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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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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BP神经网络的江苏省多维度碳排放预测 被引量:3
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作者 郑琰 夏朝泽 +2 位作者 肖玉杰 王杰 余伟 《环境科学》 北大核心 2025年第6期3485-3495,共11页
“双碳”目标下,推进节能减排是经济高质量发展的关键.通过创新提出在多维度视角下对江苏省的碳排放量进行影响因素分析和预测,针对性给出降低碳排放的策略.基于STRIPAT扩展模型和LMDI模型,构建江苏省碳排放量影响因素指标体系,多维度... “双碳”目标下,推进节能减排是经济高质量发展的关键.通过创新提出在多维度视角下对江苏省的碳排放量进行影响因素分析和预测,针对性给出降低碳排放的策略.基于STRIPAT扩展模型和LMDI模型,构建江苏省碳排放量影响因素指标体系,多维度分析不同指标因素对碳排放量的影响.运用岭回归和因子分析方法,得到碳排放量与各指标间的关联度和贡献率,采用BP神经网络算法对江苏省碳排放量进行预测.结果表明,江苏省碳排放量影响因素程度排名为:能源消耗量、GDP、人口、第三产业增加值占比、能耗结构、第二产业增加值占比和第一产业增加值占比.其中第一产业增加值占比和第二产业增加值占比这两个因素对碳排放量的增长起到了抑制作用,其余因素均为促进作用.同时根据预测结果,江苏省应当在2025~2035年间调整产业和能源结构,将非化石能源占比增至30%,单位CO_(2)排放下降28.6%,实现碳达峰.在2050年前后,将非化石能源占比提高到50%,单位能耗下降46.1%,则CO_(2)排放进入快速下降阶段.最终,在2060年前后将非化石能源占比超过80%,单位能耗下降54.6%,CO_(2)排放减少77.9%,达到碳中和. 展开更多
关键词 碳排放量影响因素 多维度 LMDI模型 岭回归 bp神经网络
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基于动量算法优化的BP神经网络HRG漂移补偿方法 被引量:1
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作者 罗巍 魏博深 +2 位作者 陈刚 唐明浩 戴劼峰 《中国惯性技术学报》 北大核心 2025年第5期502-509,共8页
针对半球谐振陀螺(HRG)漂移传统分步标定补偿方法存在的补偿精度低与耗时长问题,提出一种基于动量算法优化的反向传播(BP)神经网络HRG漂移补偿方法。根据HRG误差模型分析了分步标定补偿方法的局限性,构建了基于BP神经网络的HRG漂移补偿... 针对半球谐振陀螺(HRG)漂移传统分步标定补偿方法存在的补偿精度低与耗时长问题,提出一种基于动量算法优化的反向传播(BP)神经网络HRG漂移补偿方法。根据HRG误差模型分析了分步标定补偿方法的局限性,构建了基于BP神经网络的HRG漂移补偿模型,并引入动量算法,提升BP神经网络训练效率,利用三只自研的HRG进行了实验验证。实验结果表明:所提方法能够有效提升陀螺精度,同时简化标定和补偿流程,提高陀螺漂移补偿工作效率,相比现有分步标定补偿法,陀螺精度提升36.1%,标定补偿效率提升32.1%。 展开更多
关键词 半球谐振陀螺 bp神经网络 陀螺漂移补偿
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基于BP神经网络的路堑下穿致高铁桥墩位移的预测 被引量:1
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作者 宋旭明 陈松 +2 位作者 唐冕 孙凯 程丽娟 《中南大学学报(自然科学版)》 北大核心 2025年第6期2539-2549,共11页
依托某新建路堑工程,建立土体-桥梁三维数值模型,采用正交试验法分析高铁桥梁附加位移的参数敏感性,利用拉丁超立方抽样方法,通过神经网络(backpropagation neural network)拟合墩顶附加位移与主要影响因素的隐式函数关系,结合蒙特卡洛... 依托某新建路堑工程,建立土体-桥梁三维数值模型,采用正交试验法分析高铁桥梁附加位移的参数敏感性,利用拉丁超立方抽样方法,通过神经网络(backpropagation neural network)拟合墩顶附加位移与主要影响因素的隐式函数关系,结合蒙特卡洛法,对参数进行1×10^(6)次抽样计算,得到墩顶附加位移的超限概率。研究结果表明:浅层土体力学参数对墩顶纵向位移的影响较大,开挖深度对墩顶纵向位移的影响最显著;最优BP神经网络模型预测的墩顶附加位移与有限元计算值的均方误差为4.345×10^(-4),最大相对误差为5.1%,表明最优BP神经网络模型可代替有限元进行快速估算;当开挖深度在2 m以内时,背景工程墩顶纵向附加位移基本不会超限,当开挖深度为3 m时,超限概率达40%,建议开挖前采用适当的支护措施以确保结构安全。 展开更多
关键词 路堑开挖 敏感性分析 随机响应面 bp神经网络 位移预测 可靠度
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基于SA-PSO-BP神经网络的煤层底板破坏深度预测 被引量:3
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作者 李刚 赵艺鸣 +2 位作者 杨庆贺 才天 邹军鹏 《地下空间与工程学报》 北大核心 2025年第1期293-299,共7页
研究煤层底板破坏深度的准确预测对保证带压开采条件下煤矿的安全生产具有重要意义。针对传统BP神经网络预测底板破坏深度存在误差较大、容易陷入局部最优解、收敛速度慢等问题,提出了一种新的SA-PSO-BP网络模型。该模型以煤层倾角、开... 研究煤层底板破坏深度的准确预测对保证带压开采条件下煤矿的安全生产具有重要意义。针对传统BP神经网络预测底板破坏深度存在误差较大、容易陷入局部最优解、收敛速度慢等问题,提出了一种新的SA-PSO-BP网络模型。该模型以煤层倾角、开采深度、煤层开采厚度、工作面斜长作为评判指标,先利用粒子群优化算法(PSO)改进BP神经网络寻优过程、再引入模拟退火算法(SA)避免PSO算法陷入局部最优解,选取92组现场实测数据样本,对优化后的模型进行训练和预测。结果表明:SA-PSO-BP网络模型的拟合优度达到0.9835,比BP神经网络提高了0.2882;均方根误差达到1.3190,比BP神经网络减小了3.8641;平均绝对百分比误差达到5.4423,比BP神经网络减小了14.93%。构建的SA-PSO-BP网络模型具有可行性,为底板破坏深度的预测提供了一种合理的方法。 展开更多
关键词 带压开采 底板破坏深度 神经网络预测 SA-PSO-bp神经网络
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基于BP神经网络结合ERA5数据的风电功率预测 被引量:1
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作者 王婷婷 李斯胜 +4 位作者 于伟 能锋田 李星南 杨佳琳 熊亮 《储能科学与技术》 北大核心 2025年第1期183-189,共7页
随着我国风力发电技术的不断发展和完善,风电在电力系统运行和调度的作用越来越突出。为了高效准确地预测风电功率,减少大量风电入网带来的负面影响,本文基于BP神经网络结合ERA5数据对我国北方某风电场进行风电功率预测,并采用粒子群优... 随着我国风力发电技术的不断发展和完善,风电在电力系统运行和调度的作用越来越突出。为了高效准确地预测风电功率,减少大量风电入网带来的负面影响,本文基于BP神经网络结合ERA5数据对我国北方某风电场进行风电功率预测,并采用粒子群优化(particle swarm algorithm,PSO)算法优化模型,结合平均绝对误差、均方根误差和Pearson相关系数分析风电功率预测效果。结果表明,模型训练集中预测与实测风电功率变化趋势基本一致,呈现同增同减的趋势,BP模型的平均绝对误差为702.12 W,均方根误差为1000.18 W,相关系数为0.91,PSO-BP模型的平均绝对误差为700.75 W,均方根误差为995.16 W,相关系数为0.94;测试集中ERA5数据在一定程度上高估了风电功率,但整体趋势基本一致,BP模型的平均绝对误差为861.09 W,均方根误差为1150.86 W,相关系数为0.81;PSO-BP模型的平均绝对误差为829.55 W,均方根误差为1117.39 W,相关系数为0.83,模型的预测效果相对较好,PSO-BP模型相较于BP模型的预测效果均有一定程度的提高,在该区域的风电功率预测方面有较好的适用性。研究结果可为缺乏观测数据或观测数据质量不高的地区预测风电功率提供参考。 展开更多
关键词 风力发电 bp神经网络 ERA5再分析资料 粒子群优化算法 风电功率预测
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基于SSA-GA-BP神经网络的城轨地下线振动源强预测模型 被引量:1
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作者 刘庆杰 刘博亮 +3 位作者 冯青松 徐璐 罗信伟 刘文武 《铁道科学与工程学报》 北大核心 2025年第5期2355-2366,共12页
为寻求一种预测速度快、准确率高的城市轨道交通地下线振动源强预测模型,基于55个非减振轨道测试断面数据,经过数据清洗、分析和标签化后,建立了涵盖典型车型和主要线路参数取值范围的8 000多条实测数据库。分析地铁环境振动的影响因素... 为寻求一种预测速度快、准确率高的城市轨道交通地下线振动源强预测模型,基于55个非减振轨道测试断面数据,经过数据清洗、分析和标签化后,建立了涵盖典型车型和主要线路参数取值范围的8 000多条实测数据库。分析地铁环境振动的影响因素,利用斯皮尔曼相关系数得到各类影响因素与振动源强的关系强度。分别建立基于卷积神经网络(CNN)、随机森林(RF)、支持向量机(SVM)等5个机器学习模型,对比分析了不同模型对振动源强的预测效果。使用麻雀搜索算法(SSA)和遗传算法(GA)优化BP神经网络模型的结构、超参数、权重及阈值,对比SSA-GA-BP、SSA-BP、GA-BP神经网络对振动源强的预测精度。最终使用4个差异明显且未经模型学习的新断面验证SSA-GA-BP模型的泛化能力。结果表明:5种机器学习模型中BP神经网络的非线性回归拟合能力最强,验证集MAE损失为1.55 dB,决定系数为0.948;SSA-GA-BP模型对振动源强的预测精度高于SSA-BP和GA-BP,验证集MAE、MAPE和决定系数分别为1.289 dB、1.856%和0.967,有80.11%数据的平均绝对误差在2 dB以内;SSA-GA-BP模型对4个经典的新断面数据预测效果良好,4个断面汇总数据的MAE、MSE和MAPE误差值分别为1.21 dB、2.18 dB和1.67%,决定系数为0.977,有70%数据的预测误差在2 dB以内,证明了SSA-GA-BP模型有较强的泛化能力。SSA-GA-BP振源预测模型具有较好的预测精度和快速预测能力,研究可为轨道交通地下线路设计阶段的减振降噪设计提供参考。 展开更多
关键词 城市轨道交通地下线 振动源强 预测 bp神经网络 麻雀搜索算法 遗传算法
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PCA-BP神经网络模型在拖拉机发动机故障诊断中的应用 被引量:1
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作者 杨健 《农机化研究》 北大核心 2025年第3期254-258,共5页
拖拉机发动机故障诊断是指通过对拖拉机发动机的运行状态、传感器数据等信息进行分析和处理,识别出发动机故障的类型和位置,及时准确地诊断拖拉机发动机故障,对于提高农机装备的使用效率和经济效益具有重要的意义。为此,基于主成分分析(... 拖拉机发动机故障诊断是指通过对拖拉机发动机的运行状态、传感器数据等信息进行分析和处理,识别出发动机故障的类型和位置,及时准确地诊断拖拉机发动机故障,对于提高农机装备的使用效率和经济效益具有重要的意义。为此,基于主成分分析(PCA)算法对拖拉机发动机的传感器数据进行降维处理,并使用BP神经网络对降维后的数据进行分类识别,以实现拖拉机发动机故障的诊断。试验结果表明:PCA-BP神经网络模型可以准确地诊断拖拉机发动机的多种故障,相比于传统的BP神经网络模型,具有更高的准确率和更好的泛化能力,表明PCA-BP神经网络模型在拖拉机发动机故障诊断中具有较大的应用前景。 展开更多
关键词 拖拉机发动机 故障诊断 主成分分析 bp神经网络
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特征融合与BP神经网络结合的刀具磨损预测 被引量:1
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作者 郭宏 徐延 +1 位作者 伊亚聪 胡孔耀 《机械设计与制造》 北大核心 2025年第1期108-111,116,共5页
通过监测刀具磨损情况,能够有效应对生产加工中的意外状况。为了精确监测刀具的磨损状态,提出了一种多传感器特征融合及BP神经网络结合的刀具磨损预测方法。首先对工业加工中采集到的切削力、振动、声发射信号进行小波阈值去噪,然后在... 通过监测刀具磨损情况,能够有效应对生产加工中的意外状况。为了精确监测刀具的磨损状态,提出了一种多传感器特征融合及BP神经网络结合的刀具磨损预测方法。首先对工业加工中采集到的切削力、振动、声发射信号进行小波阈值去噪,然后在时域、频域和时频域内分析并提取特征,再将融合后的各类传感器特征使用Pearson相关系数和主成分分析(PCA)实现数据降维,最后将降维后的融合特征输入搭建好的BP神经网络,通过非线性仿真分析,从而实现刀具磨损量的预测。案例验证表明:与单一传感器预测相比,提出的多传感器特征融合的刀具磨损预测方法误差最小,且决定系数R2达到0.993。 展开更多
关键词 传感器 特征提取 小波去噪 PCA bp神经网络 磨损预测
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改进SSA优化BP神经网络的变压器故障诊断 被引量:2
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作者 汪繁荣 汪筠涵 江俊杰 《现代电子技术》 北大核心 2025年第4期145-150,共6页
变压器故障类型的准确诊断对保障电网的安全与稳定至关重要。针对BP神经网络与麻雀搜索算法(SSA)存在收敛缓慢和易陷入局部极值导致无法准确诊断的问题,提出将改进的麻雀搜索算法(ISSA)优化BP神经网络应用于变压器故障诊断。首先,引入... 变压器故障类型的准确诊断对保障电网的安全与稳定至关重要。针对BP神经网络与麻雀搜索算法(SSA)存在收敛缓慢和易陷入局部极值导致无法准确诊断的问题,提出将改进的麻雀搜索算法(ISSA)优化BP神经网络应用于变压器故障诊断。首先,引入非线性惯性权重和纵横交叉策略,从而提高算法的收敛速度和全局寻优能力;其次,将ISSA与传统SSA在收敛函数上进行对比分析,得到ISSA算法在迭代12次后以52%的准确率收敛,而SSA算法迭代23次后才达到25%的准确率,证明了ISSA在收敛速度和精度方面有明显提高;最后,将ISSA-BP、SSA-BP和BP诊断模型进行对比。实验结果表明,ISSA-BP模型准确率达到了97%,比SSA-BP、BP神经网络模型分别提高了4%和11%,可以认为提出的算法模型在变压器故障诊断领域具有更高的精度与良好的发展前景。 展开更多
关键词 麻雀搜索算法 bp神经网络 变压器 故障诊断 非线性惯性权重 纵横交叉策略
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