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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PSO-BP的水质监测系统设计
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作者 张凌飞 赵明玉 +2 位作者 赵展文 陈博行 陈洋洋 《现代电子技术》 北大核心 2026年第4期33-41,共9页
为提高水质监测系统覆盖范围并提升系统鲁棒性,设计一种以LoRa技术为通信方式,结合BP神经网络的水质监测系统。利用多节点采集水质的温度、pH值、总溶解固体(TDS)、氧化还原电位(ORP)等参数,通过无线传输技术将数据传输至汇聚节点,之后... 为提高水质监测系统覆盖范围并提升系统鲁棒性,设计一种以LoRa技术为通信方式,结合BP神经网络的水质监测系统。利用多节点采集水质的温度、pH值、总溶解固体(TDS)、氧化还原电位(ORP)等参数,通过无线传输技术将数据传输至汇聚节点,之后上传至云端物联网平台并实时下载到本地数据库,以支持网络模型处理和数据可视化分析,实现了多区域信息采集。再结合粒子群优化(PSO)算法优化BP神经网络的水质参数预测模型,实现对水质参数的预测补充,以提高系统的鲁棒性。通过实验验证系统水质信息采集的准确性以及参数预测模型的可靠性,结果表明,粒子群优化算法优化的BP神经网络模型对于pH值、温度、TDS和ORP四个参数的预测平均绝对百分比误差分别降低0.8269%、1.9475%、1.1039%和0.3125%,能够满足监测系统的需求。 展开更多
关键词 水质监测 无线传输 LoRa技术 粒子群优化算法 bp神经网络 参数预测
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基于GA-BP神经网络的碳纤维复合芯导线压接缺陷识别方法
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作者 杜志叶 黄子韧 +2 位作者 俸波 岳国华 廖永力 《电工技术学报》 北大核心 2026年第1期315-328,共14页
碳纤维复合芯导线因其低碳节能等特性,在输电线路的增容改造中有着良好的应用前景。但碳纤维芯棒十分脆弱,技术工艺不成熟,由于压接不良导致的断线事故时有发生,制约了该技术的推广应用。为此,该文针对断裂和少压两种严重压接缺陷,提出... 碳纤维复合芯导线因其低碳节能等特性,在输电线路的增容改造中有着良好的应用前景。但碳纤维芯棒十分脆弱,技术工艺不成熟,由于压接不良导致的断线事故时有发生,制约了该技术的推广应用。为此,该文针对断裂和少压两种严重压接缺陷,提出一种碳纤维复合芯导线压接缺陷的漏磁检测信号缺陷特征提取方法。通过实验优化,以漏磁检测信号数据中7个峰值点的幅值、21个相对位置信息和7个波形类型信息作为缺陷判断特征值,有效地提高了缺陷种类和缺陷程度识别的准确度。对碳纤维芯导线进行磁性制备,并研制相对应的漏磁检测装置,生产106根不同类型、不同程度的碳纤维芯压接缺陷样品,得到613组漏磁检测信号数据并完成特征值提取,搭建基于遗传算法(GA)的反向传播(BP)神经网络。实测数据表明,该方法可以有效地完成对碳纤维复合芯导线压接缺陷类型的识别,同时对缺陷程度的识别准确率可达到94.31%。 展开更多
关键词 碳纤维复合芯导线 缺陷识别 磁性制备 漏磁检测 遗传算法 bp神经网络
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基于BP神经网络的混凝土热学参数反演方法及应用
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作者 田仲初 赵望 +2 位作者 张祖军 彭涛 林乐鑫 《交通科学与工程》 2026年第1期134-142,共9页
【目的】解决大体积混凝土温度场仿真计算中热学参数与施工现场实际情况不符的问题。【方法】采用BP神经网络对温度场仿真计算所需的热学参数进行反演分析,首先通过均匀设计理论与温度场有限元法分析,构造BP神经网络的训练样本以及测试... 【目的】解决大体积混凝土温度场仿真计算中热学参数与施工现场实际情况不符的问题。【方法】采用BP神经网络对温度场仿真计算所需的热学参数进行反演分析,首先通过均匀设计理论与温度场有限元法分析,构造BP神经网络的训练样本以及测试样本;然后通过L-M算法优化BP神经网络,拟合出测点温度与热学参数的非线性关系;最后,将施工现场实测温度值输入优化后的网络,实现多个热力学参数的同步反演分析,在巴洛河主墩承台大体积混凝土施工中反演绝热温升、导热系数与表面放热系数。【结果】基于L-M算法优化后的BP神经网络能加快网络收敛速度,且反演参数对应的温度计算值与温度实测值吻合良好。【结论】将均匀设计理论引入BP神经网络反演分析中能有效地提高反演分析的效率,该研究成果能够为大体积混凝土施工温度场仿真计算提供指导,进而辅助温控施工。 展开更多
关键词 桥梁工程 大体积混凝土 bp神经网络 均匀设计 热力学参数 参数反演
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基于GOA-BP的海域蒸发波导智能预报方法
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作者 文凯 闫晓龙 廖希 《电波科学学报》 北大核心 2026年第1期187-196,共10页
面向对流层超视距通信对大区域高分辨率蒸发波导高度的精确性预报需求,提出了一种融合塘鹅优化算法(gannet optimization algorithm, GOA)和反向传播(back propagation, BP)神经网络的预报模型,即GOABP模型。首先利用天气研究和预报模型... 面向对流层超视距通信对大区域高分辨率蒸发波导高度的精确性预报需求,提出了一种融合塘鹅优化算法(gannet optimization algorithm, GOA)和反向传播(back propagation, BP)神经网络的预报模型,即GOABP模型。首先利用天气研究和预报模型(weather research and forecasting model, WRF)中尺度数值模式,获得区域环境气象参数;其次,结合美国海军研究生院NPS模型预报蒸发波导高度,构建出包含环境信息与蒸发波导高度预报值的联合数据集;再次,引入GOA优化BP神经网络的初始参数,显著增强模型的全局搜索能力和收敛速度,规避传统BP神经网络易于陷入局部最优解的缺陷;最后,经过训练得到GOA-BP模型。实验表明,GOABP模型决定系数达到0.972 1,验证均方根误差(root mean square error, RMSE)平均值为2.24 m,说明GOABP模型能够更准确有效地预报蒸发波导高度。本文方法可为超短波/微波超视距雷达和无线电通信系统规划和应用提供参考。 展开更多
关键词 蒸发波导预报 WRF NPS模型 反向传播(bp)神经网络 塘鹅优化算法(GOA)
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融合CUSUM方法与BP神经网络的实际供热管网分级泄漏检测
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作者 周守军 刘晓康 +3 位作者 王耀龙 刘书豪 董建敏 赵一林 《暖通空调》 2026年第3期139-144,共6页
为解决目前供热管网泄漏故障检测困难、效率低的现状,本文提出了一种融合CUSUM(累积和)与BP神经网络(BPNN)的管网泄漏故障分级检测系统。该系统首先采用CUSUM方法(一级)检测供热管网补水流量并判断是否泄漏,如果该管网泄漏,则再采用BP... 为解决目前供热管网泄漏故障检测困难、效率低的现状,本文提出了一种融合CUSUM(累积和)与BP神经网络(BPNN)的管网泄漏故障分级检测系统。该系统首先采用CUSUM方法(一级)检测供热管网补水流量并判断是否泄漏,如果该管网泄漏,则再采用BP神经网络(二级)对泄漏位置进行精确定位。以某矿区实际供热管网为研究对象,结合其供暖期内运行数据与仿真数据,以PCA(主成分分析)方法及数据归一化进行数据处理,构建并训练了实际供热管网泄漏位置检测的BPNN模型,最终开发了该矿区的CUSUM-BPNN供热管网泄漏故障分级检测系统。使用现场供回水管道排污阀对泄漏进行模拟,采用该系统对3个换热站及其供热管网分别进行了测试,结果表明,该系统能够准确判断泄漏故障并快速定位泄漏点所在管段,泄漏报警延迟时间在2 min之内,很少出现故障未报或者误报的情况,验证了本文所开发系统的可靠性和高效性。 展开更多
关键词 供热管网 泄漏检测 CUSUM bp神经网络 仿真模型 主成分分析
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基于GA-BP神经网络的储层油气性智能识别与预测研究
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作者 陈晓 林佳金 《计算机应用文摘》 2026年第4期253-255,共3页
针对油田后期勘探阶段地层复杂、储层识别难度大、传统方法依赖经验且准确率低的问题,提出了一种基于遗传算法(GA)优化的神经网络(BP)方法,用于储层油气性识别与物性预测。该方法以测井曲线数据为基础,通过数据预处理、特征筛选、模型... 针对油田后期勘探阶段地层复杂、储层识别难度大、传统方法依赖经验且准确率低的问题,提出了一种基于遗传算法(GA)优化的神经网络(BP)方法,用于储层油气性识别与物性预测。该方法以测井曲线数据为基础,通过数据预处理、特征筛选、模型构建与优化,实现了干层、油层和水层的精准分类,以及孔隙度和渗透率的有效预测。实验结果表明,经过数据均衡化和相关性特征筛选后,GA-BP模型在训练集上的判定系数达0.91,在测试集上的判定系数为0.82,相较于传统BP神经网络,识别准确率提高了18.7%,训练时间缩短了32.4%,为油田的高效勘探开发提供了科学且可靠的技术支撑。 展开更多
关键词 储层识别 GA-bp神经网络 测井曲线 物性预测 智能勘探
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