检索结果-内蒙古大学图书馆

Prediction of discharge through a sharp-crested triangular weir using ANN model trained with Levenberg-marquardt algorithm

引用

MODELING EARTH SYSTEMS AND ENVIRONMENT 2022年第1期8卷 1405-1417页

作者： Ali, Md. Shaheer Ayaz, Md. Mansoor, Talib Aligarh Muslim Univ Univ Polytech Civil Engn Sect Aligarh 202002 Uttar Pradesh India Aligarh Muslim Univ Dept Civil Engn Zakir Husain Coll Engn & Technol Aligarh 202002 Uttar Pradesh India

The measurement of discharge plays an important role in the design of open channels. Direct measurements of discharges in large canals and rivers are not feasible because of high flow. Weirs are the most widely used discharge-measuring device for open channels. In this study, the experimental study along with the modeling of discharge through a sharp-crested triangular weir using ANN model has been conducted. The sharp-crested triangular weirs having apex angles 30 degrees, 45 degrees, 60 degrees, 75 degrees, 90 degrees and weir heights 15 cm, 18 cm, and 20 cm have been used in this study. The experiments were conducted for each combination of weir angle and weir height. The head above the weir crest was measured for all such combinations of apex angles and weir heights for different discharges. These experimental data are then used to train the ANN model to predict the discharge over a sharp-crested triangular weir. The Levenberg-marquardt algorithm has been used as training algorithm. The MSE and R have been used as statistical parameters to judge the performance of ANN model. The ANN model terminates after 18 epochs and the MSE obtained for training, validation and testing are 8.477e - 08, 1.471 e - 07 and 1.325 e - 07, respectively. The corresponding R values obtained for training, validation and testing are 0.9987, 0.9973 and 0.9962, respectively. It was also observed that the predicted discharge stays within the range of +/- 5% of the experimental discharge value. The model performance results are encouraging and conclusive and the developed ANN model may be used to predict the discharge over sharp-crested triangular weir precisely.

关键词： Triangular weir ANN Discharge Open channel flow Levenberg– marquardt algorithm

来源：评论

学校读者我要写书评

暂无评论

Soft Tissue Deformation Model Based on marquardt algorithm and Enrichment Function

引用

Computer Modeling in Engineering & Sciences 2020年第9期124卷 1131-1147页

作者： Xiaorui Zhang Xuefeng Yu Wei Sun Aiguo Song Jiangsu Engineering Center of Network Monitoring Engineering Research Center of Digital ForensicsMinistry of EducationSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing210044China State Key Laboratory of Bioelectronics Jiangsu Key Lab of Remote Measurement and ControlSchool of Instrument Science and EngineeringSoutheast UniversityNanjing210096China

In order to solve the problem of high computing cost and low simulation accuracy caused by discontinuity of incision in traditional meshless model,this paper proposes a soft tissue deformation model based on the marquardt algorithm and enrichment *** model is based on the element-free Galerkin method,in which Kelvin viscoelastic model and adjustment function are *** algorithm is applied to fit the relation between force and displacement caused by surface deformation,and the enrichment function is applied to deal with the discontinuity in the meshless *** verify the validity of the model,the Sensable Phantom Omni force tactile interactive device is used to simulate the deformations of stomach and *** results show that the proposed model improves the real-time performance and accuracy of soft tissue deformation simulation,which provides a new perspective for the application of the meshless method in virtual surgery.

关键词： Virtual surgery meshless model marquardt algorithm enrichment function soft tissue simulation

来源：评论

学校读者我要写书评

暂无评论

Real-time deformation of human soft tissues: A radial basis meshless 3D model based on marquardt's algorithm

引用

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2018年 153卷 237-252页

作者： Zhou, Jianyong Luo, Zu Li, Chunquan Deng, Mi Nanchang Univ Sch Mechatron Engn Nanchang Jiangxi Peoples R China Nanchang Univ Sch Informat Engn Nanchang Jiangxi Peoples R China New Mexico State Univ Dept Math Sci Las Cruces NM 88003 USA

Background: When the meshless method is used to establish the mathematical-mechanical model of human soft tissues, it is necessary to define the space occupied by human tissues as the problem domain and the boundary of the domain as the surface of those tissues. Nodes should be distributed in both the problem domain and on the boundaries. Under external force, the displacement of the node is computed by the meshless method to represent the deformation of biological soft tissues. However, computation by the meshless method consumes too much time, which will affect the simulation of real-time deformation of human tissues in virtual surgery. Methods: In this article, the marquardt's algorithm is proposed to fit the nodal displacement at the problem domain's boundary and obtain the relationship between surface deformation and force. When different external forces are applied, the deformation of soft tissues can be quickly obtained based on this relationship. Results and conclusions: The analysis and discussion show that the improved model equations with marquardt's algorithm not only can simulate the deformation in real-time but also preserve the authenticity of the deformation model's physical properties. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Meshless method marquardt algorithm Surface fitting Virtual surgery Real-time deformation

来源：评论

学校读者我要写书评

暂无评论

A Joint Optimization of Momentum Item and Levenberg-marquardt algorithm to Level Up the BPNN's Generalization Ability

引用

MATHEMATICAL PROBLEMS IN ENGINEERING 2014年第1期2014卷 1-10页

作者： Xiao, Lei Chen, Xiaohui Zhang, Xinghui Chongqing Univ State Key Lab Mech Transmiss Chongqing 400030 Peoples R China Mech Engn Coll Shijiazhuang 050003 Peoples R China

Back propagation neural network (BPNN) as a kind of artificial neural network is widely used in pattern recognition and trend prediction. For standard BPNN, it has many drawbacks such as trapping into local optima, oscillation, and long training time. Because training the standard BPNN is based on gradient descent method, and the learning rate is fixed. Momentum item and Levenberg-marquardt (LM) algorithmare two ways to adjust the weights among the neurons and improve the BPNN's performance. However, there is still much space to improve the two algorithms. The hybrid optimization of damping factor of LM and the dynamic momentum item is proposed in this paper. The improved BPNN is validated by Fisher Iris data and wine data. Then, it is used to predict the visit spend. The database is provided by Dunnhumby's Shopper Challenge. Compared with the other two improved BPNNs, the proposed method gets a better performance. Therefore, the proposed method can be used to do the pattern recognition and time series prediction more effectively.

关键词： marquardt algorithm BACK propagation (Artificial intelligence) NEURAL networks (Computer science) GENERALIZATION PATTERN recognition systems

来源：评论

学校读者我要写书评

暂无评论

Fermentation Process Modeling with Levenberg-marquardt algorithm and Runge-Kutta Method on Ethanol Production by Saccharomyces cerevisiae

引用

MATHEMATICAL PROBLEMS IN ENGINEERING 2014年第1期2014卷 1-10页

作者： Liu, Dengfeng Xu, Ling Xiong, Weili Zhang, Hong-Tao Lin, Chi-Chung Jiang, Lihua Xu, Baoguo Jiangnan Univ Minist Educ Key Lab Ind Adv Proc Control Light Ind Wuxi 214122 Peoples R China Wuxi Inst Commerce Sch Internet Things Technol Wuxi 214153 Peoples R China Jiangnan Univ Minist Educ Key Lab Ind Biotechnol Wuxi 214122 Peoples R China

The core of the Chinese rice wine making is a typical simultaneous saccharification and fermentation (SSF) process. In order to control and optimize the SSF process of Chinese rice wine brewing, it is necessary to construct kinetic model and study the influence of temperature on the Chinese rice wine brewing process. An unstructured kinetic model containing 12 kinetics parameters was developed and used to describe the changing of kinetic parameters in Chinese rice wine fermentation at 22, 26, and 30 degrees C. The effects of substrate and product inhibitions were included in the model, and four variable, including biomass, ethanol, sugar and substrate were considered. The R-square values for the model are all above 0.95 revealing that the model prediction values could match experimental data very well. Our model conceivably contributes significantly to the improvement of the industrial process for the production of Chinese rice wine.

关键词： SACCHAROMYCES cerevisiae FERMENTATION marquardt algorithm RUNGE-Kutta formulas ETHANOL

来源：评论

学校读者我要写书评

暂无评论

Numerical simulation and neural network model for hydromagnetic nanofluid convection in a porous wavy channel with thermal non-equilibrium model

引用

PHYSICA SCRIPTA 2024年第11期99卷 115219-115219页

作者： Rani, H. P. Shilpa, B. Leela, V Reddy, R. Gangadhara Natl Inst Technol Dept Math Warangal India Dayananda Sagar Coll Engn Dept Math Bangalore India PES Univ Dept Sci & Humanities Bangalore India VTU AMC Engn Coll Dept Math Bangalore India

The present study aims to analyze the nanofluid MHD convective heat transfer in a porous wavy channel with a local thermal non-equilibrium (LTNE) model. Such a model finds applications related to enhancement in thermal performance, increasing the heat transfer coefficient in the compact design of heat exchangers for the aerospace and automotive industries and elevation in the efficiency of the solar collector. A sinusoidal porous wavy LTNE channel containing nanofluid and subjected to the induced and applied magnetic fields is considered. A uniform magnetic field is applied orthogonal to the channel and the induced magnetic field effects are considered due to the large magnetic Reynolds number. The momentum, continuity, energy, and nanoparticle volume fraction equations constitute the coupled nonlinear system of differential equations and are solved using the Galerkin finite element method. The reliability of the technique is assessed by comparing the proposed procedure with the results from earlier sources. A detailed analysis is presented to determine the effects of different physical parameters arising in the system on temperature, nanoparticle concentration, and velocity profiles. As an illustration, the findings exhibit that increasing the modified diffusivity ratio increases the values of the nanoparticle volume fraction whereas, reducing the modified diffusivity ratio enhances the temperature distribution. A higher value of thermal Rayleigh number presents a significant involvement of buoyancy forces, potentially resulting in the development of convective currents. A higher Nield number indicates more effective heat transport from the solid surface to the nanofluid. Consequently, there is a minimal thermal difference between the solid surface and the bulk nanofluid. Effective heat transmission enhances the nanofluid ability to absorb heat and generates a more consistent dispersion of temperature inside the fluid. The performance of the designed algorithms of

关键词： nanofluid convection local thermal non-equilibrium magnetohydrodynamics induced magnetic field Galerkin finite element analysis levenberg marquardt algorithm

来源：评论

学校读者我要写书评

暂无评论

Levenberg-marquardt algorithm for Mackey-Glass Chaotic Time Series Prediction

引用

DISCRETE DYNAMICS IN NATURE AND SOCIETY 2014年第1期2014卷 1-6页

作者： Zhao, Junsheng Li, Yongmin Yu, Xingjiang Zhang, Xingfang Liaocheng Univ Sch Math Liaocheng 252059 Peoples R China Huzhou Univ Sch Sci Huzhou 313000 Peoples R China Southeast Univ Sch Automat Nanjing 210096 Jiangsu Peoples R China

For decades, Mackey-Glass chaotic time series prediction has attracted more and more attention. When the multilayer perceptron is used to predict the Mackey-Glass chaotic time series, what we should do is to minimize the loss function. As is well known, the convergence speed of the loss function is rapid in the beginning of the learning process, while the convergence speed is very slow when the parameter is near to the minimum point. In order to overcome these problems, we introduce the Levenberg-marquardt algorithm (LMA). Firstly, a rough introduction is given to the multilayer perceptron, including the structure and the model approximation method. Secondly, we introduce the LMA and discuss how to implement the LMA. Lastly, an illustrative example is carried out to show the prediction efficiency of the LMA. Simulations show that the LMA can give more accurate prediction than the gradient descent method.

关键词： marquardt algorithm TIME series analysis MULTILAYER perceptrons LOSS functions (Statistics) TIME delay systems NONLINEAR systems

来源：评论

学校读者我要写书评

暂无评论

Learning nonlinear dynamics with behavior ordinary/partial/system of the differential equations: looking through the lens of orthogonal neural networks

引用

ENGINEERING WITH COMPUTERS 2022年第SUPPL 2期38卷 1635-1654页

作者： Omidi, M. Arab, B. Rasanan, A. H. Hadian Rad, J. A. Parand, K. Shahid Beheshti Univ Fac Math Sci Dept Comp Sci Tehran Iran Shahid Beheshti Univ Inst Cognit & Brain Sci Dept Cognit Modeling Tehran Iran Inst Res Fundamental Sci IPM Sch Comp Sci Tehran Iran Univ Waterloo Dept Stat & Actuarial Sci Waterloo ON Canada

Applications of neural network algorithms have been grown in recent years and various architectures have been introduced by researchers for the purpose of solving different types of differential equations. Physics informed neural networks, functional link neural networks, and feed-forward differential equation neural networks are some of these architectures. In this paper, we introduce a new neural network for simulating the behavior of Emden-Fowler-type dynamic modeled as an ordinary/partial/system of differential equation, i.e. ODE/PDE/SDE which is based on the development of two introduced functional link neural network and feed-forward differential equation neural network for the partial/system of differential equations. This algorithm uses roots of shifted Chebyshev polynomials as a training data set and the The Levenberg-marquardt algorithm is taken as an optimizer. To show the applicability of the proposed network, it is applied to some test problems and the obtained results are compared with some other neural network approaches and also, some other numerical algorithms. The reported results showed that the algorithm proposed in this paper is a powerful method for simulating the behavior of partial and system of differential equations and is more accurate than other methods in the literature.

关键词： Lane– Emden-type equations Feed-forward neural network Functional link neural network Levenberg– marquardt algorithm Partial differential equations System of differential equations Chebyshev polynomial

来源：评论

学校读者我要写书评

暂无评论

Estimation of release history of groundwater pollution source using ANN model

引用

MODELING EARTH SYSTEMS AND ENVIRONMENT 2022年第1期8卷 925-937页

作者： Ayaz, Md. Aligarh Muslim Univ Fac Engn & Technol Univ Polytech Civil Engn Sect Aligarh 202002 Uttar Pradesh India

Estimating the release history of a groundwater pollutant source is an important environmental forensics problem. The knowledge of the release history of pollution source is critical in the prediction of the future trend of the pollutant movement. In addition, for identifying the responsible parties for allocating the remediation costs as well as in choosing an effective remediation strategy. Estimation of the release history with the help of concentration data is an ill-posed inverse problem. A novel approach based on ANN modeling has been developed in this study to estimate the release history of groundwater pollution source without using the prior knowledge of lag time. The required sampling duration of the breakthrough curve has been decreased in this study using the only upper half portion of the breakthrough curve which also reduces the uncertainties associated at the tail ends of the breakthrough curve. The previous studies in this area utilize the complete breakthrough curve whose lag time is completely known. The Levenberg-marquardt algorithm has been used to train ANN model. The problems solved in this study address both two and three-dimensional flow fields with erroneous concentration data. The results indicate that the developed ANN model appears to be robust even for large measurement error level in concentration data up-to 10% and very effective in solving these problems.

关键词： Release history Artificial neural network Levenberg– marquardt algorithm Groundwater pollution Hydrogeology

来源：评论

学校读者我要写书评

暂无评论

Solving ordinary differential equations using an optimization technique based on training improved artificial neural networks

引用

SOFT COMPUTING 2021年第5期25卷 3713-3723页

作者： Li, Shangjie Wang, Xingang Northeastern Univ Sch Mech Engn & Automat Shenyang 110819 Peoples R China Northeastern Univ Res Ctr Mech Kinet & Reliabil Qinhuangdao 066004 Hebei Peoples R China

The solution of ordinary differential equations (ODEs) arises in a wide variety of engineering problems. This paper presents a novel method for the numerical solution of ODEs using improved artificial neural networks (IANNs). In the first step, we derive an approximate solution of ODEs by artificial neural networks (ANNs). Then, we construct a joint cost function of network system, it consists of several error functions corresponding to different sample points, and we reformulate Levenberg-marquardt (RLM) algorithm to adjust the network parameters. The advantages of this method are high calculation accuracy and fast convergence speed compared with other existed methods, also increasing the simulation stability of ANNs method. The performance of the new proposed method in terms of calculation accuracy and convergence speed is analyzed for several different types of nonlinear ODEs.

关键词： Differential equations Improved artificial neural networks Joint cost function Reformulate Levenberg– marquardt algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：