检索结果-内蒙古大学图书馆

Oriented stochastic loss descent algorithm to train very deep multi-layer neural networks without vanishing gradients

引用

KNOWLEDGE-BASED SYSTEMS 2021年 230卷 107391-107391页

作者： Abuqaddom, Inas Mahafzah, Basel A. Faris, Hossam Univ Jordan King Abdullah II Sch Informat Technol Dept Comp Sci Amman Jordan Al Hussien Tech Univ Sch Comp & Informat Amman Jordan Univ Jordan King Abdullah II Sch Informat Technol Dept Informat Technol Amman Jordan

Deep multi-layer neural networks represent hypotheses of very high degree polynomials to solve very complex problems. gradient descent optimization algorithms are utilized to train such deep networks through backpropagation, which suffers from permanent problems such as the vanishing gradient problem. To overcome the vanishing problem, we introduce a new anti-vanishing back-propagated learning algorithm called oriented stochastic loss descent (OSLD). OSLD updates a random-initialized parameter iteratively in the opposite direction of its partial derivative sign by a small positive random number, which is scaled by a tuned ratio of the model loss. This paper compares OSLD to stochastic gradient descent algorithm as the basic backpropagation algorithm and Adam as one of the best backpropagation algorithms in five benchmark models. Experimental results show that OSLD is very competitive to Adam in small and moderate depth models, and OSLD outperforms Adam in very long models. Moreover, OSLD is compatible with current backpropagation architectures except for learning rates. Finally, OSLD is stable and opens more choices in front of the very deep multi-layer neural networks. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Vanishing gradient problem Deep learning Backpropagation gradient descent algorithm Optimization algorithm Deep multi-layer neural network

来源：评论

学校读者我要写书评

暂无评论

Convergence Analysis of Interval Feedforward Neural Networks

Convergence Analysis of Interval Feedforward Neural Networks

引用

第34届中国控制与决策会议

作者： Shouping Guan Yue Liang Xiaoyu Yu College of Information Science and Engineering Northeastern University

In practical application of neural networks,we often try to change some factors to make the algorithm perform better,but the convergence analysis of the algorithm cannot keep up with it in *** paper studies the convergence of interval feedforward neural network(IFNN).First the convergence of the IFNN is derived theoretically based on gradient descent algorithm,where the IFNN possesses the interval input and output but the point weights;Then,by means of numerical analysis,the relationship between the convergence of general IFNN and interval weights is *** the numerical analysis,the coverage of interval output is taken as the objective function,and the particle swarm optimization(PSO) algorithm is used for optimizing to ensure the interval network output approaching the interval width range of the weight and threshold of the point *** the convergence of interval neural networks(INNs) can effectively promote the application range of INNs,making INNs better used in uncertain systems,reducing the impact of fluctuations,noise and measurement errors,and improving the objectivity and robustness of industrial process modeling.

关键词： Interval Neural Network gradient descent algorithm Convergence Information Granularity

来源：评论

学校读者我要写书评

暂无评论

Comparing the performance of neural networks developed by using Levenberg-Marquardt and Quasi-Newton with the gradient descent algorithm for modelling a multiple response grinding process

引用

EXPERT SYSTEMS WITH APPLICATIONS 2012年第3期39卷 2397-2407页

作者： Mukherjee, Indrajit Routroy, Srikanta Indian Inst Technol Shailesh J Mehta Sch Management Bombay 400076 Maharashtra India Birla Inst Technol & Sci Dept Mech Engn Pilani 333031 Rajasthan India

Monitoring and control of multiple process quality characteristics (responses) in grinding plays a critical role in precision parts manufacturing industries. Precise and accurate mathematical modelling of multiple response process behaviour holds the key for a better quality product with minimum variability in the process. Artificial neural network (ANN)-based nonlinear grinding process model using backpropagation weight adjustment algorithm (BPNN) is used extensively by researchers and practitioners. However, suitability and systematic approach to implement Levenberg-Marquardt (L-M) and Boyden, Fletcher, Gold-farb and Shanno (BFGS) update Quasi-Newton (Q-N) algorithm for modelling and control of grinding process is seldom explored. This paper provides L-M and BEGS algorithm-based BPNN models for grinding process, and verified their effectiveness by using a real life industrial situation. Based on the real life data, the performance of L-M and BFGS update Q-N are compared with an adaptive learning (A-L) and gradient descent algorithm-based BPNN model. The results clearly indicate that L-M and BEGS-based networks converge faster and can predict the nonlinear behaviour of multiple response grinding process with same level of accuracy as A-L based network. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Back propagation neural network gradient descent algorithm Levenberg-Marquardt algorithm Multiple response Quasi-Newton algorithm

来源：评论

学校读者我要写书评

暂无评论

Mixed-integer nonlinear programming model for layout design of subsea satellite well system in deep water oil field

引用

AUTOMATION IN CONSTRUCTION 2021年 123卷 103524-103524页

作者： Hong, Cheng Estefen, Segen F. Wang, Yuxi Lourenco, Marcelo Igor Ningbo Univ Fac Maritime & Transportat Ningbo 315211 Peoples R China Univ Fed Rio de Janeiro Ocean Engn Dept COPPE BR-21941972 Rio De Janeiro Brazil State Key Lab Petr Pollut Control Beijing 102206 Peoples R China CNPC Res Inst Safety & Environm Technol Beijing 102206 Peoples R China

This paper focuses on the concept of a subsea satellite well system in deep water oil field, and a mixed-integer nonlinear programming model (MINLP) is proposed to help design the layout to minimize the payback period. The proposed model has two key aspects. First, the objective function, payback period, reflects the link between the total cost and production. And second, the Floating Production Storage and Offloading units (FPSOs), subsea wells, flowlines, and subsea obstacles are integrated for the modeling, presenting the interaction of the components from underground to the sea level. A decomposition strategy based on gradient descent algorithm is proposed to solve the model. The case studies indicate the model's feasibility. Besides, two different applications of the model are presented, one is to optimize the layout under given horizontal displacements and the other is the cost comparison between drilling horizontal well and vertical well, indicating the model's flexibility.

关键词： Subsea production system Satellite well system concept Layout design Mixed-integer nonlinear programming gradient descent algorithm

来源：评论

学校读者我要写书评

暂无评论

Learning-Based Motion Planning of a 14-DOF Biped Robot on 3D Uneven Terrain Containing a Ditch

引用

INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS 2021年第6期18卷

作者： Kumar, Jitendra Dutta, Ashish IIT Kanpur Dept Mech Engn Kanpur 208016 Uttar Pradesh India

In this paper, a new method is proposed that integrates the 3D terrain information, ditch geometry, and biped dynamics for motion planning of a 14-DOF biped robot on 3D terrain containing a 3D ditch. The path planning is modeled as a wavefront propagation in Non-uniform medium represented by the Eikonal equation. A speed function expresses the inhomogeneity of uneven terrain. The Eikonal equation is solved by the Fast marching method (FMM) to obtain the global path. Ten Footstep variables (FSVs) characterize one step of walk on a 3D uneven terrain surface. The hip and foot trajectory parameters (HFTPs) are used to construct cubic spline-based hip and foot trajectories of the biped robot. The optimal value of HFTPs is obtained by a Genetic algorithm by minimization of energy and satisfying the constraint of dynamic balance. A walk-dataset is created that contains the optimal trajectories for different FSVs. The generated walk-dataset was used to train the biped to walk on rough terrain using a feed-forward Neural network for making a real-time estimate of optimal HFTPs. Simulation results validate the effectiveness of the proposed method of ditch crossing on different uneven terrains.

关键词： Fast marching method gradient descent algorithm genetic algorithm footstep variables hip and foot trajectory parameters walk-dataset

来源：评论

学校读者我要写书评

暂无评论

A hybrid metaheuristic algorithm for location inventory routing problem with time windows and fuel consumption

引用

EXPERT SYSTEMS WITH APPLICATIONS 2021年 166卷 114034-114034页

作者： Wu, Weitiao Zhou, Wei Lin, Yue Xie, Yuanqi Jin, Wenzhou South China Univ Technol Sch Civil Engn & Transportat Guangzhou 510641 Peoples R China

We introduce a multi-period location-inventory-routing problem with time windows and fuel consumption, which simultaneously optimizes the location, routing, and inventory decisions for both the distribution center and customers in a multi-echelon supply chain. To better reflect reality, the fuel consumption is also incorporated into the variable transportation cost. The problem is formulated as a mixed integer nonlinear programming model. We then propose a two-stage hybrid metaheuristic algorithm to address this problem. In the first stage, a customized genetic algorithm is proposed. In the second stage, a gradient descent algorithm is used to improve the inventory decision to further reduce the total cost. Results of numerical experimentations on generated instances confirm the effectiveness of the algorithm. Results show that inventory management activities contribute considerably to total cost saving. Given the cost trade-off between transportation and inventory, the retailers' inventory level shows more shortages after post-optimization, while the inventory level in the distribution centers can be either reduced or increased, depending on the spatial distribution of retailers in the vicinity of the distribution center. Sensitivity analysis on the model parameters is also conducted to provide managerial insights.

关键词： Location-inventory-routing problem Fuel consumption Hybrid heuristic algorithm gradient descent algorithm

来源：评论

学校读者我要写书评

暂无评论

Multi-objective Optimization Control for Input-Series Output-Parallel Dual-Active-Bridge DC-DC Converter in EER Application 9

Multi-objective Optimization Control for Input-Series Output...

引用

IEEE 9th International Power Electronics and Motion Control Conference (IPEMC-ECCE Asia)

作者： Zhou, Bingkai Yang, Xiaofeng Nong, Renbiao Li, Zejie Zheng, Trillion Q. Kobrle, Pavel Beijing Jiaotong Univ Sch Elect Engn Beijing Peoples R China Czech Tech Univ Fac Elect Engn Prague Czech Republic

ISBN: (纸本)9781728153018

For reducing backflow power and improving dynamic performance of the input-series output-parallel dual-active-bridge (ISOP-DAB) converter in the electric energy router application, a hybrid control strategy based on the extended-phase-shift (EPS) output voltage model predictive control and gradient descent algorithm (MPC-GDA) is proposed. Firstly, the backflow power models under single-phase-shift (SPS) and EPS control are established, and the output voltage state space averaging equation under EPS control is also derived. Then the output voltage model predictive control is obtained, and the gradient descent algorithm for backflow power optimization is proposed. Finally, the overall control block diagram of the ISOP-DAB based on MPC-GDA control is derived. The simulation models of ISOP-DAB under MPC-GDA and SPS control are built and compared. It is verified that the MPC-GDA control shows better dynamic response and backflow power optimization compared with the traditional SPS control.

关键词： dual-active-bridge input-series output-parallel backflow power model predictive control gradient descent algorithm

来源：评论

学校读者我要写书评

暂无评论

Temperature Controller Using the Takagi-Sugeno-Kang Fuzzy Inference System for an Industrial Heat Treatment Furnace 20th

Temperature Controller Using the Takagi-Sugeno-Kang Fuzzy In...

引用

20th International Conference on Computational Science and Its Applications (ICCSA)

作者： Buele, Jorge Rios-Cando, Paulina Brito, Geovanni Moreno-P, Rodrigo Salazar, Franklin W. Univ Tecnol Indoamer SISAu Res Grp Ambato 180212 Ecuador Escuela Super Politecn Chimborazo Riobamba 060155 Ecuador Univ Tecn Ambato Ambato 180103 Ecuador

ISBN: (纸本)9783030588175;9783030588168

The industrial welding industry has a high energy consumption due to the heating processes carried out. The heat treatment furnaces used for reheating equipment made of steel require a good regulator to control the temperature at each stage of the process, thereby optimizing resources. Considering dynamic and variable temperature behavior inside the oven, this paper proposes the design of a temperature controller based on a Takagi-Sugeno-Kang (TSK) fuzzy inference system of zero order. Considering the reaction curve of the temperature process, the plant model has been identified with the Miller method and a subsequent optimization based on the descending gradient algorithm. Using the conventional plant model, a TSK fuzzy model optimized by the recursive least square's algorithm is obtained. The TSK fuzzy controller is initialized from the conventional controller and is optimized by descending gradient and a cost function. Applying this controller to a real heat treatment system achieves an approximate minimization of 15 min with respect to the time spent with a conventional controller. Improving the process and integrated systems of quality management of the service provided.

关键词： Fuzzy logic controller gradient descent algorithm Heat treatment Temperature control

来源：评论

学校读者我要写书评

暂无评论

Riemannian optimization for phase retrieval from masked Fourier measurements

引用

ADVANCES IN COMPUTATIONAL MATHEMATICS 2021年第6期47卷 88-88页

作者： Li Huiping Li Song Zhejiang Univ Sch Math Sci 38 Zheda Rd Hangzhou 310027 Peoples R China Hangzhou Normal Univ Dept Math 2318 Yuhangtang Rd Hangzhou 311121 Peoples R China

In this paper, we consider the noisy phase retrieval problem under the measurements of Fourier transforms with complex random masks. Here two kinds of Riemannian optimization algorithms, namely, Riemannian gradient descent algorithm (RGrad) and Riemannian conjugate gradient descent algorithm (RCG), are presented to solve such problem from these special but widely used measurements in practical applications. Since the masked Fourier measurements are less random, we establish stable guarantees for signals by the truncated variants of RGrad and RCG, respectively. First of all, a good initialization is constructed by means of a truncated spectral method. Then we prove that a signal x is an element of C-n can be recovered robustly to bounded noise through these two algorithms, provided that L = O(log n) complex random masks are performed in the measurement process. This implies that the sample complexity is optimal up to a log factor, namely, O(n log n). Particularly, each sequence generated by the truncated RGrad and RCG provably converges to the true solution at a geometric rate in the noiseless case. Finally, several empirical experiments are provided to show the effectiveness and stability of such two kinds of algorithms compared with Wirtinger Flow(WF) algorithm, for which provable guarantee has been set up for signals under masked Fourier measurements, provided that L = O(log(4) n).

关键词： Phase retrieval Riemannian optimization gradient descent algorithm Conjugate gradient descent algorithm Masked Fourier measurements

来源：评论

学校读者我要写书评

暂无评论

Performance analysis of permanent magnet synchronous motor based on transfer function model using PID controller tuned by Ziegler-Nichols method

Results in Engineering

引用

Results in Engineering 2025年 26卷

作者： V Ramanaiah Nippatla Srihari Mandava School of Electrical Engineering Vellore Institute of Technology Vellore Tamil Nadu 632014 India

Proportional Integral and Derivative (PID) controller tuning is one of the most important factors in control systems engineering for achieving an efficient and desired system performance. There are many tuning methods available but in this article, Ziegler-Nichols (ZN) tuning method is proposed to determine the gain values ( K p , K i and K d ) of PID controller based on system behaviour. The ZN method is a heuristic and popular technique especially intended for PID controller tuning because of its advantages which are simple design, fast and perfect tuning, good reliability and mostly used in industrial applications. The speed response of Permanent Magnet Synchronous Motor (PMSM) is enhanced using PID controller tuned by proposed method. The PMSM is predominantly used in Electric Vehicles (EV), electric traction and industrial drive applications. The ZN method provides the distinctive dynamic speed response and also analyzes peak overshoot, settling time and steady-state error which are 1.677 %, 1.133 s and 1.16 times respectively, compared to the gradient descent (GD) algorithm. In this article, the proposed ZN-PID controller is tuned offline and used in both outer and inner feedback loops to control the speed and torque respectively. This work primarily depends on transfer function model based Field Oriented Control (FOC) approach using MATLAB R2019b/Simulink software. The proposed ZN-PID controller improves the speed response of PMSM in terms of time domain specifications over existing GD-PID controller. The MATLAB R2019b/Simulation work is done and also tested the stability analysis with Bode plot. The hardware results are compared with MATLAB/Simulation results.

关键词： gradient descent algorithm Field Oriented Control Proportional Integral and Derivative controller Permanent Magnet Synchronous Motor Ziegler-Nichols tuning method

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

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

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

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

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：