• Title/Summary/Keyword: evolution algorithm

Search Result 640, Processing Time 0.03 seconds

An Implementation of the Controller Design System Using the Runge Kutta Method and Genetic Algorithms (런지-커타 기법과 유전자 알고리즘을 이용한 제어기 설계 시스템의 구현)

  • Lee, Chung-Ki;Kang, Hwan-Il;Yu, Il-Kyu
    • Journal of the Korean Institute of Intelligent Systems
    • /
    • v.13 no.3
    • /
    • pp.259-259
    • /
    • 2003
  • Genetic algorithms using a Process of genetic evolution of an organism are appropriate for hard problems that have not been solved by any deterministic method. Up to now, the controller design method has been made with the frequency dependent specification but the design method with the time specification has gotten little progress. In this paper, we study the controller design to satisfy the performance of a plant using the generalized Manabe standard form. When dealing with a controller design in the case of two parameter configurations, there are some situations that neither a known pseudo inverse technique nor the inverse method can be applicable. In this case, we propose two methods of designing a controller by the gradient algorithm and the new pseudo inverse method so that the desired closed polynomials are either equalized to or approximated to the designed polynomial. Design methods of the proposed controller are implemented in Java.

Synergetics based damage detection of frame structures using piezoceramic patches

  • Hong, Xiaobin;Ruan, Jiaobiao;Liu, Guixiong;Wang, Tao;Li, Youyong;Song, Gangbing
    • Smart Structures and Systems
    • /
    • v.17 no.2
    • /
    • pp.167-194
    • /
    • 2016
  • This paper investigates the Synergetics based Damage Detection Method (SDDM) for frame structures by using surface-bonded PZT (Lead Zirconate Titanate) patches. After analyzing the mechanism of pattern recognition from Synergetics, the operating framework with cooperation-competition-update process of SDDM was proposed. First, the dynamic identification equation of structural conditions was established and the adjoint vector (AV) set of original vector (OV) set was obtained by Generalized Inverse Matrix (GIM).Then, the order parameter equation and its evolution process were deduced through the strict mathematics ratiocination. Moreover, in order to complete online structural condition update feature, the iterative update algorithm was presented. Subsequently, the pathway in which SDDM was realized through the modified Synergetic Neural Network (SNN) was introduced and its assessment indices were confirmed. Finally, the experimental platform with a two-story frame structure was set up. The performances of the proposed methodology were tested for damage identifications by loosening various screw nuts group scenarios. The experiments were conducted in different damage degrees, the disturbance environment and the noisy environment, respectively. The results show the feasibility of SDDM using piezoceramic sensors and actuators, and demonstrate a strong ability of anti-disturbance and anti-noise in frame structure applications. This proposed approach can be extended to the similar structures for damage identification.

The development of a back analysis program for subsea tunnel stability under operation: transversal tunnel section (운영 중 해저 터널의 안정성 평가를 위한 역해석 프로그램 개발: 횡단방향)

  • An, Joon-Sang;Kim, Byung-Chan;Lee, Sang-Hyun;Song, Ki-Il
    • Journal of Korean Tunnelling and Underground Space Association
    • /
    • v.19 no.2
    • /
    • pp.195-212
    • /
    • 2017
  • When back analysis is used for the assessment of an operating subsea tunnel safety in various measurement information such as stress, water pressure and tunnel lining and ground stiffness degradation, the reliable results within tolerable error rate can be obtained. By utilizing a commercial geotechnical analysis program FLAC3D, back analysis can be performed with a DEA which has already been successfully validated in previous studies. However, relative more time-consumption is the drawback of this approach. For this reason, this study introduced beam-spring model-based on FEM solver which uses less analysis time relatively. Beam-spring program capable of structural analysis of a circular tunnel section was developed by using Python language and combined with the built-DEA. From the measurement datum, expected to estimate the stability of an operation tunnel close to real-time.

Swell Correction of Shallow Marine Seismic Reflection Data Using Genetic Algorithms

  • park, Sung-Hoon;Kong, Young-Sae;Kim, Hee-Joon;Lee, Byung-Gul
    • Journal of the korean society of oceanography
    • /
    • v.32 no.4
    • /
    • pp.163-170
    • /
    • 1997
  • Some CMP gathers acquired from shallow marine seismic reflection survey in offshore Korea do not show the hyperbolic trend of moveout. It originated from so-called swell effect of source and streamer, which are towed under rough sea surface during the data acquisition. The observed time deviations of NMO-corrected traces can be entirely ascribed to the swell effect. To correct these time deviations, a residual statics is introduced using Genetic Algorithms (GA) into the swell correction. A new class of global optimization methods known as GA has recently been developed in the field of Artificial Intelligence and has a resemblance with the genetic evolution of biological systems. The basic idea in using GA as an optimization method is to represent a population of possible solutions or models in a chromosome-type encoding and manipulate these encoded models through simulated reproduction, crossover and mutation. GA parameters used in this paper are as follows: population size Q=40, probability of multiple-point crossover P$_c$=0.6, linear relationship of mutation probability P$_m$ from 0.002 to 0.004, and gray code representation are adopted. The number of the model participating in tournament selection (nt) is 3, and the number of expected copies desired for the best population member in the scaling of fitness is 1.5. With above parameters, an optimization run was iterated for 101 generations. The combination of above parameters are found to be optimal for the convergence of the algorithm. The resulting reflection events in every NMO-corrected CMP gather show good alignment and enhanced quality stack section.

  • PDF

Optimization of Design Parameters of a EPPR Valve Solenoid using Artificial Neural Network (인공 신경회로망을 이용한 전자비례 감압밸브의 솔레노이드 형상 최적화)

  • Yoon, Ju Ho;Nguyen, Minh Nhat;Lee, Hyun Su;Youn, Jang Won;Kim, Dang Ju;Lee, Dong Won;Ahn, Kyoung Kwan
    • Journal of Drive and Control
    • /
    • v.13 no.2
    • /
    • pp.34-41
    • /
    • 2016
  • Unlike the commonly used On/Off solenoid, constant attraction force which is independent of plunger displacement is a considerably important characteristic to proportional solenoid of the EPPR Valve. Attraction force uniformity is mainly affected by the internal shape design parameters. Due to a number of shape design parameters, the optimal parameter values are very complex and time consuming to find by trial and error method. Much research has been conducted or are still in progress to find the optimal parameter values by applying various optimization techniques like Genetic Algorithm, Evolution Strategy, Simulated Annealing, or the Taguchi method. In this paper, the design parameters which have primary effects on the attraction force uniformity and the average attraction force are decided by main effects analysis of Design of Experiments. Optimal parameter values are derived using finite-element analysis and a neural network model.

A Study on Modified Adaptive Weighted Filter in Mixed Noise Environments (복합잡음 환경에서 변형된 적응 가중치 필터에 관한 연구)

  • Kwon, Se-Ik;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2014.10a
    • /
    • pp.798-801
    • /
    • 2014
  • Nowadays, the demand for multimedia services has grown with the rapid evolution in the digital era. But due to external causes in the process of processing, transmitting and storing image data, the images are damaged. One of the major causes of such damage is known to be noise. Some of the most commonly used methods for removing noise are CWMF(center weighted median filter), A-TMF(alpha-trimmed mean filter) and AWMF(adaptive weighted median filter). However, these filters all leave a bit to be desired in removing noise in a complex noise environment. Therefore this paper suggest an image restoration filter algorithm that first judges the noise and sets a adjustment weight based on the median value and distance of the mask to remove the complex noise. For an objective analysis, the results were compared against existing methods and the PSNR(peak signal to noise ratio) was used as a reference.

  • PDF

A Study on Intelligent Emotional Recommendation System Using Biological Information (생체정보를 이용한 지능형 감성 추천시스템에 관한 연구)

  • Kim, Tae-Yeun
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
    • /
    • v.14 no.3
    • /
    • pp.215-222
    • /
    • 2021
  • As the importance of human-computer interaction (Human Computer Interface) technology grows and research on HCI is progressing, it is inferred about the research emotion inference or the computer reaction according to the user's intention, not the computer reaction by the standard input of the user. Stress is an unavoidable result of modern human civilization, and it is a complex phenomenon, and depending on whether or not there is control, human activity ability can be seriously changed. In this paper, we propose an intelligent emotional recommendation system using music as a way to relieve stress after measuring heart rate variability (HRV) and acceleration photoplethymogram (APG) increased through stress as part of human-computer interaction. The differential evolution algorithm was used to extract reliable data by acquiring and recognizing the user's biometric information, that is, the stress index, and emotional inference was made through the semantic web based on the obtained stress index step by step. In addition, by searching and recommending a music list that matches the stress index and changes in emotion, an emotional recommendation system suitable for the user's biometric information was implemented as an application.

Evaluating LIMU System Quality with Interval Evidence and Input Uncertainty

  • Xiangyi Zhou;Zhijie Zhou;Xiaoxia Han;Zhichao Ming;Yanshan Bian
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.17 no.11
    • /
    • pp.2945-2965
    • /
    • 2023
  • The laser inertial measurement unit is a precision device widely used in rocket navigation system and other equipment, and its quality is directly related to navigation accuracy. In the quality evaluation of laser inertial measurement unit, there is inevitably uncertainty in the index input information. First, the input numerical information is in interval form. Second, the index input grade and the quality evaluation result grade are given according to different national standards. So, it is a key step to transform the interval information input by the index into the data form consistent with the evaluation result grade. In the case of uncertain input, this paper puts forward a method based on probability distribution to solve the problem of asymmetry between the reference grade given by the index and the evaluation result grade when evaluating the quality of laser inertial measurement unit. By mapping the numerical relationship between the designated reference level and the evaluation reference level of the index information under different distributions, the index evidence symmetrical with the evaluation reference level is given. After the uncertain input information is transformed into evidence of interval degree distribution by this method, the information fusion of interval degree distribution evidence is carried out by interval evidential reasoning algorithm, and the evaluation result is obtained by projection covariance matrix adaptive evolution strategy optimization. Taking a five-meter redundant laser inertial measurement unit as an example, the applicability and effectiveness of this method are verified.

Design of pRBFNNs Pattern Classifier-based Face Recognition System Using 2-Directional 2-Dimensional PCA Algorithm ((2D)2PCA 알고리즘을 이용한 pRBFNNs 패턴분류기 기반 얼굴인식 시스템 설계)

  • Oh, Sung-Kwun;Jin, Yong-Tak
    • Journal of the Institute of Electronics and Information Engineers
    • /
    • v.51 no.1
    • /
    • pp.195-201
    • /
    • 2014
  • In this study, face recognition system was designed based on polynomial Radial Basis Function Neural Networks(pRBFNNs) pattern classifier using 2-directional 2-dimensional principal component analysis algorithm. Existing one dimensional PCA leads to the reduction of dimension of image expressed by the multiplication of rows and columns. However $(2D)^2PCA$(2-Directional 2-Dimensional Principal Components Analysis) is conducted to reduce dimension to each row and column of image. and then the proposed intelligent pattern classifier evaluates performance using reduced images. The proposed pRBFNNs consist of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with the aid of fuzzy c-means clustering. In the conclusion part of rules. the connection weight of RBFNNs is represented as the linear type of polynomial. The essential design parameters (including the number of inputs and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. Using Yale and AT&T dataset widely used in face recognition, the recognition rate is obtained and evaluated. Additionally IC&CI Lab dataset is experimented with for performance evaluation.

Genetic Relationship of the Ampelopsis brevipedunculata var. heterophylla and Vitis thunbergii var. sinuata with the Other Vitis Plants (개머루와 까마귀머루의 유전적 유연관계 분석)

  • Bae, Young-Min
    • Journal of Life Science
    • /
    • v.27 no.1
    • /
    • pp.89-94
    • /
    • 2017
  • DNA sequences of the intergenic spacer 1 and intergenic spacer 2 of the nineteen plants belonging Vitis genus were collected from the Genbank. DNA sequences of the same regions of Vitis thunbergii var. sinuata and Ampelopsis brevipedunculata var. heterophylla, both common plants in Korea, were not available in Genbank. Those two plants were collected, their genomic DNA encoding 18S rRNA, intergenic spacer 1, 5.8S rRNA, intergenic spacer 2 and part of 28S rRNA amplified and DNA sequence determined. DNA sequences of twenty-one plants including two Korean plants were aligned by the Multiple sequence comparison by log-expectation(MUSCLE) algorithm and the alignment was used to calculate neighbor-joining tree and pairwise distance. The results indicate DNA sequences of the two Korean plants are highly homologous with each other, but they are quite distantly related to the other Vitis plants. Distant relationship of the two Korean plants with the other Vitis plants might be due to independent evolution of those two plants in geographically isolated environment. Those two Korean plants are classified in different genera based on the morphology, one in Vitis genus and the other in Ampelopsis genus, providing another example of discrepancy between morphological and genetic classification.