$\require{mediawiki-texvc}$
  • 검색어에 아래의 연산자를 사용하시면 더 정확한 검색결과를 얻을 수 있습니다.
  • 검색연산자
검색연산자 기능 검색시 예
() 우선순위가 가장 높은 연산자 예1) (나노 (기계 | machine))
공백 두 개의 검색어(식)을 모두 포함하고 있는 문서 검색 예1) (나노 기계)
예2) 나노 장영실
| 두 개의 검색어(식) 중 하나 이상 포함하고 있는 문서 검색 예1) (줄기세포 | 면역)
예2) 줄기세포 | 장영실
! NOT 이후에 있는 검색어가 포함된 문서는 제외 예1) (황금 !백금)
예2) !image
* 검색어의 *란에 0개 이상의 임의의 문자가 포함된 문서 검색 예) semi*
"" 따옴표 내의 구문과 완전히 일치하는 문서만 검색 예) "Transform and Quantization"

특허 상세정보

Approximate fitness functions

국가/구분 United States(US) Patent 등록
국제특허분류(IPC7판) G06F-015/18   
미국특허분류(USC) 706/013
출원번호 US-0007734 (2001-11-09)
우선권정보 EP-00124825(2000-11-14)
발명자 / 주소
출원인 / 주소
대리인 / 주소
    Fenwick &
인용정보 피인용 횟수 : 15  인용 특허 : 12
초록

A framework for managing approximate models in generation-based evolution control is proposed. This framework is well suited for parallel evolutionary optimization that is able to guarantee the correct convergence of the evolutionary algorithm and to reduce the computation costs as much as possible. Control of the evolution and updating of the approximate models are based on the estimated fidelity of the approximate model. The frequency at which the original function is called and the approximate model is updated is determined by the local fidelity of th...

대표
청구항

What is claimed is: 1. A method for evolutionary optimization, comprising the following steps: setting up an initial population as parents, reproducing the parents to create a plurality of offsprings, evaluating the quality of the offsprings by means of a fitness function, said fitness function is one of an original fitness function and an approximate fitness function, and selecting at least one offspring having the highest evaluated quality value as parents, characterized in that the frequency of the use of the original fitness function is adaptable...

이 특허에 인용된 특허 (12)

  1. Smith Brian L.. Adaptive computing systems, computer readable memories and processes employing hyperlinear chromosomes. USP1998105819244.
  2. McCormack Michael D. ; MacAllister Donald J. ; Stoisits Richard F. ; Scherer Perry W. ; Ma Tuan D.. Automated material balance system for hydrocarbon reservoirs using a genetic procedure. USP1999075924048.
  3. Wang Daniel T. (Jacksonville FL) Johnson Lars W. (Indialantic FL) Lepper John M. (Jacksonville FL) Martin Wallace A. (Orange Park FL) Reinhart Leonard R. (Melbourne FL) Sanka Ravi S. (Jacksonville FL. Computer system for quality control correlations. USP1995105461570.
  4. Syswerda Gilbert P. (Winchester MA). Generation of schedules using a genetic procedure. USP1994065319781.
  5. McCormack Michael D. (Plano TX) Feldman D. Scott (Anchorage AK) Bowling Chester M. (Evergreen CO). Genetic method of scheduling the delivery of non-uniform inventory. USP1996075541848.
  6. Rai, Man Mohan; Madavan, Nateri K.. Method for constructing composite response surfaces by combining neural networks with other interpolation or estimation techniques. USP2003086606612.
  7. Xiao, Jing. Method for generating near-optimal sequencing of manufacturing tasks subject to user-given hard and soft constraints. USP2003126662167.
  8. Koza John R. (25372 La Rena La. Los Altos Hills CA 94022) Rice James P. (Redwood City CA). Non-linear genetic process for use with plural co-evolving populations. USP1992095148513.
  9. Roska Tamas (Budapest CA HUX) Chua Leon O. (Berkeley CA). Reprogrammable CNN and supercomputer. USP1994105355528.
  10. Lawrence E. Hunter. System and method for combining multiple learning agents to produce a prediction method. USP2002096449603.
  11. Ulyanov, Sergei V.. System and method for control using quantum soft computing. USP2003066578018.
  12. Allen John B. (Long Beach CA). Trailing edge splitter. USP1993115265830.

이 특허를 인용한 특허 피인용횟수: 15

  1. Goldberg, David E.; Sastry, Kumara; Lobo, Fenando G.; Lima, Claudio F.. Adaptive optimization methods. USP2012038131656.
  2. Graepel, Thore; Candela, Joaquin Quinonero; Borchert, Thomas Ivan; Herbrich, Ralf. Event prediction in dynamic environments. USP2013048417650.
  3. Sendhoff, Bernhard; Beyer, Hans-Georg. Evolutionary search for robust solutions. USP2010087783583.
  4. Rai,Man Mohan. Hybrid neural network and support vector machine method for optimization. USP2007117293001.
  5. Prokhorov, Danil V.. Method for approximation of optimal control for nonlinear discrete time systems. USP2013098538901.
  6. Goldberg, David E.; Sastry, Kumara; Llorá, Xavier F.. Methods and systems for interactive computing. USP2011077979365.
  7. Jin,Yaochu; Sendhoff,Bernhard. Methods for multi-objective optimization using evolutionary algorithms. USP2008047363280.
  8. Chitapur, Siddalingaprabhu Amareshappa; Almeida, Kiran Joseph; Bommaiah, Sridhar; Reddy, Veera Raghava. Policy scheduling. USP2014068762304.
  9. Bollen, Johan L T M; Mao, Hulna. Predicting economic trends via network communication mood tracking. USP2013028380607.
  10. Jin,Yaochu; Sendhoff,Bernhard. Reduction of fitness evaluations using clustering techniques and neural network ensembles. USP2008047363281.
  11. Rai,Man Mohan. Robust, optimal subsonic airfoil shapes. USP2008117454321.
  12. Olhofer,Markus; Sendhoff,Bernhard. Strategy parameter adaptation in evolution strategies. USP2007077243056.
  13. Jin,Yaochu; Sendhoff,Bernhard; Okabe,Tatsuya; Olhofer,Markus. System and method for estimation of a distribution algorithm. USP2008097428514.
  14. Kumar, Rakesh. System and method for performing non-linear constrained optimization with a genetic algorithm. USP2010037672910.
  15. Kumar, Rakesh. System and method for the use of an adaptive mutation operator in genetic algorithms. USP2010027660773.