TITLE

A new damping factor algorithm based on line search of the local minimum point for inverse approach

AUTHOR(S)
Zhang, Yaqi; Liu, Weijie; Lu, Fang; Zhang, Xiangkui; Hu, Ping
PUB. DATE
May 2013
SOURCE
AIP Conference Proceedings;May2013, Vol. 1532 Issue 1, p870
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
The influence of damping factor on the convergence and computational efficiency of the inverse approach was studied through a series of practical examples. A new selection algorithm of the damping (relaxation) factor which takes into account of both robustness and calculation efficiency is proposed, then the computer program is implemented and tested on Siemens PLM NX | One-Step. The result is compared with the traditional Armijo rule through six examples such as U-beam, square box and cylindrical cup et al, confirming the effectiveness of proposed algorithm.
ACCESSION #
87656117

 

Related Articles

  • A robust recurrent simultaneous perturbation stochastic approximation training algorithm for recurrent neural networks. Xu, Zhao; Song, Qing; Wang, Danwei // Neural Computing & Applications;Jun2014, Vol. 24 Issue 7/8, p1851 

    Training of recurrent neural networks (RNNs) introduces considerable computational complexities due to the need for gradient evaluations. How to get fast convergence speed and low computational complexity remains a challenging and open topic. Besides, the transient response of learning process...

  • Software Project Scheduling by AGA. Hanchate, Dinesh Bhagwan; Bichkar, Rajankumar S. // International Journal of Computer Applications;Jun2014, Vol. 96, p21 

    This paper proposes general techniques for adapting operators in SGA for software project scheduling problem. The use of adaptive of crossover and mutation gives chance to control the diversity. Adaptive nature also tends to give convergence in the complex solution. Crossover and Mutation...

  • A New Method to Generate Test Cases by Genetic Algorithm. Liu Yu; Wang Fengqin; Han Qiufeng // Applied Mechanics & Materials;2014, Issue 644-650, p2547 

    Because of the powerful capability of global searching and robustness of genetic algorithm, so it can be well applied in the automated generation of test data. Establish a module to generate test cases automatically by genetic algorithms. We can find that genetic algorithm guide the generation...

  • Wolf Pack Algorithm for Unconstrained Global Optimization. Hu-Sheng Wu; Feng-Ming Zhang // Mathematical Problems in Engineering;2014, p1 

    The wolf pack unites and cooperates closely to hunt for the prey in the Tibetan Plateau, which shows wonderful skills and amazing strategies. Inspired by their prey hunting behaviors and distribution mode, we abstracted three intelligent behaviors, scouting, calling, and besieging, and two...

  • A Branch-and-Bound Algorithm Embedded with DCA for DC Programming. Meihua Wang; Fengmin Xu; Chengxian Xu // Mathematical Problems in Engineering;2012, Vol. 2012, Special section p1 

    The special importance of Difference of Convex (DC) functions programming has been recognized in recent studies on nonconvex optimization problems. In this work, a class of DC programming derived from the portfolio selection problems is studied. The most popular method applied to solve the...

  • EFFICIENT ALGORITHMS FOR PRESERVING ENERGY AT NODES OF A NETWORK. Zanaj, Elma; Zanaj, Blerina // Albanian Journal of Natural & Technical Sciences;2011, Vol. 30 Issue 1, p109 

    Introduced in different topologies and characterized by simplicity of application, averaging algorithms are of great interest to researchers due to their simplicity in implementation. Simulated behaviour of three algorithms-Standard, Broadcast and Geographic Gossip-are applied here in two...

  • A Branch-and-Bound Algorithm Embedded with DCA for DC Programming. Meihua Wang; Fengmin Xu; Chengxian Xu // Mathematical Problems in Engineering;2012, Vol. 2012, Special section p1 

    The special importance of Difference of Convex (DC) functions programming has been recognized in recent studies on nonconvex optimization problems. In this work, a class of DC programming derived from the portfolio selection problems is studied. The most popular method applied to solve the...

  • Stochastic Portfolio Selection Using Breeding Swarm Optimization. Moradi, Shahab Mohammad; Khaloozadeh, Hamid; Forghani, Nosratollah // Journal of Applied Sciences;2008, Vol. 8 Issue 11, p2130 

    In this study, the portfolio selection problem is concerned, in case that expected return rates are stochastic variables and the breeding swarm algorithm is applied to solve this problem. The first, the stochastic portfolio model and reliable decision are presented. The second, the global...

  • A New Algorithm with Low Complexity for Adaptive Filtering. Arezki, M.; Benallal, A.; Meyrueis, P.; Berkani, D. // Engineering Letters;2010, Vol. 18 Issue 3, p205 

    In this paper, we propose a new algorithm M-SMFTF for adaptive filtering with fast convergence and low complexity. It is the result of a simplified FTF type algorithm, where the adaptation gain is obtained only from the forward prediction variables and using a new recursive method to compute the...

Share

Read the Article

Courtesy of VIRGINIA BEACH PUBLIC LIBRARY AND SYSTEM

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics