412.9894.419584111612959.667.50.004324507114697.7664.204480861612959.6700.004356345115074.3984.205491761612959.672.50.004388171115446.2834.223689971612959.6750.004420005115817.064.225428371612959.677.50.004451827116181.8844.244586011612959.6800.004483657116544.3744.249679141612959.6800.004483658116544.3744.248809471612959.682.50.004515479116900.294.265653841612959.6850.004547304117252.1044.272975051612959.687.50.004579125117596.6724.2864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