• Title/Summary/Keyword: convergence in probability

Search Result 537, Processing Time 0.022 seconds

Structural Topology Design Using Compliance Pattern Based Genetic Algorithm (컴플라이언스 패턴 기반 유전자 알고리즘을 이용한 구조물 위상설계)

  • Park, Young-Oh;Min, Seung-Jae
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.33 no.8
    • /
    • pp.786-792
    • /
    • 2009
  • Topology optimization is to find the optimal material distribution of the specified design domain minimizing the objective function while satisfying the design constraints. Since the genetic algorithm (GA) has its advantage of locating global optimum with high probability, it has been applied to the topology optimization. To guarantee the structural connectivity, the concept of compliance pattern is proposed and to improve the convergence rate, small number of population size and variable probability in genetic operators are incorporated into GA. The rank sum weight method is applied to formulate the fitness function consisting of compliance, volume, connectivity and checkerboard pattern. To substantiate the proposed method design examples in the previous works are compared with respect to the number of function evaluation and objective function value. The comparative study shows that the compliance pattern based GA results in the reduction of computational cost to obtain the reasonable structural topology.

Probabilistic Prediction Model for the Cyclic Freeze-Thaw Deteriorations in Concrete Structures (콘크리트 구조물의 반복적 동결융해에 의한 확률론적 열화예측모델)

  • Cho, Tae-Jun
    • Proceedings of the Korea Concrete Institute Conference
    • /
    • 2006.11a
    • /
    • pp.957-960
    • /
    • 2006
  • In order to predict the accumulated damages by cyclic freeze-thaw, a regression analysis by the Response Surface Method (RSM) is used. RSM has merits when the other probabilistic simulation techniques can not guarantee the convergence of probability of occurrence or when the others can not differentiate the derivative terms of limit state functions, which are composed of random design variables in the model of complex system or the system having higher reliability. For composing limit state function, the important parameters for cyclic freeze-thaw-deterioration of concrete structures, such as water to cement ratio, entrained air pores, and the number of cycles of freezing and thawing, are used as input parameters of RSM. The predicted results of relative dynamic modulus and residual strains after 300 cycles of freeze-thaw for specimens show very good agreements with the experimental results. The RSM result can be used to predict the probability of occurrence for designer specified critical values. Therefore, it is possible to evaluate the life cycle management of concrete structures considering the accumulated damages by the cyclic freeze-thaw by the use of proposed prediction method.

  • PDF

An Experimental Study on the Prospect Theory (전망이론에 관한 실험연구)

  • Guahk, Seyoung
    • Journal of Digital Convergence
    • /
    • v.15 no.11
    • /
    • pp.107-112
    • /
    • 2017
  • This paper performed an experimental study to test the validity of the prospect theory proposed by Tversky and Kahneman as an alternative to the expected utility theory. 115 college students attended the hypothetical games to choose one of two lotteries, one is safe option while the other one is risky. The risky options were set up to have low, medium or high probability of payoffs or losses. The amount of payoffs and losses of the lotteries was either large or small. Maximum likelihood estimation of the hypothetical games have shown that in case of high probability of positive payoffs the respondents were risk averse and when the probability of positive payoffs were small the respondents were risk loving. when the possibility of loss is high they were risk loving, while the probability is of loss is low the respondents were found to be risk averse. When the probability of risky options were medium the results were significant statistically in case of only losses. The amount of positive payoff or losses does not affect the results. Overall the results of this experiments support the prospect theory more than those of Laury & Holts (2008).

Can Minimum Wage Policy Increase Personal Income? -Evidence from China

  • Fan YANG;Shuang ZHANG;Ya-Hao LI
    • Journal of Wellbeing Management and Applied Psychology
    • /
    • v.6 no.4
    • /
    • pp.1-10
    • /
    • 2023
  • Purpose: As an important provision to protect the rights and interests of low-income groups, it is worth studying whether the minimum wage policy can improve the quality of life for people. Research design, data and methodology: Using data from the 2015 and 2017 China General Social Survey (CGSS), this paper employs the logit model to estimate the probability of an individual's annual income being higher than the per capita disposable income of their province. It also utilizes the DID model to analyze the impact of minimum wage increases on individuals' annual incomes. Results: The analysis reveals that an overall increase in the minimum wage raises the probability of an individual's annual income exceeding the per capita disposable income by 3%. Among them, the probability increased by 2.2% for males and by 3.2% for females. Furthermore, the impact of the minimum wage on annual income varies depending on the individual's income level. Notably, the most positive and significant impact is observed for individuals whose income level is close to the minimum wage standard. Conclusions: This provides evidence that the increase in the minimum wage has effectively improved the quality of life for the population.

Comparative Evaluation of Machine Learning Models for Predicting Soccer Injury Types

  • Davronbek Malikov;Jaeho Kim;Jung Kyu Park
    • Journal of the Korean Society of Industry Convergence
    • /
    • v.27 no.2_1
    • /
    • pp.257-268
    • /
    • 2024
  • Soccer is type of sport that carries a high risk of injury. Injury is not only cause in the unlucky soccer carrier and also team performance as well as financial effects can be worse since soccer is a team-based game. The duration of recovery from a soccer injury typically relies on its type and severity. Therefore, we conduct this research in order to predict the probability of players injury type using machine learning technologies in this paper. Furthermore, we compare different machine learning models to find the best fit model. This paper utilizes various supervised classification machine learning models, including Decision Tree, Random Forest, K-Nearest Neighbors (KNN), and Naive Bayes. Moreover, based on our finding the KNN and Decision models achieved the highest accuracy rates at 70%, surpassing other models. The Random Forest model followed closely with an accuracy score of 62%. Among the evaluated models, the Naive Bayes model demonstrated the lowest accuracy at 56%. We gathered information about 54 professional soccer players who are playing in the top five European leagues based on their career history. We gathered information about 54 professional soccer players who are playing in the top five European leagues based on their career history.

Stable Model for Active Contour based Region Tracking using Level Set PDE

  • Lee, Suk-Ho
    • Journal of information and communication convergence engineering
    • /
    • v.9 no.6
    • /
    • pp.666-670
    • /
    • 2011
  • In this paper, we propose a stable active contour based tracking method which utilizes the bimodal segmentation technique to obtain a background color diminished image frame. The proposed method overcomes the drawback of the Mansouri model which is liable to fall into a local minimum state when colors appear in the background that are similar to the target colors. The Mansouri model has been a foundation for active contour based tracking methods, since it is derived from a probability based interpretation. By stabilizing the model with the proposed speed function, the proposed model opens the way to extend probability based active contour tracking for practical applications.

Relaxational stereo matching using adaptive support between disparities (변이간의 적응적 후원을 이용한 이완 스테레오 정합)

  • 도경훈;김용숙;하영호
    • Journal of the Korean Institute of Telematics and Electronics B
    • /
    • v.33B no.3
    • /
    • pp.69-78
    • /
    • 1996
  • This paper presetns an iterative relaxation method for stereo matching using matching probability and compatibility coefficients between disparities. Stereo matching can be considered as the labeling problem of assigning unique matches to feature points of image an relaxation labelin gis an iterative procedure which reduces local ambiguities and achieves global consistency. the relation between disparities is determined from highly reliable matches in initial matching and quantitatively expressed in temrs of compatibility coefficient. The matching results of neighbor pixels support center pixel through compatibility coefficients and update its matching probability. The proposed adaptive method reduces the degradtons on the discontinuities of disparity areas and obtains fast convergence.

  • PDF

MEAN CONVERGENCE THEOREMS AND WEAK LAWS OF LARGE NUMBERS FOR DOUBLE ARRAYS OF RANDOM ELEMENTS IN BANACH SPACES

  • Dung, Le Van;Tien, Nguyen Duy
    • Bulletin of the Korean Mathematical Society
    • /
    • v.47 no.3
    • /
    • pp.467-482
    • /
    • 2010
  • For a double array of random elements {$V_{mn};m{\geq}1,\;n{\geq}1$} in a real separable Banach space, some mean convergence theorems and weak laws of large numbers are established. For the mean convergence results, conditions are provided under which $k_{mn}^{-\frac{1}{r}}\sum{{u_m}\atop{i=1}}\sum{{u_n}\atop{i=1}}(V_{ij}-E(V_{ij}|F_{ij})){\rightarrow}0$ in $L_r$ (0 < r < 2). The weak law results provide conditions for $k_{mn}^{-\frac{1}{r}}\sum{{T_m}\atop{i=1}}\sum{{\tau}_n\atop{j=1}}(V_{ij}-E(V_{ij}|F_{ij})){\rightarrow}0$ in probability where {$T_m;m\;{\geq}1$} and {${\tau}_n;n\;{\geq}1$} are sequences of positive integer-valued random variables, {$k_{mn};m{{\geq}}1,\;n{\geq}1$} is an array of positive integers. The sharpness of the results is illustrated by examples.

Industrial Engineering as a Multidisciplinary Field : Exploring the Structure of Academic Convergence in Industrial Engineering by Journal Citation Network Analysis (융합 학문으로서의 산업공학 : 학술지 인용 네트워크 분석을 활용한 산업공학의 학문적 융합 구조 탐색)

  • Jeong, Bokwon;Lee, Hakyeon
    • Journal of Korean Institute of Industrial Engineers
    • /
    • v.42 no.3
    • /
    • pp.182-197
    • /
    • 2016
  • One of the distinctive characteristics of industrial engineering (IE) is its multidisciplinarity. This paper explores the multidisciplinary nature of IE using journal citation network analysis. Using the relatedness indexes of IE journals obtained from journal citation report (JCR), we firstly construct the IE network only composed of 26 IE journals. The resulting IE network is partitioned into three sub-networks: management engineering, manufacturing/quality, and ergonomics. We then propose the IE convergence network which includes 81 related journals in other disciplines as well as 26 IE journals. Scrutinizing the IE convergence network reveals that IE has a high degree of interactions with seven disciplines : Operations Research and Management Science, Statistics and Probability, Manufacturing Engineering, Computer Science, Engineering Design, Business Management, Human Factors and Ergonomics. We investigate the contributions of the related disciplines to IE as well as contributions of IE to the related disciplines. The role of IE journals in exchanging knowledge with related disciplines is also identified by brokerage analysis. It is shown that visualizing and analyzing the IE convergence network can provide an excellent overview of the multidisciplinary structure of IE, which can help IE researchers easily grasp the state-of-the art of IE research.

Development of Probability-Based Assessment Index for Docking Process Assessment (무인잠수정의 도킹 과정 평가를 위한 확률 기반 평가지표 개발)

  • Chon, Seung-jae;Kim, Joon-young;Choi, Joong-lak;Jeong, Seong-hoon;Kim, Jong-hwa
    • Journal of Advanced Navigation Technology
    • /
    • v.25 no.3
    • /
    • pp.177-184
    • /
    • 2021
  • This paper proposes an assessment method using probability-based index for safe and successful underwater docking of autonomous underwater vehicles(AUVs) to the docking stations(DSs). The proposed method assesses the probability of docking according to the degree to which the state of the AUV is consistent with the state criteria for docking. The assessment is performed within a specific area considering the kinematic constraints and docking plans of the AUV. The assessment process is defining probability density function, calculating probabilities for reaching the docking station according to the difference to position and heading criteria, and computing the probability-based index in real-time. We verify the validity of the proposed method through analyzing the data acquired on operation test.