• Title/Summary/Keyword: genetic structure

Search Result 1,618, Processing Time 0.028 seconds

Auto-Tuning Method for fuzzy Controller Using Genetic Algorithms (유전 알고리즘을 이용한 퍼지 제어기의 자동 동조)

  • Rho, Gi-Gab;Joo, Young-Hoon;Park, Jin-Bae
    • Proceedings of the KIEE Conference
    • /
    • 1997.07b
    • /
    • pp.728-731
    • /
    • 1997
  • This paper proposes the systematic auto-tuning method for fuzzy controller using genetic algorithm(GA). In general, the design of fuzzy logic controller has difficulties in the acquisition of expert's knowledge and relies to a great extent on heuristic knowledge which, in many cases, cannot be objectively justified. So, the performance of the controller can be degraded in the case of plant parameter variations or unpredictable incident which the designer may have ignored. Proposed genetic algorithm searches the optimal rule structure, parameters of membership functions and scaling factors simultaneously and automatically by a new genetic coding format. Inverted pendrum system is provided to show the advantages of the proposed method.

  • PDF

Testing microsatellite loci and preliminary genetic study for Eurasian otter in South Korea

  • Jo, Yeong-Seok;Won, Chang-Man;Jung, Jongwoo
    • Journal of Species Research
    • /
    • v.1 no.2
    • /
    • pp.240-248
    • /
    • 2012
  • We used a non-invasive technique with microsatellite primers to investigate genetic variation among Eurasian otters Lutra lutra in eastern South Korea. We collected twenty two otter spraints in January and six in August 2008. We used spraints from five dead otters from five different river systems for the present genetic analysis. We extracted DNA from 20 spraints from the January sample. Ten microsatellite primers (Lut435, Lut453, Lut457, Lut604, Lut615, Lut701, Lut715, Lut717, Lut733, and Lut832) for Eurasian otters were tested, and four loci were successfully amplified for further analyses. The results of genotyping the otter population with microsatellite loci lead to the identification of 9 individuals from the Ungokcheon Stream. The Ungokcheon population also showed a genetic structure represented by the Hardy-Weinberg equilibrium.

A Study on the Optimal Facility Layout Design Using an Improved Genetic Algorithm (개선된 유전자 알고리즘을 이용한 최적 공간 배치 설계에 관한 연구)

  • 한성남;이규열;노명일
    • Korean Journal of Computational Design and Engineering
    • /
    • v.6 no.3
    • /
    • pp.174-183
    • /
    • 2001
  • This study proposes an improved genetic algorithm (GA) to derive solutions for facility layout problems having inner walls and passages. The proposed algorithm models the layout of facilities on a flour-segmented chromosome. Improved solutions are produced by employing genetic operations known as selection, crossover, inversion, mutation, and refinement of these genes for successive generations. All relationships between the facilities and passages are represented as an adjacency graph. The shortest path and distance between two facilities are calculated using Dijkstra's algorithm of graph theory. Comparative testing shows that the proposed algorithm performs better than other existing algorithm for the optimal facility layout design. Finally, the proposed algorithm is applied to ship compartment layout problems with the computational results compared to an actual ship compartment layout.

  • PDF

A Study on Genetic Algorithm of Concurrent Spare Part Selection for Imported Weapon Systems (국외구매 무기체계에 대한 동시조달수리부속 선정 유전자 알고리즘 연구)

  • Cho, Hyun-Ki;Kim, Woo-Je
    • Journal of Korean Institute of Industrial Engineers
    • /
    • v.36 no.3
    • /
    • pp.164-175
    • /
    • 2010
  • In this study, we developed a genetic algorithm to find a near optimal solution of concurrent spare parts selection for the operational time period with limited information of weapon systems purchased from overseas. Through the analysis of time profiles related with system operations, we first define the optimization goal which maintains the expected system operating rate under the budget restrictions, and the number of failures and the lead time for each spare part are used to calculate the estimated total down time of the system. The genetic algorithm for CSP selection shows that the objective function minimizes the estimated total down time of systems with satisfying the restrictions. The method provided by this study can be applied to the generalized model of CSP selection for the systems purchased from overseas without provision of their full structure and adequate information.

$H_\infty$ Optimal tuning of Power System Stabilizer using Genetic Algorithm (유전알고리즘을 이용한 전력계통 안정화 장치의 강인한 $H_\infty$최적 튜닝)

  • Jeong, Hyeong-Hwan;Lee, Jun-Tak;Lee, Jeong-Pil;Han, Gil-Man
    • The Transactions of the Korean Institute of Electrical Engineers A
    • /
    • v.49 no.3
    • /
    • pp.85-94
    • /
    • 2000
  • In this paper, a robust H$\infty$ optimal tuning problem of a structure-specified PSS is investigated for power systems with parameter variation and disturbance uncertainties. Genetic algorithm is employed for optimization method of PSS parameters. The objective function of the optimization problem is the H$\infty$-norm of a closed loop system. The constraint of the optimization problem are based on the stability of the controller, limits on the values of the parameters and the desired damping of the dominant oscillation mode. It is shown that the proposed H$\infty$ PSS tuned using genetic algorithm is more robust than conventional PSS.

  • PDF

Weapon-Target Assignment Using Genetic Algorithm (유전자 알고리즘을 이용한 무장 할당)

  • Kwon, Kyoung-Youb;Joh, Joong-Seon
    • Journal of the Korean Institute of Intelligent Systems
    • /
    • v.13 no.5
    • /
    • pp.539-544
    • /
    • 2003
  • The weapon-target assignment problem is solved using a genetic algorithm in this paper. The weapon-target assignment is an optimization problem which minimizes damages from enemy s attack or maximizes the kill probability of targets. Genetic algorithm is applied in this paper since it usually converges to a near global optimal solution. A specific structure of genetic algorithm which is suitable for the weapon-target assignment problem is proposed. A guideline selecting associated parameters is investigated through simulations. Comparition of the proposed method with several traditional optimization techniques for the weapon-target assignment problem shows the validity of the proposed method.

Information Granulation-based Fuzzy Inference Systems by Means of Genetic Optimization and Polynomial Fuzzy Inference Method

  • Park Keon-Jun;Lee Young-Il;Oh Sung-Kwun
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • v.5 no.3
    • /
    • pp.253-258
    • /
    • 2005
  • In this study, we introduce a new category of fuzzy inference systems based on information granulation to carry out the model identification of complex and nonlinear systems. Informal speaking, information granules are viewed as linked collections of objects (data, in particular) drawn together by the criteria of proximity, similarity, or functionality. To identify the structure of fuzzy rules we use genetic algorithms (GAs). Granulation of information with the aid of Hard C-Means (HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms and the least square method (LSM). The proposed model is contrasted with the performance of the conventional fuzzy models in the literature.

Prediction model of service life for tunnel structures in carbonation environments by genetic programming

  • Gao, Wei;Chen, Dongliang
    • Geomechanics and Engineering
    • /
    • v.18 no.4
    • /
    • pp.373-389
    • /
    • 2019
  • It is important to study the problem of durability for tunnel structures. As a main influence on the durability of tunnel structures, carbonation-induced corrosion is studied. For the complicated environment of tunnel structures, based on the data samples from real engineering examples, the intelligent method (genetic programming) is used to construct the service life prediction model of tunnel structures. Based on the model, the prediction of service life for tunnel structures in carbonation environments is studied. Using the data samples from some tunnel engineering examples in China under carbonation environment, the proposed method is verified. In addition, the performance of the proposed prediction model is compared with that of the artificial neural network method. Finally, the effect of two main controlling parameters, the population size and sample size, on the performance of the prediction model by genetic programming is analyzed in detail.

Optimization of Local Retail Distribution Company Problem using Genetic Algorithm (지역소매 유통회사의 효율 최적화를 위한 Genetic Algorithm의 적용)

  • Yoon, H. M.;Kim, D. W.;Ryu, K. W.
    • Journal of Korean Port Research
    • /
    • v.11 no.1
    • /
    • pp.75-83
    • /
    • 1997
  • In this paper, we codify the objective function that should be optimized by using Genetic Algorithm instead of Heuristic method to solve these problems. So, each bit that constitutes one structure can signify each commodity. Therefore, we can exchange customers without restriction if the traveling distance diminishes among the districts. Furthermore, even though the capacity of a customer's commodities exceeds that of a vehicle, the following vehicle can be allocated. Also, we obtained good result by testing with real data. To be brief, we can effectively allocate innumerable commodities, that have various magnitudes and weight, into restricted capacity of the vehicle by applying genetic algorithm that is useful in solving the problems of optimization.

  • PDF