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Underwater Image Classification Based on EfficientnetB0 and Two-Hidden-Layer Random Vector Functional Link
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作者 ZHOU Zhiyu LIU Mingxuan +2 位作者 JI Haodong WANG Yaming ZHU Zefei 《Journal of Ocean University of China》 CAS CSCD 2024年第2期392-404,共13页
The ocean plays an important role in maintaining the equilibrium of Earth’s ecology and providing humans access to a wealth of resources.To obtain a high-precision underwater image classification model,we propose a c... The ocean plays an important role in maintaining the equilibrium of Earth’s ecology and providing humans access to a wealth of resources.To obtain a high-precision underwater image classification model,we propose a classification model that combines an EfficientnetB0 neural network and a two-hidden-layer random vector functional link network(EfficientnetB0-TRVFL).The features of underwater images were extracted using the EfficientnetB0 neural network pretrained via ImageNet,and a new fully connected layer was trained on the underwater image dataset using the transfer learning method.Transfer learning ensures the initial performance of the network and helps in the development of a high-precision classification model.Subsequently,a TRVFL was proposed to improve the classification property of the model.Net construction of the two hidden layers exhibited a high accuracy when the same hidden layer nodes were used.The parameters of the second hidden layer were obtained using a novel calculation method,which reduced the outcome error to improve the performance instability caused by the random generation of parameters of RVFL.Finally,the TRVFL classifier was used to classify features and obtain classification results.The proposed EfficientnetB0-TRVFL classification model achieved 87.28%,74.06%,and 99.59%accuracy on the MLC2008,MLC2009,and Fish-gres datasets,respectively.The best convolutional neural networks and existing methods were stacked up through box plots and Kolmogorov-Smirnov tests,respectively.The increases imply improved systematization properties in underwater image classification tasks.The image classification model offers important performance advantages and better stability compared with existing methods. 展开更多
关键词 underwater image classification EfficientnetB0 random vector functional link convolutional neural network
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Fully Distributed Learning for Deep Random Vector Functional-Link Networks
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作者 Huada Zhu Wu Ai 《Journal of Applied Mathematics and Physics》 2024年第4期1247-1262,共16页
In the contemporary era, the proliferation of information technology has led to an unprecedented surge in data generation, with this data being dispersed across a multitude of mobile devices. Facing these situations a... In the contemporary era, the proliferation of information technology has led to an unprecedented surge in data generation, with this data being dispersed across a multitude of mobile devices. Facing these situations and the training of deep learning model that needs great computing power support, the distributed algorithm that can carry out multi-party joint modeling has attracted everyone’s attention. The distributed training mode relieves the huge pressure of centralized model on computer computing power and communication. However, most distributed algorithms currently work in a master-slave mode, often including a central server for coordination, which to some extent will cause communication pressure, data leakage, privacy violations and other issues. To solve these problems, a decentralized fully distributed algorithm based on deep random weight neural network is proposed. The algorithm decomposes the original objective function into several sub-problems under consistency constraints, combines the decentralized average consensus (DAC) and alternating direction method of multipliers (ADMM), and achieves the goal of joint modeling and training through local calculation and communication of each node. Finally, we compare the proposed decentralized algorithm with several centralized deep neural networks with random weights, and experimental results demonstrate the effectiveness of the proposed algorithm. 展开更多
关键词 Distributed Optimization Deep Neural Network Random Vector functional-link (RVFL) Network Alternating Direction Method of Multipliers (ADMM)
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ADAPTIVE PREDICTIVE CONTROL OF NEAR-SPACE VEHICLE USING FUNCTIONAL LINK NETWORK 被引量:3
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作者 都延丽 吴庆宪 姜长生 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2010年第2期148-154,共7页
A novel nonlinear adaptive control method is presented for a near-space hypersonic vehicle (NHV) in the presence of strong uncertainties and disturbances. The control law consists of the optimal generalized predicti... A novel nonlinear adaptive control method is presented for a near-space hypersonic vehicle (NHV) in the presence of strong uncertainties and disturbances. The control law consists of the optimal generalized predictive controller (OGPC) and the functional link network (FLN) direct adaptive law. OGPC is a continuous-time nonlinear predictive control law. The FLN adaptive law is used to offset the unknown uncertainties and disturbances in a flight through the online learning. The learning process does not need any offline training phase. The stability analyses of the NHV close-loop system are provided and it is proved that the system error and the weight learning error are uniformly ultimately hounded. Simulation results show the satisfactory performance of the con- troller for the attitude tracking. 展开更多
关键词 predictive control systems adaptive control systems UNCERTAINTY functional link network near-space vehicle
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Adaptive functional link network control of near-space vehicles with dynamical uncertainties 被引量:5
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作者 Yanli Du Qingxian Wu Changsheng Jiang Jie Wen 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2010年第5期868-876,共9页
The control law design for a near-space hypersonic vehicle(NHV) is highly challenging due to its inherent nonlinearity,plant uncertainties and sensitivity to disturbances.This paper presents a novel functional link ... The control law design for a near-space hypersonic vehicle(NHV) is highly challenging due to its inherent nonlinearity,plant uncertainties and sensitivity to disturbances.This paper presents a novel functional link network(FLN) control method for an NHV with dynamical thrust and parameter uncertainties.The approach devises a new partially-feedback-functional-link-network(PFFLN) adaptive law and combines it with the nonlinear generalized predictive control(NGPC) algorithm.The PFFLN is employed for approximating uncertainties in flight.Its weights are online tuned based on Lyapunov stability theorem for the first time.The learning process does not need any offline training phase.Additionally,a robust controller with an adaptive gain is designed to offset the approximation error.Finally,simulation results show a satisfactory performance for the NHV attitude tracking,and also illustrate the controller's robustness. 展开更多
关键词 adaptive control system dynamical uncertainties partially feedback functional link network near-space vehicle.
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Optimized functional linked neural network for predicting diaphragm wall deflection induced by braced excavations in clays 被引量:4
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作者 Chengyu Xie Hoang Nguyen +1 位作者 Yosoon Choi Danial Jahed Armaghani 《Geoscience Frontiers》 SCIE CAS CSCD 2022年第2期34-51,共18页
Deep excavation during the construction of underground systems can cause movement on the ground,especially in soft clay layers.At high levels,excessive ground movements can lead to severe damage to adjacent structures... Deep excavation during the construction of underground systems can cause movement on the ground,especially in soft clay layers.At high levels,excessive ground movements can lead to severe damage to adjacent structures.In this study,finite element analyses(FEM)and the hardening small strain(HSS)model were performed to investigate the deflection of the diaphragm wall in the soft clay layer induced by braced excavations.Different geometric and mechanical properties of the wall were investigated to study the deflection behavior of the wall in soft clays.Accordingly,1090 hypothetical cases were surveyed and simulated based on the HSS model and FEM to evaluate the wall deflection behavior.The results were then used to develop an intelligent model for predicting wall deflection using the functional linked neural network(FLNN)with different functional expansions and activation functions.Although the FLNN is a novel approach to predict wall deflection;however,in order to improve the accuracy of the FLNN model in predicting wall deflection,three swarm-based optimization algorithms,such as artificial bee colony(ABC),Harris’s hawk’s optimization(HHO),and hunger games search(HGS),were hybridized to the FLNN model to generate three novel intelligent models,namely ABC-FLNN,HHO-FLNN,HGS-FLNN.The results of the hybrid models were then compared with the basic FLNN and MLP models.They revealed that FLNN is a good solution for predicting wall deflection,and the application of different functional expansions and activation functions has a significant effect on the outcome predictions of the wall deflection.It is remarkably interesting that the performance of the FLNN model was better than the MLP model with a mean absolute error(MAE)of 19.971,root-mean-squared error(RMSE)of 24.574,and determination coefficient(R^(2))of 0.878.Meanwhile,the performance of the MLP model only obtained an MAE of 20.321,RMSE of 27.091,and R^(2)of 0.851.Furthermore,the results also indicated that the proposed hybrid models,i.e.,ABC-FLNN,HHO-FLNN,HGS-FLNN,yielded more superior performances than those of the FLNN and MLP models in terms of the prediction of deflection behavior of diaphragm walls with an MAE in the range of 11.877 to 12.239,RMSE in the range of 15.821 to 16.045,and R^(2)in the range of 0.949 to 0.951.They can be used as an alternative tool to simulate diaphragm wall deflections under different conditions with a high degree of accuracy. 展开更多
关键词 Diaphragm wall deflection Braced excavation Finite element analysis Clays Meta-heuristic algorithms functional linked neural network
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Functional Link Neural Network for Predicting Crystallization Temperature of Ammonium Chloride in Air Cooler System 被引量:3
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作者 Jin Haozhe Gu Yong +3 位作者 Ren Jia Wu Xiangyao Quan Jianxun Xu Linfengyi 《China Petroleum Processing & Petrochemical Technology》 SCIE CAS 2020年第2期86-92,共7页
The air cooler is an important equipment in the petroleum refining industry.Ammonium chloride(NH4 Cl)deposition-induced corrosion is one of its main failure forms.In this study,the ammonium salt crystallization temper... The air cooler is an important equipment in the petroleum refining industry.Ammonium chloride(NH4 Cl)deposition-induced corrosion is one of its main failure forms.In this study,the ammonium salt crystallization temperature is chosen as the key decision variable of NH4 Cl deposition-induced corrosion through in-depth mechanism research and experimental analysis.The functional link neural network(FLNN)is adopted as the basic algorithm for modeling because of its advantages in dealing with non-linear problems and its fast-computational ability.A hybrid FLNN attached to a small norm is built to improve the generalization performance of the model.Then,the trained model is used to predict the NH4 Cl salt crystallization temperature in the air cooler of a sour water stripper plant.Experimental results show the proposed improved FLNN algorithm can achieve better generalization performance than the PLS,the back propagation neural network,and the conventional FLNN models. 展开更多
关键词 air cooler NH4Cl salt crystallization temperature DATA-DRIVEN functional link neural network particle swarm optimization
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AN APPROACH TO THEORETICAL FUNCTION OF DISLOCATION LINK LENGTH DISTRIBUTION IN METAL
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作者 WANG Bosheng SUN Fuyu MENG Qing’ en XU Wenchong Central Iron and steel Research Institute,Ministry of Metallurgical Industry,Beijing,China 《Acta Metallurgica Sinica(English Letters)》 SCIE EI CAS CSCD 1992年第5期314-317,共4页
A statistical distribution function of the dislocation link length,in unit volume of the crystalline materials has been derived theoretically after semi-infinite normalization by as- suming the distribution of actual ... A statistical distribution function of the dislocation link length,in unit volume of the crystalline materials has been derived theoretically after semi-infinite normalization by as- suming the distribution of actual links in all positions of crystalline materials with equal prob- ability,i.e. (l)dl=2ρl_γ^(-4)l^2exp(l^2/l_γ~2)dl where ρ is dislocation density,This assumption seems to be reasonable for polycrystalline fec metallic materials,and confirmation has been found in pure Ni and stainless steel 1Cr18Ni9Ti TEM experiments alresults. 展开更多
关键词 dislocation link length distribution function crystal defect
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微惯性环节介入法与同阶闭环系统的稳定性
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作者 朱明 郁镓瑄 朱嘉慧 《电气自动化》 2024年第4期24-28,共5页
奈奎斯特判据是经典控制理论中最为重要的稳定性判据,但并不适用于同阶闭环系统。同时由于基本环节样式不全、开环传递函数含义易误解且使用不便,导致初学者对自控原理学习和理解的困扰。为此对频域法的一些概念和表达方式进行了梳理,... 奈奎斯特判据是经典控制理论中最为重要的稳定性判据,但并不适用于同阶闭环系统。同时由于基本环节样式不全、开环传递函数含义易误解且使用不便,导致初学者对自控原理学习和理解的困扰。为此对频域法的一些概念和表达方式进行了梳理,对基本环节和控制系统进行了完整的分类,提出环路传递函数概念解决了开环传递函数含义易误解和使用不便的问题,提出微惯性环节介入法解决了同阶闭环系统稳定性判断的问题,环路传递函数、微惯性环节介入法、巨惯性环节与微阻尼振荡环节替代等方法大大地简化了系统特性的分析,从而完善了频域分析法及其知识体系。 展开更多
关键词 基本环节 环路传递函数 微惯性环节 巨惯性环节 微阻尼振荡环节
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全链路数字化转型过程中的组织惯性克服机制
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作者 苏敬勤 武宪云 《技术经济》 CSSCI 北大核心 2024年第8期74-84,共11页
数字经济时代,涵盖全场域的全链路数字化转型往往面临更广范围的历史束缚,使得传统企业深陷历史惯性囹圄,克服组织惯性成为传统企业实现数字化发展的首要任务。本文对飞鹤乳业的数字化转型实践过程进行探索性案例分析,探究传统企业全链... 数字经济时代,涵盖全场域的全链路数字化转型往往面临更广范围的历史束缚,使得传统企业深陷历史惯性囹圄,克服组织惯性成为传统企业实现数字化发展的首要任务。本文对飞鹤乳业的数字化转型实践过程进行探索性案例分析,探究传统企业全链路数字化转型过程中面临的组织惯性及其克服机制。研究发现:全链路数字化转型过程中,(1)组织惯性显现范围被扩大,企业面临跨功能认知惯性与跨功能结构惯性的变革阻力;(2)传统企业通过由外而内的资源编排方式来克服跨功能组织惯性阻力,且不同类别跨功能组织惯性克服的内在机理存在异质性。对于跨功能认知惯性克服,企业采用“外源型结构化-传承型能力化-置换型杠杆化”的资源编排策略;对于跨功能结构惯性克服,企业采用“外源型结构化-开拓型能力化-组合型杠杆化”的资源编排策略。本文不仅扩展了数字化转型情境下组织惯性的相关理论,还为传统企业成功推进数字化转型提供了实践指引。 展开更多
关键词 全链路数字化转型 跨功能组织惯性 资源编排 克服机制 案例研究
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阿尔茨海默病的多层脑网络链路预测重构
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作者 曹春萍 俞璎时 《小型微型计算机系统》 CSCD 北大核心 2024年第2期483-489,共7页
功能脑网络的构建工作是阿尔茨海默病辅助诊断中的基础任务.针对基于全频域的单层网络构建方法难以处理小频段间的异质性特征以及脑网络中可能存在错误边或缺失边的问题,提出一种基于多层网络链路预测的功能脑网络模型.利用多层网络框... 功能脑网络的构建工作是阿尔茨海默病辅助诊断中的基础任务.针对基于全频域的单层网络构建方法难以处理小频段间的异质性特征以及脑网络中可能存在错误边或缺失边的问题,提出一种基于多层网络链路预测的功能脑网络模型.利用多层网络框架使节点间存在多个频段描述下的连接关系,并设计融合层间相似性和节点重要性的局部相似性指标,进而基于多层网络拓扑结构进行链路预测,以重构网络结构.实验结果表明,与当前先进的脑网络模型相比,该模型在阿尔茨海默病分类诊断中性能表现更好,证明所提模型能有效提升网络表达的精准性,且在计算机辅助诊断中具有良好的应用价值. 展开更多
关键词 多层网络 链路预测 层间相似性 节点重要性 功能脑网络
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含有调速器多死区环节的风水火系统频率稳定分析
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作者 周子超 吴水军 +4 位作者 束洪春 孙士云 冯海洋 邓涵 徐韬 《电力系统保护与控制》 EI CSCD 北大核心 2024年第5期1-11,共11页
“双高”背景下新型电力系统面临着非线性机理复杂的稳定问题,传统机组调速器与风电控制器中死区非线性组合间的相互作用,在一定程度上影响了系统的频率稳定性。为此,在奈氏定理的基础上探究不同死区非线性组合下系统频率振荡的影响规律... “双高”背景下新型电力系统面临着非线性机理复杂的稳定问题,传统机组调速器与风电控制器中死区非线性组合间的相互作用,在一定程度上影响了系统的频率稳定性。为此,在奈氏定理的基础上探究不同死区非线性组合下系统频率振荡的影响规律,主要针对死区类型、死区大小和死区顺序3个方面进行研究,涉及单死区系统和多死区系统。理论分析了其非线性系统的稳定性,并根据稳定极限环条件求解系统的临界振幅和振荡频率。通过改变死区类型及顺序,影响机组对系统频率的支撑能力,指出了系统频率稳定与临界振幅的关系,并在Matlab/Simulink中对上述理论分析进行了仿真验证。结果表明机组死区大小和类型均会改变系统的临界振幅和振荡频率,为机组配置死区提供了一定的参考依据。 展开更多
关键词 频率稳定 多死区环节 非线性环节 调速器 扩展描述函数
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NNN-链接护理模式联合双重任务训练对脑卒中患者的认知功能与护理结局的影响
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作者 黄远梅 巫国庆 +2 位作者 陈陪能 黄雪娟 陈苗 《中国医学创新》 CAS 2024年第14期73-77,共5页
目的:探究NNN-链接护理模式联合双重任务训练应用于脑卒中患者的效果。方法:选取2022年1—12月于第九〇九医院(厦门大学附属东南医院)就诊的脑卒中患者100例,按照随机数字表法分为对照组和观察组,各50例。对照组予以双重任务训练干预模... 目的:探究NNN-链接护理模式联合双重任务训练应用于脑卒中患者的效果。方法:选取2022年1—12月于第九〇九医院(厦门大学附属东南医院)就诊的脑卒中患者100例,按照随机数字表法分为对照组和观察组,各50例。对照组予以双重任务训练干预模式,观察组在对照组的基础上联合NNN-链接护理模式进行干预。观察两组口面部运动功能、认知功能、平衡功能、日常生活活动能力、吞咽功能改善效果及护理结局。结果:干预后,观察组北欧口腔颜面功能检查-筛查(NOT-S)评分明显低于对照组,简易智力状况检查(MMSE)、Berg平衡量表(BBS)及改良巴塞尔指数均明显高于对照组,差异均有统计学意义(P<0.05)。观察组总有效率(90.00%)显著高于对照组(74.00%),差异有统计学意义(P<0.05)。随访结束后,观察组功能健康、健康知识与行为、生理健康、心理社会健康及家庭健康的护理结局评分均明显高于对照组,差异均有统计学意义(P<0.05)。结论:NNN-链接护理模式联合双重任务训练应用于脑卒中患者,可明显改善患者的口面部运动功能、认知功能及平衡功能,增强患者的日常生活活动能力,改善患者的吞咽功能和护理结局。 展开更多
关键词 脑卒中 双重任务训练 NNN-链接护理模式 吞咽功能 护理结局
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VHF机载电台ACARS功能激活方法的研究 被引量:2
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作者 岳猛 洪雪婷 +1 位作者 蒋一阳 郑瀚 《中国民航大学学报》 CAS 2024年第1期16-23,共8页
飞机通信寻址与报告系统(ACARS,aircraft communication addressing and reporting system)是目前世界范围内使用最广泛的空地数据链通信系统。以激活真实航材的ACARS功能为目的,选择典型的甚高频(VHF,very high frequency)机载电台柯林... 飞机通信寻址与报告系统(ACARS,aircraft communication addressing and reporting system)是目前世界范围内使用最广泛的空地数据链通信系统。以激活真实航材的ACARS功能为目的,选择典型的甚高频(VHF,very high frequency)机载电台柯林斯VHF-2100型,从接口规范、数据交互时序关系和电气连接特性3个方面进行研究,设计了ACARS功能的激活方法。通过实验平台的验证,测试结果表明:所设计的方法能够对VHF-2100机载电台进行配置,并能使其收发ACARS报文。真实航材的激活验证了接口控制的可行性,对ACARS机载电台的国产化有一定的借鉴意义。 展开更多
关键词 飞机通信寻址报告系统 数据链 机载电台 功能激活
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采用改进FRAM模型方法的管道爆裂事故分析
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作者 栗婧 柳慧妍 +2 位作者 宫梓超 秦永莹 蔡忠杰 《安全与环境学报》 CAS CSCD 北大核心 2024年第4期1460-1468,共9页
近年来,主蒸汽管道爆管事故频发,为了找出管道爆裂事故的致因路径,有效预防和控制此类事故发生,以某重大蒸汽管道裂爆事故为例,采用时间和事件序列图(Sequentially Timed Events Plotting,STEP)技术和蒙特卡罗模拟方法对功能共振分析法(... 近年来,主蒸汽管道爆管事故频发,为了找出管道爆裂事故的致因路径,有效预防和控制此类事故发生,以某重大蒸汽管道裂爆事故为例,采用时间和事件序列图(Sequentially Timed Events Plotting,STEP)技术和蒙特卡罗模拟方法对功能共振分析法(Functional Resonance Analysis Method,FRAM)进行改进,进行事故致因分析并建立屏障措施。结果表明,改进后的FRAM模型可以全面识别功能信息并且定量确定FRAM模型中各功能的变化及耦合关系,减少功能性能变化及潜在耦合变化分析的主观性,找出系统发生共振的功能及失效连接。最后,根据失效连接制定相应屏障措施来预防此类事故的发生。 展开更多
关键词 安全工程 管道爆裂事故 功能共振分析法(FRAM) 事故分析 失效连接
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谷氨酰胺转氨酶介导的荞麦蛋白-花生蛋白交联及其功能特性研究
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作者 陈方圆 金建 蓝许诺 《中国粮油学报》 CAS CSCD 北大核心 2024年第2期104-112,共9页
以谷氨酰胺转氨酶(TGase)为交联酶制剂,对荞麦蛋白与花生蛋白进行交联,通过单因素实验对2种蛋白的比例、总蛋白质质量浓度、TG酶添加量、交联温度、交联时间和pH进行了参数优化,并研究了最佳交联工艺条件下制备得到的交联产物的功能特... 以谷氨酰胺转氨酶(TGase)为交联酶制剂,对荞麦蛋白与花生蛋白进行交联,通过单因素实验对2种蛋白的比例、总蛋白质质量浓度、TG酶添加量、交联温度、交联时间和pH进行了参数优化,并研究了最佳交联工艺条件下制备得到的交联产物的功能特性。结果表明,荞麦蛋白与花生蛋白的质量比1∶1、总蛋白质量浓度4 g/100 mL、酶质量分数1.25%、反应温度40℃、反应时间120 min、pH 8.0时的交联反应效果最佳,交联度为63.1%。功能特性测定结果表明,与未交联的蛋白质相比,交联后的蛋白质的持水性、持油性和乳化稳定性有所提高,但乳化性、起泡性和起泡稳定性降低;在pH 3~12范围,交联蛋白质的溶解度逐渐升高,尤其在pI 4.0处,溶解度提高最为显著。 展开更多
关键词 谷氨酰胺转氨酶 蛋白质交联 功能特性 荞麦蛋白 花生蛋白
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特征扩展的随机向量函数链神经网络
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作者 龙茂森 王士同 《软件学报》 EI CSCD 北大核心 2024年第6期2903-2922,共20页
基于宽度学习的动态模糊推理系统(broad-learning-based dynamic fuzzy inference system,BL-DFIS)能自动构建出精简的模糊规则并获得良好的分类性能.然而,当遇到大型复杂的数据集时,BL-DFIS因会使用较多模糊规则来试图达到令人满意的... 基于宽度学习的动态模糊推理系统(broad-learning-based dynamic fuzzy inference system,BL-DFIS)能自动构建出精简的模糊规则并获得良好的分类性能.然而,当遇到大型复杂的数据集时,BL-DFIS因会使用较多模糊规则来试图达到令人满意的识别精度,从而对其可解释性造成了不利影响.对此,提出一种兼顾分类性能和可解释性的模糊神经网络,将其称为特征扩展的随机向量函数链神经网络(FA-RVFLNN).在该网络中,一个以原始数据为输入的RVFLNN被作为主体结构,BL-DFIS则用作性能补充,这意味着FA-RVFLNN包含具有性能增强作用的直接链接.由于主体结构的增强节点使用Sigmoid激活函数,因此,其推理过程可借助一种模糊逻辑算子(I-OR)来解释.而且,具有明确含义的原始输入数据也有助于解释主体结构的推理规则.在直接链接的支撑下,FA-RVFLNN可利用增强节点、特征节点和模糊节点学到更丰富的有用信息.实验表明:FA-RVFLNN既减缓了主体结构RVFLNN中过多增强节点带来的“规则爆炸”问题,也提高了性能补充结构BL-DFIS的可解释性(平均模糊规则数降低了50%左右),在泛化性能和网络规模上仍具有竞争力. 展开更多
关键词 宽度学习系统 模糊推理系统 特征扩展 随机向量函数链神经网络(RVFLNN) Sigmoid激活函数 可解释
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头针结合E-LINK上肢评估训练系统对脑卒中偏瘫患者手功能疗效观察 被引量:2
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作者 张裴景 毛光兰 +3 位作者 郭青川 郭健 张铭 白艳杰 《中国中医药现代远程教育》 2015年第18期84-86,共3页
目的探索中国传统康复治疗方法头针结合E-LINK上肢评估训练系统在脑卒中偏瘫患者康复中手功能的疗效。方法将60例脑卒中偏瘫患者随机分为治疗组和对照组进行研究。在治疗过程中,治疗组采用头针结合E-LINK上肢评估训练系统进行手功能训练... 目的探索中国传统康复治疗方法头针结合E-LINK上肢评估训练系统在脑卒中偏瘫患者康复中手功能的疗效。方法将60例脑卒中偏瘫患者随机分为治疗组和对照组进行研究。在治疗过程中,治疗组采用头针结合E-LINK上肢评估训练系统进行手功能训练,对照组只运用E-LINK上肢评估训练系统进行手功能训练,两组治疗前后均采用Fugl-Meyer运动量表评估患侧上肢及手的运动功能,采用表面肌电信号(s EMG)评估肱二头肌、肱三头肌、旋前圆肌及的肌力。结果治疗组与对照组治疗前后肱二头肌、肱三头肌、旋前圆肌的肌力均无显著性差异(P>0.05),治疗组与对照组治疗前后上肢及手功能的运动功能及表面肌电图评估均有显著性差异(P<0.05)。结论头针结合E-LINK上肢评估训练系统的康复治疗方法对脑卒中偏瘫患者康复优于只进行E-LINK上肢评估训练系统单一的训练方法。 展开更多
关键词 头针 E-link上肢评估训练系统 卒中 偏瘫 手功能
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E-LINK手功能评定训练系统结合蒙医放血疗法对腕管综合征术后早期康复干预 被引量:3
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作者 薛慧琴 《中国民族医药杂志》 2016年第10期10-12,共3页
目的:观察E-LINK手功能评定训练系统结合蒙医放血疗法对腕管综合征术后早期康复干预的疗效。方法:选取58例腕管综合征术后的患者,其中29例采用E-LINK手功能评定训练系统结合蒙医放血疗法,29例患者进行常规的综合康复训练,治疗前后采用... 目的:观察E-LINK手功能评定训练系统结合蒙医放血疗法对腕管综合征术后早期康复干预的疗效。方法:选取58例腕管综合征术后的患者,其中29例采用E-LINK手功能评定训练系统结合蒙医放血疗法,29例患者进行常规的综合康复训练,治疗前后采用腕关节功能评分Cooney腕关节评分(改良Green和O’Brien腕关节评分);日常生活能力评分(ADL)方法观察各组患者治疗效果并进行比较。结果:治疗后,患者ADL评分均较治疗前有所提升,改良Green和O’Brien腕关节评分均较治疗前明显改善,与治疗前比较,差异有统计学意义(P<0.05);治疗后治疗组优4例,良15例,优良率为73.08%,对照组优3例,良6例,优良率为40.91%。两组比较差异有统计学意义(P<0.05),治疗组疗效优于对照组。结论:E-LINK手功能训练系统结合蒙医放血疗法对腕管综合征术后早期康复的疗效优于早期的常规康复治疗;并且在康复治疗时患者的易接受性、趣味性、积极性优于常规的康复治疗;蒙医放血疗法可以运用于腕管综合征术后的康复治疗。 展开更多
关键词 E-link手功能评定 蒙医放血疗法 腕管综合征术 早期康复干预
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奇异值分解下在线鲁棒正则化随机网络
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作者 于洋 邓瑞 +1 位作者 余刚 庞新富 《控制理论与应用》 EI CAS CSCD 北大核心 2024年第3期407-415,共9页
在线鲁棒随机权神经网络(OR-RVFLN)具有较好的逼近性、较快的收敛速度、较高的鲁棒性能以及较小的存储空间.但是,OR-RVFLN算法计算过程中会产生矩阵的不适定问题,使得隐含层输出矩阵的精度较低.针对这个问题,本文提出了奇异值分解下在... 在线鲁棒随机权神经网络(OR-RVFLN)具有较好的逼近性、较快的收敛速度、较高的鲁棒性能以及较小的存储空间.但是,OR-RVFLN算法计算过程中会产生矩阵的不适定问题,使得隐含层输出矩阵的精度较低.针对这个问题,本文提出了奇异值分解下在线鲁棒正则化随机网络(SVD-OR-RRVFLN).该算法在OR-RVFLN算法的基础上,将正则化项引入到权值的估计中,并且对隐含层输出矩阵进行奇异值分解;同时采用核密度估计(KDE)法,对整个SVD-OR-RRVFLN网络的权值矩阵进行更新,并分析了所提算法的必要性和收敛性.最后,将所提的方法应用于Benchmark数据集和磨矿粒度的指标预测中,实验结果证实了该算法不仅可以有效地提高模型的预测精度和鲁棒性能,而且具有更快的训练速度. 展开更多
关键词 随机权神经网络 正则化 奇异值分解 磨矿过程 磨矿粒度
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谈德国施普林格数据库(Springer link)的特点及检索功能 被引量:2
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作者 谈鹤玲 《农业图书情报学刊》 2003年第5期115-116,共2页
作者通过对德国施普林格数据库 (Springerlink)的长期实际运用 ,就其概况、分类科学性、收录权威性、标识明确性、运用简单性等特点及检索功能进行了分析介绍 ,以供读者借鉴。
关键词 德国 施普林格数据库 期刊检索系统 电子出版物 文献分类 文献权威性 文献标识
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