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The Application of BP Networks to Land Suitability Evaluation 被引量:14
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作者 LIU Yanfang JIAO Limin 《Geo-Spatial Information Science》 2002年第1期55-61,共7页
The back propagation (BP) model of artificial neural networks (ANN) has many good qualities comparing with ordinary methods in land suitability evaluation.Through analyzing ordinary methods’ limitations,some sticking... The back propagation (BP) model of artificial neural networks (ANN) has many good qualities comparing with ordinary methods in land suitability evaluation.Through analyzing ordinary methods’ limitations,some sticking points of BP model used in land evaluation,such as network structure,learning algorithm,etc.,are discussed in detail,The land evaluation of Qionghai city is used as a case study.Fuzzy comprehensive assessment method was also employed in this evaluation for validating and comparing. 展开更多
关键词 ANN bp networks bp algorithm land suitability evaluation
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Prediction of Hot Ductility of Low-Carbon Steels Based on BP Network 被引量:3
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作者 Xinyu Liu, Bo Wen, Xinhua Wang, Qiang Niu, Hong Chen Key Lab of New Packaging Materials & Technology of China National Packaging Corporation, Zhuzhou Engineering College, 412008, China University of Science & Technology Beijing, Beijing 100083, China 《Journal of University of Science and Technology Beijing》 CSCD 2001年第3期182-184,共3页
The purpose of the research is to obtain an effective method to predict the hot ductility of low-carbon steels, which will be a reference to evaluate the crack sensitivity of steels. Several sub-networks modeled from ... The purpose of the research is to obtain an effective method to predict the hot ductility of low-carbon steels, which will be a reference to evaluate the crack sensitivity of steels. Several sub-networks modeled from BP network were constructed for different temperature use, and the measured reduction of area (A(R)) of 12 kinds of low-carbon steels under the temperature of 600 to 1000 degreesC were processed as training samples. The result of software simulation shows that the model established is relatively effective for predicting the hot ductility of steels. 展开更多
关键词 bp network hot ductility crack sensitivity
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Classification of Infrared Monitor Images of Coal Using an Feature Texture Statistics and Improved BP Network 被引量:2
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作者 SUN Ji-ping CHEN Wei +3 位作者 MA Feng-ying WANG Fu-zeng TANG Liang LIU Yan-jie 《Journal of China University of Mining and Technology》 EI 2007年第4期489-493,共5页
It is very important to accurately recognize and locate pulverized and block coal seen in a coal mine's infrared image monitoring system. Infrared monitor images of pulverized and block coal were sampled in the ro... It is very important to accurately recognize and locate pulverized and block coal seen in a coal mine's infrared image monitoring system. Infrared monitor images of pulverized and block coal were sampled in the roadway of a coal mine. Texture statistics from the grey level dependence matrix were selected as the criterion for classification. The distributions of the texture statistics were calculated and analysed. A normalizing function was added to the front end of the BP network with one hidden layer. An additional classification layer is joined behind the linear layer. The recognition of pulverized from block coal images was tested using the improved BP network. The results of the experiment show that texture variables from the grey level dependence matrix can act as recognizable features of the image. The innovative improved BP network can then recognize the pulverized and block coal images. 展开更多
关键词 pulverized-coal-image block-coal-image gray level dependence matrix improved bp networks
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Performance of Feedback BP Networks 被引量:1
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作者 Luo Siwei Yang Wujie & Zhang Aijun(Dept. of Computer Science & Technology. Northern Jiaotong University, Beijing 100044, China) 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 1995年第3期11-18,共8页
Through adding feedbacks in multi-layer BP networks, the network performance is improvedconsiderably compared with general BP network and Hopfield network, particularly the associative memorizing ability. In this pape... Through adding feedbacks in multi-layer BP networks, the network performance is improvedconsiderably compared with general BP network and Hopfield network, particularly the associative memorizing ability. In this paper, we analyze the two networks: feedback BP network and Hopfiled network andcompare the property between them. The conclusion shows that feedback BP network has more powerfulassociation memorizing ability than Hopfiled network. 展开更多
关键词 Neural network ALGORITHM bp network
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Real-time multi-step prediction control for BP network with delay 被引量:8
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作者 张吉礼 欧进萍 于达仁 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2000年第2期82-86,共5页
Real time multi step prediction of BP network based on dynamical compensation of system characteristics is suggested by introducing the first and second derivatives of the system and network outputs into the network i... Real time multi step prediction of BP network based on dynamical compensation of system characteristics is suggested by introducing the first and second derivatives of the system and network outputs into the network input layer, and real time multi step prediction control is proposed for the BP network with delay on the basis of the results of real time multi step prediction, to achieve the simulation of real time fuzzy control of the delayed time system. 展开更多
关键词 DELAYED time system multi STEP prediction bp network COMPENSATION of DYNAMICAL characteristics fuzzy control simulation
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The applying of BP network in forecasting the demand and its growth rate for coal 被引量:4
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作者 纪成君 刘宏超 《Journal of Coal Science & Engineering(China)》 2001年第1期102-107,共6页
Based on the statistical data from 1975 to 1997, we forecast the growth rate of coal consuming and the quantity in coming decade with the BP neuron network in the article.
关键词 the quantity of coal consuming the growth rate of consuming bp neuron network forecasting
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Optimization of Injection Molding Process of Bearing Stand Based on BP Network Method 被引量:1
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作者 虞俊波 周小林 +2 位作者 邓常乐 刘军 王骥 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2014年第2期180-185,共6页
The quality of injection plastic molded parts relates to precise geometry,smooth surface,strength,durability,and other indicators that are associated with the mold,materials,injection process,and service environment.T... The quality of injection plastic molded parts relates to precise geometry,smooth surface,strength,durability,and other indicators that are associated with the mold,materials,injection process,and service environment.The warpage is one of main defects of injection products,which cost much time and materials.In order to minimize warpage to ensure the precise shape of molded parts,it needs to combine design,service conditions,process parameters,material properties,and other factors in the design and manufacturing.Finite element tools and material database are used to analyze the occurrence of warpage,and analysis results contribute to the improvement and optimization of injection molding process of typical parts.To find the optimal process parameters in the solution space,experimental data are used to establish backpropagation(BP)network for predicting warpage of a bearing stand based on analysis with Moldflow.With a proper transfer function and the BP network architecture,results from the BP network method satisfiy the criteria of accuracy.The optimal solutions are searched in the BP network by the genetic algorithm with the finding that the optimization method based on the BP network is efficient. 展开更多
关键词 injection molding orthogonal test MOLDFLOW bp neural network warpage deflection
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MENDED GENETIC BP NETWORK AND APPLICATION TO ROLLING FORCE PREDICTION OF 4-STAND TANDEM COLD STRIP MILL 被引量:3
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作者 ZhangDazhi SunYikang +1 位作者 WangYanping CaiHengjun 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2004年第2期297-300,共4页
In order to make good use of the ability to approach any function of BP (backpropagation) network and overcome its local astringency, and also make good use of the overallsearch ability of GA (genetic algorithms), a p... In order to make good use of the ability to approach any function of BP (backpropagation) network and overcome its local astringency, and also make good use of the overallsearch ability of GA (genetic algorithms), a proposal to regulate the network's weights using bothGA and BP algorithms is suggested. An integrated network system of MGA (mended genetic algorithms)and BP algorithms has been established. The MGA-BP network's functions consist of optimizing GAperformance parameters, the network's structural parameters, performance parameters, and regulatingthe network's weights using both GA and BP algorithms. Rolling forces of 4-stand tandem cold stripmill are predicted by the MGA-BP network, and good results are obtained. 展开更多
关键词 Genetic algorithms bp algorithms Neural network Tandem cold strip mill Rolling force prediction
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Forecasting Loss of Ecosystem Service Value Using a BP Network: A Case Study of the Impact of the South-to-north Water Transfer Project on the Ecological Environmental in Xiangfan, Hubei Province, China 被引量:1
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作者 YUN-FENG CHEN, JING-XUAN ZHOU, JIE XIAO, AND YAN-PING LIEnvironmental Science and Engineering College, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China 《Biomedical and Environmental Sciences》 SCIE CAS CSCD 2003年第4期379-391,共13页
Objective To recognize and assess the impact of the South-to-north Water Transfer Project (SNWTP) on the ecological environment of Xiangfan, Hubei Province, situated in the water-out area, and develop sound scientific... Objective To recognize and assess the impact of the South-to-north Water Transfer Project (SNWTP) on the ecological environment of Xiangfan, Hubei Province, situated in the water-out area, and develop sound scientific countermeasures. Methods A three-layer BP network was built to simulate topology and process of the eco-economy system of Xiangfan. Historical data of ecological environmental factors and socio-economic factors as inputs, and corresponding historical data of ecosystem service value (ESV) and GDP as target outputs, were presented to train and test the network. When predicted input data after 2001 were presented to trained network as generalization sets, ESVs and GDPs of 2002, 2003, 2004... till 2050 were simulated as output in succession. Results Up to 2050, the area would have suffered an accumulative total ESV loss of RMB 104.9 billion, which accounted for 37.36% of the present ESV. The coinstantaneous GDP would change asynchronously with ESV, it would go through an up-to-down process and finally lose RMB89.3 billion, which accounted for 18.71% of 2001. Conclusions The simulation indicates that ESV loss means damage to the capability of socio-economic sustainable development, and suggests that artificial neural networks (ANNs) provide a feasible and effective method and have an important potential in ESV modeling. 展开更多
关键词 Artificial neural network bp Ecosystem service value South-to-north Water Transfer Project
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Application of genetic BP network to discriminating earthquakes and explosions
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作者 BIAN Yin-ju(边银菊) 《Acta Seismologica Sinica(English Edition)》 EI CSCD 2002年第5期540-549,共10页
We developed a GA-BP algorithm by combining the genetic algorithm (GA) with the back propagation (BP) algorithm and established a genetic BP neural network. We also applied the BP neural network based on the BP algori... We developed a GA-BP algorithm by combining the genetic algorithm (GA) with the back propagation (BP) algorithm and established a genetic BP neural network. We also applied the BP neural network based on the BP algorithm and the genetic BP neural network based on the GA-BP algorithm to discriminate earthquakes and explosions. The obtained result shows that the discriminating performance of the genetic BP network is slightly better than that of the BP network. 展开更多
关键词 artificial neural network bp algorithm genetic algorithm
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基于多算法优化BP神经网络的机床主轴振动监控方法
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作者 孙文 郭磊磊 +2 位作者 曾威 席文奎 魏航信 《工具技术》 北大核心 2026年第1期102-109,共8页
针对机床主轴在切削过程及运行故障时产生较大振动,会导致加工产品质量下降和机床切削精度降低的问题,提出基于粒子群、遗传、模拟退火算法优化的BP神经网络机床主轴振动监控模型。阐述BP神经网络和3种优化算法模型的理论公式。基于解... 针对机床主轴在切削过程及运行故障时产生较大振动,会导致加工产品质量下降和机床切削精度降低的问题,提出基于粒子群、遗传、模拟退火算法优化的BP神经网络机床主轴振动监控模型。阐述BP神经网络和3种优化算法模型的理论公式。基于解算三轴振动传感器方法,将三轴振动传感器部署在机床主轴上,完成不同工况下机床主轴振动信号的采集。利用采集到的数据对BP神经网络进行训练和测试,并将统计学方法融入BP神经网络测试函数,提升监控模型的输出精度。结果表明,优化的监控模型训练初始误差降低40%~50%,训练时误差收敛速度高于未优化模型,其中粒子群算法能更好地提高BP神经网络的误差收敛速度。该研究结果为机床主轴振动监控和切削过程优化提供理论参考。 展开更多
关键词 机床主轴 bp神经网络 振动 传感器 监控
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Utilizing BP neural networks to accurately reconstruct the tritium depth profile in materials for BIXS
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作者 Chen Zhao Wei Jin +2 位作者 Yan Shi Chang-An Chen Yi-Ying Zhao 《Nuclear Science and Techniques》 2025年第1期103-114,共12页
β-ray-induced X-ray spectroscopy(BIXS)is a promising method for tritium detection in solid materials because of its unique advantages,such as large detection depth,nondestructive testing capabilities,and low requirem... β-ray-induced X-ray spectroscopy(BIXS)is a promising method for tritium detection in solid materials because of its unique advantages,such as large detection depth,nondestructive testing capabilities,and low requirements for sample preparation.However,high-accuracy reconstruction of the tritium depth profile remains a significant challenge for this technique.In this study,a novel reconstruction method based on a backpropagation(BP)neural network algorithm that demonstrates high accuracy,broad applicability,and robust noise resistance is proposed.The average reconstruction error calculated using the BP network(8.0%)was much lower than that obtained using traditional numerical methods(26.5%).In addition,the BP method can accurately reconstruct BIX spectra of samples with an unknown range of tritium and exhibits wide applicability to spectra with various tritium distributions.Furthermore,the BP network demonstrates superior accuracy and stability compared to numerical methods when reconstructing the spectra,with a relative uncertainty ranging from 0 to 10%.This study highlights the advantages of BP networks in accurately reconstructing the tritium depth profile from BIXS and promotes their further application in tritium detection. 展开更多
关键词 β-ray-induced X-ray spectroscopy Tritium detection bp network Ridge regression Reconstruction problem
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基于WOA-BP-LSTM自编码器的CFRP薄壁C柱轴压响应预测
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作者 牟浩蕾 张贾 +1 位作者 冯振宇 白春玉 《航空学报》 北大核心 2026年第4期112-124,共13页
针对航空器货舱下部碳纤维增强复合材料(CFRP)薄壁C柱在准静态轴压下的力-位移响应预测问题,提出了一种融合鲸鱼优化算法(WOA)、反向传播(BP)神经网络和长短期记忆(LSTM)自编码器的智能预测模型(WOA-BPLSTM自编码器模型)。通过CFRP薄壁... 针对航空器货舱下部碳纤维增强复合材料(CFRP)薄壁C柱在准静态轴压下的力-位移响应预测问题,提出了一种融合鲸鱼优化算法(WOA)、反向传播(BP)神经网络和长短期记忆(LSTM)自编码器的智能预测模型(WOA-BPLSTM自编码器模型)。通过CFRP薄壁C柱准静态轴压试验验证了有限元模型可靠性,其轴压响应评价指标误差均小于10%,基于该模型构建了包含700组变截面几何参数的力-位移响应数据集。采用LSTM自编码器实现力-位移响应特征降维与重建,随后采用BP神经网络对力-位移响应进行预测,并采用WOA进行神经网络参数优化。结果表明,LSTM自编码器实现了力-位移响应的高精度重建,测试集初始峰值压溃力和能量吸收的重建误差均小于3%,80%样本误差小于1%;优化后预测模型的力-位移响应预测精度显著提升,测试集平均绝对误差(MAE)降低17.55%,均方误差(MSE)降低31.77%,均方根误差(RMSE)降低17.47%,初始峰值压溃力和能量吸收的预测误差均小于8%,80%样本误差小于5%。该智能预测模型实现了变截面CFRP薄壁C柱轴压响应的快速精准预测并降低了计算成本,为其轴压响应研究提供了一种高效的参数-性能映射工具。 展开更多
关键词 CFRP薄壁C柱 轴压响应 LSTM自编码器 鲸鱼优化算法 bp神经网络
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基于BP神经网络的成都砂卵石离散元模型细观参数标定研究
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作者 袁胜洋 练小莲 +3 位作者 周伟星 李城栋 谷耀 刘先峰 《铁道学报》 北大核心 2026年第1期140-150,共11页
砂卵石土广泛分布于成都地区,受颗粒粒径限制,采用常规试验手段研究其力学特性时,耗时长且成本高。离散元数值试验是研究砂卵石力学特性的一有效手段,但颗粒间细观参数难以确定。基于砂卵石三轴试验,通过统计真实颗粒圆度和纵横比,采用... 砂卵石土广泛分布于成都地区,受颗粒粒径限制,采用常规试验手段研究其力学特性时,耗时长且成本高。离散元数值试验是研究砂卵石力学特性的一有效手段,但颗粒间细观参数难以确定。基于砂卵石三轴试验,通过统计真实颗粒圆度和纵横比,采用凸包法生成不规则颗粒,利用三维离散元软件构建考虑砂卵石颗粒形貌特征的数值模型。基于不同细观参数试算得到的25组数据建立神经网络,采用BP神经网络反演方式标定模型参数,分别采用莱文贝格-马夸特方法、贝叶斯正则化方法和量化共轭梯度法对数据进行训练。使用后验差分析法评估3种方法预测的模型数据精度。结果表明:使用贝叶斯正则化方法得出的预测参数精度最高,确定的砂卵石土颗粒法切向刚度比k、摩擦系数f分别为1.633、0.831;基于该细观参数,对不同细粒含量的砂卵石三轴试验进行模拟,模型数据和试验数据误差基本都在±10%以内,表明BP神经网络可用于砂卵石模型颗粒法切向刚度比和摩擦系数标定。 展开更多
关键词 砂卵石 不规则颗粒 三维离散元 bp神经网络 细观参数标定
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基于GA-BP神经网络的露天矿山排土场边坡失稳预测
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作者 谢尊贤 马浩浩 +1 位作者 江松 武潇云 《中国安全科学学报》 北大核心 2026年第3期81-88,共8页
为提高矿山排土场边坡失稳预测的准确性与可靠性,构建一种基于改进遗传算法(GA)优化反向传播(BP)神经网络的露天矿山排土场边坡失稳预测模型。利用GA全局优化BP神经网络的权值和阈值,并引入Levenberg-Marquardt(LM)算法以提升网络收敛效... 为提高矿山排土场边坡失稳预测的准确性与可靠性,构建一种基于改进遗传算法(GA)优化反向传播(BP)神经网络的露天矿山排土场边坡失稳预测模型。利用GA全局优化BP神经网络的权值和阈值,并引入Levenberg-Marquardt(LM)算法以提升网络收敛效率;选取台阶坡面角、岩土内应力、台阶高度、地表位移、孔隙水压力等10个关键指标作为输入,以边坡安全系数为输出,并通过150组矿山案例数据进行模型训练与验证。结果表明:相较于传统BP模型,GA-BP模型的均方误差(MSE)、平均绝对误差(MAE)和平均绝对百分比误差(MAPE)分别降低46.9%、25.4%和5.38%,预测值更贴近安全系数阈值(F_(s)=1.2),预测灵敏度和稳定性显著提升。皮尔森相关性分析进一步显示,地表位移与内部位移(0.98)、孔隙水压力与降雨量(0.75)呈强相关性,验证了输入指标的合理性。 展开更多
关键词 遗传算法(GA) 反向传播(bp)神经网络 露天矿山 排土场 边坡失稳预测 安全系数
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基于BP神经网络构建儿童肺炎支原体混合腺病毒感染的重症肺炎预测模型
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作者 姚国华 刘杰 +3 位作者 张雯 马翠安 魏博涛 高娜 《天津医药》 2026年第4期369-373,共5页
目的基于反向传播法(BP)神经网络构建儿童肺炎支原体(MP)混合腺病毒(ADV)感染的重症肺炎的临床预测模型。方法回顾性分析138例MP混合ADV感染的社区获得性肺炎患儿的临床、实验室及影像学资料,按7∶3将研究对象随机分为训练集(96例)和测... 目的基于反向传播法(BP)神经网络构建儿童肺炎支原体(MP)混合腺病毒(ADV)感染的重症肺炎的临床预测模型。方法回顾性分析138例MP混合ADV感染的社区获得性肺炎患儿的临床、实验室及影像学资料,按7∶3将研究对象随机分为训练集(96例)和测试集(42例),构建BP神经网络预测模型。训练集用沙普利加法解释量化临床特征贡献度,筛选出MP混合ADV的重症肺炎的预测因子。通过测试集的准确率、损失值、混淆矩阵对其进行验证。结果重症组发热持续天数、最高体温、中性粒细胞百分比(N%)、天冬氨酸转氨酶(AST)、乳酸脱氢酶(LDH)、白细胞介素-6(IL-6)、大片炎性实变、住院天数高于非重症组,淋巴细胞百分比(L%)、白蛋白低于非重症组(P<0.05)。基于BP神经网络研究的结果显示发热持续天数、AST、N%、最高体温、大片炎性实变、IL-6、L%、LDH是MP混合ADV感染所致重症肺炎的关键预测因子。在构建儿童重症MP混合ADV临床预测模型上,测试集显示准确率90.48%、损失值0.2332。结论基于BP神经网络成功构建的儿童MP混合ADV感染重症肺炎的预测模型筛选出8项关键预测因子,可为临床早期识别重症病例提供参考。 展开更多
关键词 肺炎 支原体 腺病毒 同时感染 模型 统计学 儿童 bp神经网络 沙普利加法解释
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基于BP神经网络-滑动模态控制的多轴实时混合试验研究
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作者 张涛 谭平 +2 位作者 姚洪灿 上官跃坤 周惠蒙 《振动与冲击》 北大核心 2026年第7期56-66,共11页
针对多轴实时混合试验中耦合效应及时滞累积的问题,基于三层三跨钢框架的Benchmark控制问题,提出了反向传播(back propagation,BP)神经网络-滑动模态控制的补偿方法。BP神经网络通过数据归一化、隐含层输出计算及误差反馈调整权值阈值,... 针对多轴实时混合试验中耦合效应及时滞累积的问题,基于三层三跨钢框架的Benchmark控制问题,提出了反向传播(back propagation,BP)神经网络-滑动模态控制的补偿方法。BP神经网络通过数据归一化、隐含层输出计算及误差反馈调整权值阈值,实现非线性时滞的有效预测;而滑模控制器通过构造含积分项的滑模面函数与饱和控制律,可实现作动器的动态解耦并抑制抖振。在软件MATLAB中结合状态空间模型,集成神经网络训练结果与滑模控制模块,实现多轴协同控制及时滞补偿。所提出的方法显著降低了作动器间的耦合效应,增强了复杂工况下多自由度协同鲁棒性,为工程结构动力响应评估提供了新的有效手段。 展开更多
关键词 多轴实时混合试验 反向传播(bp)神经网络 滑动模态控制 时滞补偿方法
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基于感性工学与BP神经网络的电动修枝剪造型设计优化
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作者 杨梅 张帆 苏兆婧 《工业设计》 2026年第2期143-146,共4页
文章从用户情感需求与产品造型设计要素出发,结合数学模型相关理论与方法构建回归模型,实现高适应性的产品设计,从而解决目标产品设计与用户实际需求难以深度匹配的问题。首先,采用语义差异量表法,系统收集用户对目标产品的感性意象量... 文章从用户情感需求与产品造型设计要素出发,结合数学模型相关理论与方法构建回归模型,实现高适应性的产品设计,从而解决目标产品设计与用户实际需求难以深度匹配的问题。首先,采用语义差异量表法,系统收集用户对目标产品的感性意象量化数据,并进行归纳与分类;其次,对目标产品模型进行模块化分解,对各模块进行数字化编码,利用所获得的情感意象评价值与模型数据进行模型训练;最后,通过二次语义差异法问卷实验验证方法的有效性。在此基础上,基于BP神经网络预测情感评价最优的产品造型,并进行第二轮用户问卷评分,以检验模型精度。该方法有助于缓解农业工具设计实践中主观需求向客观设计转化过程中存在的匹配不足问题。 展开更多
关键词 工业设计 bp神经网络 遗传算法 感性工学 电动修枝剪
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基于BP神经网络与遗传算法优化白芍产地加工与炮制生产一体化工艺研究
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作者 张喜红 王玉香 《安徽中医药大学学报》 2026年第2期98-103,共6页
目的解决白芍炮制生产一体化生产工艺参数寻优方法单一的问题,进一步优化白芍炮制工艺参数。方法以白芍炮制生产一体化工艺流程为研究对象,基于BP神经网络算法,选取煮制时间、干燥时间、干燥温度3项工艺参数为神经网络输入,以白芍主要... 目的解决白芍炮制生产一体化生产工艺参数寻优方法单一的问题,进一步优化白芍炮制工艺参数。方法以白芍炮制生产一体化工艺流程为研究对象,基于BP神经网络算法,选取煮制时间、干燥时间、干燥温度3项工艺参数为神经网络输入,以白芍主要成分含量的总评归一值为神经网络输出,构建质量评价预测模型。将所构建的质量评价预测模型与遗传算法相结合,构建时间与质量复合型适应度函数,进行工艺参数寻优研究。结果遗传算法-BP神经网络工艺参数寻优模型求得的最佳工艺参数为煮制时间13.956 min,干燥时间4.495 h,干燥温度52.498℃,总评归一值0.759。结论遗传算法-BP神经网络工艺参数寻优模型与Box-Behnken响应面法可相互验证,遗传算法-BP神经网络工艺参数寻优方法可作为单一响应面法寻优的有力补充,为白芍炮制领域工艺参数寻优提供了一种新的解决方案。 展开更多
关键词 白芍 炮制工艺 bp神经网络 遗传算法
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面向电主轴的TFOA-BP电阻辨识方法
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作者 李鹏 李鸿业 张丽秀 《制造技术与机床》 北大核心 2026年第4期235-243,共9页
高速电主轴作为高速切削机床的核心部件,其控制精度直接受到定子电阻变化的影响,然而高速电主轴在实际运行中,会出现因温升等因素导致定子电阻发生漂移,进而引发控制性能下降的关键问题,以及传统辨识方法对初始值敏感、易陷入局部最优... 高速电主轴作为高速切削机床的核心部件,其控制精度直接受到定子电阻变化的影响,然而高速电主轴在实际运行中,会出现因温升等因素导致定子电阻发生漂移,进而引发控制性能下降的关键问题,以及传统辨识方法对初始值敏感、易陷入局部最优的缺陷。针对以上问题,提出了一种基于改进果蝇优化算法(tent-chaos improved fruit fly optimization algorithm, TFOA)与反向传播(back propagation, BP)神经网络相结合的定子电阻辨识方法(TFOA-back propagation, TFOA-BP),旨在提高辨识精度与鲁棒性。仿真实验结果表明,所提TFOA-BP方法的定子电阻辨识误差稳定在±0.004 6Ω,较传统BP神经网络误差降低68.2%;与多种主流方法对比,均方误差(mean squared error, MSE)平均减少了42.7%。所提方法在辨识精度、收敛速度及稳定性方面均具明显优势,对电机参数智能辨识具有理论参考与工程应用价值。 展开更多
关键词 果蝇优化算法 Tent混沌映射 精英保留机制 bp神经网络 电主轴
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