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Application of CFD and FEA Coupling to Predict Structural Dynamic Responses of A Trimaran in Uni-and Bi-Directional Waves
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作者 LIAO Xi-yu XIA Jin-song +4 位作者 CHEN Zhan-yang TANG Qin ZHAO Nan ZHAO Wei-dong GUI Hong-bin 《China Ocean Engineering》 SCIE EI CSCD 2024年第1期81-92,共12页
To predict the wave loads of a flexible trimaran in different wave fields,a one-way interaction numerical simulation method is proposed by integrating the fluid solver(Star-CCM+)and structural solver(Abaqus).Differing... To predict the wave loads of a flexible trimaran in different wave fields,a one-way interaction numerical simulation method is proposed by integrating the fluid solver(Star-CCM+)and structural solver(Abaqus).Differing from the existing coupled CFD-FEA method for monohull ships in head waves,the presented method equates the mass and stiffness of the whole ship to the hull shell so that any transverse and longitudinal section stress of the hull in oblique waves can be obtained.Firstly,verification study and sensitivity analysis are carried out by comparing the trimaran motions using different mesh sizes and time step schemes.Discussion on the wave elevation of uni-and bi-directional waves is also carried out.Then a comprehensive analysis on the structural responses of the trimaran in different uni-directional regular wave and bi-directional cross sea conditions is carried out,respectively.Finally,the differences in structural response characteristics of trimaran in different wave fields are studied.The results show that the present method can reduce the computational burden of the two-way fluid-structure interaction simulations. 展开更多
关键词 CFD-FEA fluid-structure coupling structural responses TRIMARAN bi-directional cross sea
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A chaotic hierarchical encryption/watermark embedding scheme for multi-medical images based on row-column confusion and closed-loop bi-directional diffusion
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作者 张哲祎 牟俊 +1 位作者 Santo Banerjee 曹颖鸿 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第2期228-237,共10页
Security during remote transmission has been an important concern for researchers in recent years.In this paper,a hierarchical encryption multi-image encryption scheme for people with different security levels is desi... Security during remote transmission has been an important concern for researchers in recent years.In this paper,a hierarchical encryption multi-image encryption scheme for people with different security levels is designed,and a multiimage encryption(MIE)algorithm with row and column confusion and closed-loop bi-directional diffusion is adopted in the paper.While ensuring secure communication of medical image information,people with different security levels have different levels of decryption keys,and differentiated visual effects can be obtained by using the strong sensitivity of chaotic keys.The highest security level can obtain decrypted images without watermarks,and at the same time,patient information and copyright attribution can be verified by obtaining watermark images.The experimental results show that the scheme is sufficiently secure as an MIE scheme with visualized differences and the encryption and decryption efficiency is significantly improved compared to other works. 展开更多
关键词 chaotic hierarchical encryption multi-medical image encryption differentiated visual effects row-column confusion closed-loop bi-directional diffusion transform domain watermark embedding
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基于RF-RNN模型的DNS隐蔽信道检测方法
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作者 冯燕茹 《信息与电脑》 2024年第3期158-160,共3页
为提高检测隐蔽信道的灵敏度,提出一种基于随机森林(Random Forest,RF)和循环神经网络(Recurrent Neural Network,RNN)的域名系统(Domain Name System,DNS)隐蔽信道检测方法。该方法采用域名检测作为主要手段,使用RF模型对域名进行分类... 为提高检测隐蔽信道的灵敏度,提出一种基于随机森林(Random Forest,RF)和循环神经网络(Recurrent Neural Network,RNN)的域名系统(Domain Name System,DNS)隐蔽信道检测方法。该方法采用域名检测作为主要手段,使用RF模型对域名进行分类,通过深度学习方法挖掘更高阶的特征表示。实验结果表明,与单一模型相比,该方法在检测准确性和健壮性方面均取得了显著提升。 展开更多
关键词 域名系统(DNS) 随机森林(RF) 循环神经网络(rnn)
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Text Sentiment Analysis Based on Multi-Layer Bi-Directional LSTM with a Trapezoidal Structure
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作者 Zhengfang He Cristina E.Dumdumaya Ivy Kim D.Machica 《Intelligent Automation & Soft Computing》 SCIE 2023年第7期639-654,共16页
Sentiment analysis,commonly called opinion mining or emotion artificial intelligence(AI),employs biometrics,computational linguistics,nat-ural language processing,and text analysis to systematically identify,extract,m... Sentiment analysis,commonly called opinion mining or emotion artificial intelligence(AI),employs biometrics,computational linguistics,nat-ural language processing,and text analysis to systematically identify,extract,measure,and investigate affective states and subjective data.Sentiment analy-sis algorithms include emotion lexicon,traditional machine learning,and deep learning.In the text sentiment analysis algorithm based on a neural network,multi-layer Bi-directional long short-term memory(LSTM)is widely used,but the parameter amount of this model is too huge.Hence,this paper proposes a Bi-directional LSTM with a trapezoidal structure model.The design of the trapezoidal structure is derived from classic neural networks,such as LeNet-5 and AlexNet.These classic models have trapezoidal-like structures,and these structures have achieved success in the field of deep learning.There are two benefits to using the Bi-directional LSTM with a trapezoidal structure.One is that compared with the single-layer configuration,using the of the multi-layer structure can better extract the high-dimensional features of the text.Another is that using the trapezoidal structure can reduce the model’s parameters.This paper introduces the Bi-directional LSTM with a trapezoidal structure model in detail and uses Stanford sentiment treebank 2(STS-2)for experiments.It can be seen from the experimental results that the trapezoidal structure model and the normal structure model have similar performances.However,the trapezoidal structure model parameters are 35.75%less than the normal structure model. 展开更多
关键词 Text sentiment bi-directional LSTM Trapezoidal structure
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A Modified Bi-Directional Evolutionary Structural Optimization Procedure with Variable Evolutionary Volume Ratio Applied to Multi-Objective Topology Optimization Problem
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作者 Xudong Jiang Jiaqi Ma Xiaoyan Teng 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第4期511-526,共16页
Natural frequency and dynamic stiffness under transient loading are two key performances for structural design related to automotive,aviation and construction industries.This article aims to tackle the multi-objective... Natural frequency and dynamic stiffness under transient loading are two key performances for structural design related to automotive,aviation and construction industries.This article aims to tackle the multi-objective topological optimization problem considering dynamic stiffness and natural frequency using modified version of bi-directional evolutionary structural optimization(BESO).The conventional BESO is provided with constant evolutionary volume ratio(EVR),whereas low EVR greatly retards the optimization process and high EVR improperly removes the efficient elements.To address the issue,the modified BESO with variable EVR is introduced.To compromise the natural frequency and the dynamic stiffness,a weighting scheme of sensitivity numbers is employed to form the Pareto solution space.Several numerical examples demonstrate that the optimal solutions obtained from the modified BESO method have good agreement with those from the classic BESO method.Most importantly,the dynamic removal strategy with the variable EVR sharply springs up the optimization process.Therefore,it is concluded that the modified BESO method with variable EVR can solve structural design problems using multi-objective optimization. 展开更多
关键词 bi-directional evolutionary structural optimization variable evolutionary volume ratio multi-objective optimization weighted sum topology optimization
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Wave propagation responses of porous bi-directional functionally graded magneto-electro-elastic nanoshells via nonlocal strain gradient theory
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作者 Xinte WANG Juan LIU +2 位作者 Biao HU Bo ZHANG Huoming SHEN 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI CSCD 2023年第10期1821-1840,共20页
This study examines the wave propagation characteristics for a bi-directional functional grading of barium titanate(BaTiO_(3)) and cobalt ferrite(CoFe_(2)O_(4)) porous nanoshells,the porosity distribution of which is ... This study examines the wave propagation characteristics for a bi-directional functional grading of barium titanate(BaTiO_(3)) and cobalt ferrite(CoFe_(2)O_(4)) porous nanoshells,the porosity distribution of which is simulated by the honeycomb-shaped symmetrical and asymmetrical distribution functions.The nonlocal strain gradient theory(NSGT) and first-order shear deformation theory are used to determine the size effect and shear deformation,respectively.Nonlocal governing equations are derived for the nanoshells by Hamilton's principle.The resulting dimensionless differential equations are solved by means of an analytical solution of the combined exponential function after dimensionless treatment.Finally,extensive parametric surveys are conducted to investigate the influence of diverse parameters,such as dimensionless scale parameters,radiusto-thickness ratios,bi-directional functionally graded(FG) indices,porosity coefficients,and dimensionless electromagnetic potentials on the wave propagation characteristics.Based on the analysis results,the effect of the dimensionless scale parameters on the dispersion relationship is found to be related to the ratio of the scale parameters.The wave propagation characteristics of nanoshells in the presence of a magnetoelectric field depend on the bi-directional FG indices. 展开更多
关键词 bi-directional functionally graded(FG) wave propagation dimensionless magneto-electro-elastic(MEE)nanoshell nonlocal strain gradient theory(NSGT) porosity
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并行RNN分组策略研究
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作者 易也难 卞艺杰 《智能计算机与应用》 2024年第3期133-139,共7页
并行RNN结构或者分组RNN结构可以显著减少模型中的参数总量,从而有效地降低模型的训练成本并提高训练效率。本文提出一种高效的并行RNN分组策略,该策略不需要对输入数据进行拆分和重组操作,并且可以降低梯度反向传播的不稳定性对于模型... 并行RNN结构或者分组RNN结构可以显著减少模型中的参数总量,从而有效地降低模型的训练成本并提高训练效率。本文提出一种高效的并行RNN分组策略,该策略不需要对输入数据进行拆分和重组操作,并且可以降低梯度反向传播的不稳定性对于模型训练造成的负面影响。在语言建模和命名实体识别的任务中的实验结果表明,本文所提出的并行RNN分组策略,模型的参数计算总量大幅度减少,在2个任务中的表现显著提升。 展开更多
关键词 并行rnn 分组策略 语言建模 命名实体识别
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RNN循环神经网络的服务机器人交互手势辨识
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作者 郑奕捷 李翠玉 郑祖芳 《机械设计与制造》 北大核心 2024年第4期282-285,共4页
服务机器人交互过程中机器人重要关节点难以确定,导致交互手势辨识难以增加,因此设计一种基于RNN循环神经网络的服务机器人交互手势辨识方法。利用Kinect捕获服务机器人交互手势深度图像,确定服务机器人交互过程中的重要关节点,提取服... 服务机器人交互过程中机器人重要关节点难以确定,导致交互手势辨识难以增加,因此设计一种基于RNN循环神经网络的服务机器人交互手势辨识方法。利用Kinect捕获服务机器人交互手势深度图像,确定服务机器人交互过程中的重要关节点,提取服务机器人交互手势特征。根据手势特征提取结果,定义手势模板,采用RNN循环神经网络对手势模板进行学习处理,搭建服务机器人交互手势辨识模型,得到相关的交互手势辨识结果。实验测试结果表明,采用所提方法可以快速获取高精度的服务机器人交互手势辨识结果,实际应用效果好。 展开更多
关键词 rnn循环神经网络 服务机器人 交互手势 辨识
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Enhancing Skin Cancer Diagnosis with Deep Learning:A Hybrid CNN-RNN Approach
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作者 Syeda Shamaila Zareen Guangmin Sun +2 位作者 Mahwish Kundi Syed Furqan Qadri Salman Qadri 《Computers, Materials & Continua》 SCIE EI 2024年第4期1497-1519,共23页
Skin cancer diagnosis is difficult due to lesion presentation variability. Conventionalmethods struggle to manuallyextract features and capture lesions spatial and temporal variations. This study introduces a deep lea... Skin cancer diagnosis is difficult due to lesion presentation variability. Conventionalmethods struggle to manuallyextract features and capture lesions spatial and temporal variations. This study introduces a deep learning-basedConvolutional and Recurrent Neural Network (CNN-RNN) model with a ResNet-50 architecture which usedas the feature extractor to enhance skin cancer classification. Leveraging synergistic spatial feature extractionand temporal sequence learning, the model demonstrates robust performance on a dataset of 9000 skin lesionphotos from nine cancer types. Using pre-trained ResNet-50 for spatial data extraction and Long Short-TermMemory (LSTM) for temporal dependencies, the model achieves a high average recognition accuracy, surpassingprevious methods. The comprehensive evaluation, including accuracy, precision, recall, and F1-score, underscoresthe model’s competence in categorizing skin cancer types. This research contributes a sophisticated model andvaluable guidance for deep learning-based diagnostics, also this model excels in overcoming spatial and temporalcomplexities, offering a sophisticated solution for dermatological diagnostics research. 展开更多
关键词 Skin cancer classification deep learning Convolutional Neural Network(CNN) rnn ResNet-50
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Effects of data smoothing and recurrent neural network(RNN)algorithms for real-time forecasting of tunnel boring machine(TBM)performance
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作者 Feng Shan Xuzhen He +1 位作者 Danial Jahed Armaghani Daichao Sheng 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第5期1538-1551,共14页
Tunnel boring machines(TBMs)have been widely utilised in tunnel construction due to their high efficiency and reliability.Accurately predicting TBM performance can improve project time management,cost control,and risk... Tunnel boring machines(TBMs)have been widely utilised in tunnel construction due to their high efficiency and reliability.Accurately predicting TBM performance can improve project time management,cost control,and risk management.This study aims to use deep learning to develop real-time models for predicting the penetration rate(PR).The models are built using data from the Changsha metro project,and their performances are evaluated using unseen data from the Zhengzhou Metro project.In one-step forecast,the predicted penetration rate follows the trend of the measured penetration rate in both training and testing.The autoregressive integrated moving average(ARIMA)model is compared with the recurrent neural network(RNN)model.The results show that univariate models,which only consider historical penetration rate itself,perform better than multivariate models that take into account multiple geological and operational parameters(GEO and OP).Next,an RNN variant combining time series of penetration rate with the last-step geological and operational parameters is developed,and it performs better than other models.A sensitivity analysis shows that the penetration rate is the most important parameter,while other parameters have a smaller impact on time series forecasting.It is also found that smoothed data are easier to predict with high accuracy.Nevertheless,over-simplified data can lose real characteristics in time series.In conclusion,the RNN variant can accurately predict the next-step penetration rate,and data smoothing is crucial in time series forecasting.This study provides practical guidance for TBM performance forecasting in practical engineering. 展开更多
关键词 Tunnel boring machine(TBM) Penetration rate(PR) Time series forecasting Recurrent neural network(rnn)
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RNN在线学习框架下CNN-LSTM模型对黄金期货价格的预测
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作者 石岩松 杨博 《现代信息科技》 2024年第11期141-144,152,共5页
黄金是一种特殊的金融商品,具有避险功能。黄金期货价格受多方面因素的影响,一般认为黄金期货价格变化趋势呈现非线性非平稳的时间序列,传统的预测模型难以对其进行有效的预测。文章向传统在线学习算法中加入信息传递,提出基于RNN的在... 黄金是一种特殊的金融商品,具有避险功能。黄金期货价格受多方面因素的影响,一般认为黄金期货价格变化趋势呈现非线性非平稳的时间序列,传统的预测模型难以对其进行有效的预测。文章向传统在线学习算法中加入信息传递,提出基于RNN的在线学习算法ROA(RNN-based Online Algorithm);选用芝加哥商品交易所黄金期货价格数据进行实证分析,使用CNN-LSTM作为基础预测模型,以MAE、RMSE、R^(2)作为评价指标,结果表明在所有评价指标中ROA的预测性能均优于传统在线学习算法。 展开更多
关键词 rnn 黄金期货价格 在线学习算法
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基于LSTM-RNN的船舶操纵运动黑箱建模
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作者 田延飞 李知临 +1 位作者 艾万政 韩喜红 《舰船科学技术》 北大核心 2024年第11期80-84,共5页
当无需揭示船舶操纵运动机理过程,而只需对输入输出建立映射时,黑箱建模成为一种有效途径。本文基于长短期记忆-循环神经网络(Long Short-term Memory-recurrent Neural Network,LSTM-RNN)构建船舶航向-舵角黑箱模型,LSTM网络为10-10-1... 当无需揭示船舶操纵运动机理过程,而只需对输入输出建立映射时,黑箱建模成为一种有效途径。本文基于长短期记忆-循环神经网络(Long Short-term Memory-recurrent Neural Network,LSTM-RNN)构建船舶航向-舵角黑箱模型,LSTM网络为10-10-1结构,误差指标为RMSE,参数学习采用Adam算法。开展实船Z型操纵实验获取了航向-舵角数据。前70%用于模型训练,后30%用于模型测试。训练后的模型使得RMSE达到设计目标。对测试集数据,训练后模型拟合优度在0.98以上,表明其具有良好的有效性和泛化性。文中航向-舵角LSTM-RNN黑箱模型结构简明清晰,参数明确,易于实际操作使用,为航向-舵角关系建模提供了一种可行方法。 展开更多
关键词 船舶操纵运动 黑箱建模 机器学习 LSTM-rnn
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基于PyTorch+ARIMA/RNN的时序数据预测方法比较研究
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作者 邓抒江 《电脑编程技巧与维护》 2024年第4期71-73,共3页
随着深度学习的发展,PyTorch作为一个灵活的深度学习框架,被广泛应用于时序预测任务中。研究阐明了PyTorch框架及其在时序预测任务中的应用优势,介绍了基于PyTorch实现ARIMA和循环神经网络(RNN)两种典型时序预测模型的技术路线,从精度... 随着深度学习的发展,PyTorch作为一个灵活的深度学习框架,被广泛应用于时序预测任务中。研究阐明了PyTorch框架及其在时序预测任务中的应用优势,介绍了基于PyTorch实现ARIMA和循环神经网络(RNN)两种典型时序预测模型的技术路线,从精度、效率方面对两种模型进行比较,给出了各自的应用场景及优化方向,为时序预测任务提供了算法选型和实现参考与建议。 展开更多
关键词 时序预测 PyTorch框架 ARIMA模型 rnn模型
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基于改进DBSCAN-RNN的电力负荷建模及可调特征提取 被引量:4
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作者 张露 颜宏文 马瑞 《智慧电力》 北大核心 2023年第3期39-45,共7页
针对面向能源消纳的电力负荷实时调控需求,以电热水器为例建立调控模型,提出一种改进DBSCANRNN算法的电力负荷可调特征提取与可调潜力挖掘方法。以改进DBSCAN聚类结果作为RNN输入获得一种深度学习新策略,基于改进DBSCAN-RNN进行电器群... 针对面向能源消纳的电力负荷实时调控需求,以电热水器为例建立调控模型,提出一种改进DBSCANRNN算法的电力负荷可调特征提取与可调潜力挖掘方法。以改进DBSCAN聚类结果作为RNN输入获得一种深度学习新策略,基于改进DBSCAN-RNN进行电器群设定温度与天气温度、电器负荷功率的建模,考虑用户电器使用习惯,输出输入量对电器实际功率的影响因子以及电器可调功率与真实功率对应的状态方程参数。某市电热水器群实际数据结果表明所提方法可正确有效地获取海量电热水器群聚合负荷模型及其可调功率。 展开更多
关键词 可调潜力挖掘 改进DBSCAN聚类算法 rnn特征提取 负荷特性建模
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一种基于Pred-RNN模型的地震预测方法———以圣安德烈斯断层区域为例
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作者 王雪娇 陈雨 《电子测试》 2023年第4期86-90,共5页
地震预测具有十分重要的现实意义和社会价值。本文提出一种利用时空预测模型的方法来进行地震预测,基于加利福尼亚圣安德烈斯断层区域的地震数据,采用Pred-RNN模型预测未来地震事件的区域、震级和趋势。实验表明,Pred-RNN模型在MSE、SSI... 地震预测具有十分重要的现实意义和社会价值。本文提出一种利用时空预测模型的方法来进行地震预测,基于加利福尼亚圣安德烈斯断层区域的地震数据,采用Pred-RNN模型预测未来地震事件的区域、震级和趋势。实验表明,Pred-RNN模型在MSE、SSIM等评价指标上都具有很好的表现。分析结果表明,本文提出的方法在强化地震预测方面具有显著潜力,为地震预测研究提供了新思路。 展开更多
关键词 地震预测 Pred-rnn 圣安德烈斯断层 时空预测
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Multi-agent system application in accordance with game theory in bi-directional coordination network model 被引量:3
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作者 ZHANG Jie WANG Gang +3 位作者 YUE Shaohua SONG Yafei LIU Jiayi YAO Xiaoqiang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2020年第2期279-289,共11页
The multi-agent system is the optimal solution to complex intelligent problems. In accordance with the game theory, the concept of loyalty is introduced to analyze the relationship between agents' individual incom... The multi-agent system is the optimal solution to complex intelligent problems. In accordance with the game theory, the concept of loyalty is introduced to analyze the relationship between agents' individual income and global benefits and build the logical architecture of the multi-agent system. Besides, to verify the feasibility of the method, the cyclic neural network is optimized, the bi-directional coordination network is built as the training network for deep learning, and specific training scenes are simulated as the training background. After a certain number of training iterations, the model can learn simple strategies autonomously. Also,as the training time increases, the complexity of learning strategies rises gradually. Strategies such as obstacle avoidance, firepower distribution and collaborative cover are adopted to demonstrate the achievability of the model. The model is verified to be realizable by the examples of obstacle avoidance, fire distribution and cooperative cover. Under the same resource background, the model exhibits better convergence than other deep learning training networks, and it is not easy to fall into the local endless loop.Furthermore, the ability of the learning strategy is stronger than that of the training model based on rules, which is of great practical values. 展开更多
关键词 LOYALTY GAME THEORY bi-directional COORDINATION network MULTI-AGENT system learning strategy
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Experimental Investigation of Local Scour Around A New Pile-Group Foundation for Offshore Wind Turbines in Bi-Directional Current 被引量:4
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作者 JI Chao ZHANG Jin-feng +2 位作者 ZHANG Qing-he LI Ming-xing CHEN Tong-qing 《China Ocean Engineering》 SCIE EI CSCD 2018年第6期737-745,共9页
The local scour around a new pile-group foundation of offshore wind turbine subjected to a bi-directional current was physically modeled with a bi-directional flow flume. In a series of experiments, the flow velocity ... The local scour around a new pile-group foundation of offshore wind turbine subjected to a bi-directional current was physically modeled with a bi-directional flow flume. In a series of experiments, the flow velocity and topography of the seabed were measured based on a system composed of plane positioning equipment and an ADV.Experimental results indicate that the development of the scour hole was fast at the beginning, but then the scour rate decreased until reaching equilibrium. Erosion would occur around each pile of the foundation. In most cases, the scour pits were connected in pairs and the outside widths of the scour holes were larger than the inner widths. The maximum scour depth occurred at the side pile of the foundation for each test. In addition, a preliminary investigation shows that the larger the flow velocity, the larger the scour hole dimensions but the shorter equilibrium time. The field maximum scour depth around the foundation was obtained based on the physical experiments with the geometric length scales of 1:27.0, 1:42.5 and 1:68.0, and it agrees with the scour depth estimated by the HEC-18 equation. 展开更多
关键词 offshore wind turbines new pile-group foundation local scour bi-directional current
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Construction and analysis of a plant transformation binary vector pBDGG harboring a bi-directional promoter fusing dual visible reporter genes 被引量:3
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作者 Chunxiao Zhang Ying Gai +3 位作者 Wenqi Wang Yanyan Zhu Xuemei Chen Xiangning Jiang 《Journal of Genetics and Genomics》 SCIE CAS CSCD 北大核心 2008年第4期245-249,共5页
The constitutive promoter of cauliflower mosaic virus 35S (CaMV 35S) is a polar unidirectional promoter and is widely used in plant genetic engineering. In the present study, the unidirectional CaMV 35S promoter has... The constitutive promoter of cauliflower mosaic virus 35S (CaMV 35S) is a polar unidirectional promoter and is widely used in plant genetic engineering. In the present study, the unidirectional CaMV 35S promoter has been modified to a bi-directional promoter by fusing its minimal promoter element to the 5' end of CaMV 35S promoter in the opposite orientation. To qualitatively and quantitatively estimate its bi-directional transcriptional function and activity, two visible reporter genes, gusA (13-glucuronidase, GUS) and gfp (green fluorescent protein, GFP), were fused to the two ends of the promoter in bi-orientations ending with NOS terminator sequences, respectively. Stable expression of gusA and gfp genes in transgenic tobacco (Nicotiana tabacum L.) was visulized by histochemically staining for GUS and fluorescence microscopic observation under UV for GFP in transgenic plants. The expression of two reporter genes showed that the constructed bi-directional promoter did have the bi-directional transcriptional function in both expected orientations. The quantitative estimation of GUS and GFP were determined on a HITACHI F1000 Fluorescence Spectrophotometer with various wavelengths of excitation and emission. The GUS activity varied from g to 250 pmol 4-MU/min/mg protein and the GFP content varied from 0.9 to 1.8 μg/ mg protein in various lines of transgenic tobacco plants. Higher GUS activity generally coupled with lower GFP content, and vice versa. 展开更多
关键词 bi-directional promoter gusA gene gfp gene Nicotiana tabacum L. expression
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Quantitative measurements of one-dimensional OH absolute concentration profiles in a methane/air flat flame by bi-directional laser-induced fluorescence 被引量:3
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作者 于欣 杨振 +5 位作者 彭江波 张蕾 马欲飞 杨超博 李晓晖 孙锐 《Chinese Physics B》 SCIE EI CAS CSCD 2015年第11期270-279,共10页
The one-dimensional (1D) spatial distributions of OH absolute concentration in methane/air laminar premixed flat flame under different equivalence ratios at atmospheric pressure are investigated by using bi-directio... The one-dimensional (1D) spatial distributions of OH absolute concentration in methane/air laminar premixed flat flame under different equivalence ratios at atmospheric pressure are investigated by using bi-directional laser-induced flu- orescence (LIF) detection scheme combined with the direct absorption spectroscopy. The effective peak absorption cross section and the average temperature at a height of 2 mm above the burner are obtained by exciting absorption on the Q1(8) rotational line in the A2∑+ (Dt = 0) ←- X2∏ (v = 0) at 309.240 nm. The measured values are 1.86×10-15 cm2 and 1719 K, respectively. Spatial filtering and frequency filtering methods of reducing noise are used to deal with the experi- mental data, and the smoothing effects are also compared using the two methods. The spatial distribution regularities of OH concentration are obtained with the equivalence ratios ranging from 0.8 to 1.3. The spatial resolution of the measured result is 84μm. Finally, a comparison is made between the experimental result of this paper and other relevant study results. 展开更多
关键词 bi-directional laser-induced fluorescence laminar premixed flat flame hydroxyl radical absoluteconcentration
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Application of bi-directional static loading test to deep foundations 被引量:4
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作者 Guoliang Dai Weiming Gong 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE 2012年第3期269-275,共7页
Bi-directional static loading test adopting load cells is widely used around the world at present, with increase in diameter and length of deep foundations. In this paper, a new simple conversion method to predict the... Bi-directional static loading test adopting load cells is widely used around the world at present, with increase in diameter and length of deep foundations. In this paper, a new simple conversion method to predict the equivalent pile head load-settlement curve considering elastic shortening of deep foundation was put forward according to the load transfer mechanism. The proposed conversion method was applied to root caisson foundation in a bridge and to large diameter pipe piles in a sea wind power plant. Some new load cells, test procedure, and construction technology were adopted based on the applications to different deep foundations, which could enlarge the application scopes of bi-directional loading test. A new type of bi-directional loading test for pipe pile was conducted, in which the load cell was installed and loaded after the pipe pile with special connector has been set up. Unlike the conventional bi-directional loading test, the load cell can be reused and shows an evident economic benefit. 展开更多
关键词 deep foundations bi-directional static loading test root caisson foundation large diameter pipe pile
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