• Title/Summary/Keyword: Convergence in probability

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On Sweeping Operators for Reducing Premature Convergence of Genetic Algorithms (유전 알고리즘의 조기수렴 저감을 위한 연산자 소인방법 연구)

  • Lee, Hong-Kyu
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.12
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    • pp.1210-1218
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    • 2011
  • GA (Genetic Algorithms) are efficient for searching for global optima but may have some problems such as premature convergence, convergence to local extremum and divergence. These phenomena are related to the evolutionary operators. As population diversity converges to low value, the search ability of a GA decreases and premature convergence or converging to local extremum may occur but population diversity converges to high value, then genetic algorithm may diverge. To guarantee that genetic algorithms converge to the global optima, the genetic operators should be chosen properly. In this paper, we analyze the effects of the selection operator, crossover operator, and mutation operator on convergence properties, and propose the sweeping method of mutation probability and elitist propagation rate to maintain the diversity of the GA's population for getting out of the premature convergence. Results of simulation studies verify the feasibility of using these sweeping operators to avoid premature convergence and convergence to local extrema.

Stochastic Model based Fault Diagnosis System of Induction Motors using Online Probability Density Estimation (온라인 확률분포 추정기법을 이용한 확률모델 기반 유도전동기의 고장진단 시스템)

  • Cho, Hyun-Cheol;Kim, Kwang-Soo;Lee, Kwon-Soon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.10
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    • pp.1847-1853
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    • 2008
  • This paper presents stochastic methodology based fault detection algorithm for induction motor systems. We measure current of healthy induction motors by means of hall sensor systems and then establish its probability distribution. We propose online probability density estimation which is effective in real-time implementation due to its simplicity and low computational burden. In addition, we accomplish theoretical analysis to demonstrate convergence property of the proposed estimation by using statistical convergence and system stability theory. We apply our fault diagnosis approach to three-phase induction motors and achieve real-time experiment for evaluating its reliability and practicability in industrial fields.

A Cluster modeling using New Convergence properties (새로운 수렴특성을 이용한 클러스터 모델링)

  • Kim, Sung-Suk;Baek, Chan-Soo;Kim, Sung-Soo;Ryu, Joeng-Woong
    • Proceedings of the KIEE Conference
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    • 2004.11c
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    • pp.382-384
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    • 2004
  • In this parer, we propose a clustering that perform algorithm using new convergence properties. For detection and optimization of cluster, we use to similarity measure with cumulative probability and to inference the its parameters with MLE. A merits of using the cumulative probability in our method is very effectiveness that robust to noise or unnecessary data for inference the parameters. And we adopt similarity threshold to converge the number of cluster that is enable to past convergence and delete the other influence for this learning algorithm. In the simulation, we show effectiveness of our algorithm for convergence and optimization of cluster in riven data set.

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An Improvement of Personalized Computer Aided Diagnosis Probability for Smart Healthcare Service System (스마트 헬스케어 서비스를 위한 통계학적 개인 맞춤형 질병예측 기법의 개선)

  • Min, Byung-won
    • Journal of Convergence Society for SMB
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    • v.6 no.4
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    • pp.79-84
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    • 2016
  • A novel diagnosis scheme PCADP(personalized computer aided diagnosis probability) is proposed to overcome the problems mentioned above. PCADP scheme is a personalized diagnosis method based on ontology and it makes the bio-data analysis just a 'process' in the Smart healthcare service system. In addition, we offer a semantics modeling of the smart healthcare ontology framework in order to describe smart healthcare data and service specifications as meaningful representations based on this PCADP. The PCADP scheme is a kind of statistical diagnosis method which has real-time processing, characteristics of flexible structure, easy monitoring of decision process, and continuous improvement.

Choquet weak convergence for interval-valued capacity functionals of random sets (확률집합의 구간치 용적 범함수에 대한 쇼케이 약 수렴성에 관한 연구)

  • Jang, Lee-Chae;Kim, Tae-Kyun;Kim, Young-Hee
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.6
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    • pp.837-841
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    • 2008
  • In this paper, we consider interval probability as a unifying concept for uncertainty and Choquet integrals with resect to a capacity functional. By using interval probability, we will define an interval-valued capacity functional and Choquet integral with respect to an interval-valued capacity functional. Furthermore, we investigate Choquet weak convergence of interval-valued capacity functionals of random sets.

Contention-based Reservation MAC Protocol for Burst Traffic in Wireless Packet Networks

  • Lim, In-Taek
    • Journal of information and communication convergence engineering
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    • v.5 no.2
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    • pp.93-97
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    • 2007
  • In this paper, centralized access control and slot allocation algorithm is proposed for wireless networks. The proposed algorithm is characterized by the contention-based reservation. In order to reduce the collision probability of reservation request, the base station calculates and broadcasts the transmission probability of reservation requests, and the wireless terminal transmits its reservation request with the received transmission probability. The scheduler allocates the uplink data slots based on the successful reservation requests. Simulation results show that the proposed algorithms can provide high channel utilization, and furthermore, maintains constant delay performance in the heavy traffic environment.

Performance Analysis of S-SFR-based OFDMA Cellular Systems

  • Kim, Yi-Kang;Cho, Choong-Ho;Yoon, Seok-Ho;Kim, Seung-Yeon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.1
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    • pp.186-205
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    • 2019
  • Intercell interference coordination (ICIC) is considered as a promising technique to increase the spectral efficiency of OFDMA cellular systems. The soft frequency reuse (SFR) and fractional frequency reuse (FFR) are representative and efficient management techniques for ICIC. Herein, to enhance the performance of the SFR scheme, we propose a call admission (CAC) scheme. In this CAC scheme, called Spectrum handoff-SFR(S-SFR), the spectrum handoff technique is applied to the user equipment (UE) located near the cell center. We derive the traffic analysis model to describe the S-SFR. In addition, a two-dimensional (2-D) Markov chain and an outage analysis are used in our analytical model. From the traffic analysis, the significant performance measures are the outage probability, call blocking probability, system throughput and resource utilization. Based on those, the outage probability and system throughput are obtained using resource utilization as an interference pattern. The analytical results are verified with computer simulation results. Finally, we compare our proposed scheme with other ICI schemes.

A New Constant Modulus Algorithm based on Maximum Probability Criterion

  • Kim, Nam-Yong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.2A
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    • pp.85-90
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    • 2009
  • In this paper, as an alternative to constant modulus algorithm based on MSE, maximization of the probability that equalizer output power is equal to the constant modulus of the transmitted symbols is introduced. The proposed algorithm using the gradient ascent method to the maximum probability criterion has superior convergence and steady-state MSE performance, and the error samples of the proposed algorithm exhibit more concentrated density functions in blind equalization environments. Simulation results indicate that the proposed training has a potential advantage versus MSE training for the constant modulus approach to blind equalization.

A Weak Convergence Theorem for Mixingale Arrays

  • Hong, Dug-Hun;Kim, Hye-Kyung;Kim, Ju-Young
    • Journal of the Korean Statistical Society
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    • v.24 no.2
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    • pp.273-280
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    • 1995
  • This paper gives a generalization of an $L_1$-convergence theorem for dependent processes due to Andrews (1988) and also a probability convergence theorem.

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