• Title/Summary/Keyword: Optimum selection probability

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Optimum Selection Probabilites in Stratified Two-stage Sampling (층화 이단계 표본추출시 최적 선택율)

  • 신민웅;오상훈
    • The Korean Journal of Applied Statistics
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    • v.14 no.2
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    • pp.429-437
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    • 2001
  • 단순 이단계 표본 추출의 경우에 최적 선택률은 Hansen과 Hurwitz(1949)에 의하여 구하여졌다. 그러나 통계청에서 실시하는 표본조사등은 층화 이단계 추출을 한다. 따라서 실제적인 필요성에 의하여 층화 2단계 표본 설계를 시도 하였다. 층화 이단계 표본추출시에 주어진 비용아래서 모총계의 추정량의 분산을 최소로 하는 최적의 선택확률(optimum selection probability), 표본추출율과 부차 표본추출율을 Lagrangean 승수법에 의하여 구한다.

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Economical selection of optimum pressurized hollow fiber membrane modules in water purification system using RbLCC

  • Lee, Chul-sung;Nam, Young-wook;Kim, Doo-il
    • Membrane and Water Treatment
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    • v.8 no.2
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    • pp.137-147
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    • 2017
  • A water treatment utility in South Korea operates a large system of pressurized hollow fiber membrane (PHFM) modules. The optimal selection of membrane module for the full scale plant was critical issue and carried out using Risk-based Life Cycle Cost (RbLCC) analysis based on the historical data of operation and maintenance. The RbLCC analysis was used in the process of decision-making for replacing aged modules. The initial purchasing cost and the value at risk during operation were considered together. The failure of modules occurs stochastically depending on the physical deterioration with usage over time. The life span of module was used as a factor for the failure of Poisson's probability model, which was used to obtain the probability of failure during the operation. The RbLCC was calculated by combining the initial cost and the value at risk without its warranty term. Additionally, the properties of membrane were considered to select the optimum product. Results showed that the module's life span in the system was ten years (120 month) with safety factor. The optimum product was selected from six candidates membrane for a full scale water treatment facility. This method could be used to make the optimum and rational decision for the operation of membrane water purification facility.

Evaluating the Performance of Four Selections in Genetic Algorithms-Based Multispectral Pixel Clustering

  • Kutubi, Abdullah Al Rahat;Hong, Min-Gee;Kim, Choen
    • Korean Journal of Remote Sensing
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    • v.34 no.1
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    • pp.151-166
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    • 2018
  • This paper compares the four selections of performance used in the application of genetic algorithms (GAs) to automatically optimize multispectral pixel cluster for unsupervised classification from KOMPSAT-3 data, since the selection among three main types of operators including crossover and mutation is the driving force to determine the overall operations in the clustering GAs. Experimental results demonstrate that the tournament selection obtains a better performance than the other selections, especially for both the number of generation and the convergence rate. However, it is computationally more expensive than the elitism selection with the slowest convergence rate in the comparison, which has less probability of getting optimum cluster centers than the other selections. Both the ranked-based selection and the proportional roulette wheel selection show similar performance in the average Euclidean distance using the pixel clustering, even the ranked-based is computationally much more expensive than the proportional roulette. With respect to finding global optimum, the tournament selection has higher potential to reach the global optimum prior to the ranked-based selection which spends a lot of computational time in fitness smoothing. The tournament selection-based clustering GA is used to successfully classify the KOMPSAT-3 multispectral data achieving the sufficient the matic accuracy assessment (namely, the achieved Kappa coefficient value of 0.923).

Optimal Design of Water Distribution Networks using the Genetic Algorithms:(II) -Sensitivity Analysis- (Genetic Algorithm을 이용한 상수관망의 최적설계: (II) -민감도 분석을 중심으로-)

  • Shin, Hyun-Gon;Park, Heekyun
    • Journal of Korean Society of Water and Wastewater
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    • v.12 no.2
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    • pp.50-58
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    • 1998
  • Genetic Algorithm (GA) consists of selection, reproduction, crossover and mutation processes and many parameters including population size, generation number, the probability of crossover (Pc) and the probability of mutation (Pm). Determining values of the parameters is found critical in the whole optimization process and a sensitivity analysis with them seems mandatory. This paper tries to demonstrate such importance of sensitivity analysis of GA using an example water supply tunnel network of the New York City. For optimization of the network with GA, Pc and Pm vary from 0.5 to 0.9 by an increment of 0.1 and from 0.01 to 0.05 by an increment of 0.01, respectively, while fixing both the population size and the generation number to 100. This sensitivity analysis results in an optimum design of 22.3879 million dollars at the values of 0.8 and 0.01 for Pc and Pm, respectively. In addition, the probability of recombination (Pr) is introduced to check its applicability in the GA optimization of water distribution network. When Pr is 0.05 with the same values of Pc and Pm as above, the optimum design costs 20.9077 million dollars. This is lower than the cost of 22.3879 million dollars for the case of not using Pr by 6.6%. These results indicate that conducting a sensitivity analysis with parameter values and using Pr are useful in the optimization of WDN.

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Improved marine predators algorithm for feature selection and SVM optimization

  • Jia, Heming;Sun, Kangjian;Li, Yao;Cao, Ning
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.4
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    • pp.1128-1145
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    • 2022
  • Owing to the rapid development of information science, data analysis based on machine learning has become an interdisciplinary and strategic area. Marine predators algorithm (MPA) is a novel metaheuristic algorithm inspired by the foraging strategies of marine organisms. Considering the randomness of these strategies, an improved algorithm called co-evolutionary cultural mechanism-based marine predators algorithm (CECMPA) is proposed. Through this mechanism, search agents in different spaces can share knowledge and experience to improve the performance of the native algorithm. More specifically, CECMPA has a higher probability of avoiding local optimum and can search the global optimum quickly. In this paper, it is the first to use CECMPA to perform feature subset selection and optimize hyperparameters in support vector machine (SVM) simultaneously. For performance evaluation the proposed method, it is tested on twelve datasets from the university of California Irvine (UCI) repository. Moreover, the coronavirus disease 2019 (COVID-19) can be a real-world application and is spreading in many countries. CECMPA is also applied to a COVID-19 dataset. The experimental results and statistical analysis demonstrate that CECMPA is superior to other compared methods in the literature in terms of several evaluation metrics. The proposed method has strong competitive abilities and promising prospects.

An Input Feature Selection Method Applied to Fuzzy Neural Networks for Signal Estimation

  • Na, Man-Gyun;Sim, Young-Rok
    • Nuclear Engineering and Technology
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    • v.33 no.5
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    • pp.457-467
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    • 2001
  • It is well known that the performance of a fuzzy neural network strongly depends on the input features selected for its training. In its applications to sensor signal estimation, there are a large number of input variables related with an output As the number of input variables increases, the training time of fuzzy neural networks required increases exponentially. Thus, it is essential to reduce the number of inputs to a fuzzy neural network and to select the optimum number of mutually independent inputs that are able to clearly define the input-output mapping. In this work, principal component analysis (PCA), genetic algorithms (CA) and probability theory are combined to select new important input features. A proposed feature selection method is applied to the signal estimation of the steam generator water level, the hot-leg flowrate, the pressurizer water level and the pressurizer pressure sensors in pressurized water reactors and compared with other input feature selection methods.

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Optimum Selection of Equalizer Taps Losing Noise Power Estimation (잡음 전력 추정을 이용한 등화기 탭의 최적 선택 방법)

  • 성원진;신동준
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.26 no.12A
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    • pp.1971-1977
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    • 2001
  • Multipath Rayleigh fading channels for mobile radio transmission can be represented by the linear filter model, and depending on the delay path characteristics, only a selected number of taps may have significance in the receiver structure design. By using tap-selective equalization, reduction in both processing complexity and power consumption can be obtained. In this paper, we present an optimal tap selection method for a given channel model, and demonstrate the performance improvement over an existing method. We show the method performs the CFAR (Constant False Alarm Rate) detection when the noise power information is available, and derive exact expressions of the error probability for the case of noise power estimation. Using the derived formulas and simulation results, it is demonstrated that the error probability quickly approaches to the optimal performance as the number samples used for the noise power estimation increases.

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Mesh selectivity of monofilament and multifilament nylon trammel net for marbled sole(Pleuronectes yokohamae) in the western sea of Korea (서해안 문치가자미 삼중망의 망지 재료에 따른 망목선택성)

  • KIM, In-Ok;PARK, Chang-Doo;CHO, Sam-Kwang;KIM, Hyun-Young;CHA, Bong-Jin;LEE, Gun-Ho
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.51 no.3
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    • pp.302-311
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    • 2015
  • A series of field tests to estimate the size selectivity of monofilament and multifilament gill net for marbled sole, Pleuronectes yokohamae, were carried out 12 times with five different mesh sizes (86.6, 101.0, 121.2, 137.7 and 151.5mm) in the western sea of Korea from 2007 to 2009. The master selection curve was estimated by the extended Kitahara's method. The total number of catch species was 23 and that of catch was 1,688 in the field tests. Marbled sole of total catch was 1,150 with 68.1 percent. In the monofilament trammel net, the optimum value of total length (TL) per mesh size (m) for 1.0 of retention probability was estimated 0.280 and the values of TL/m were estimated to be 0.187, 0.201, 0.210, 0.218 and 0.226 when the retention probability were 0.1, 0.2, 0.3, 0.4 and 0.5, respectively. In the multifilament trammel net, the optimum value of TL/m for 1.0 of retention probability was estimated 0.307 and the values of TL/m were estimated to be 0.195, 0.211, 0.222, 0.232 and 0.241 when the retention probability were 0.1, 0.2, 0.3, 0.4 and 0.5, respectively.

Optimum Power Allocation of Cooperative NOMA Systems based on User Relay (사용자 릴레이를 채택한 협동 NOMA 시스템의 최적 전력할당)

  • Kim, Nam-Soo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.5
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    • pp.25-33
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    • 2017
  • NOMA (Non-orthogonal multiple access) system becoming a strong candidate for 5G cellular system of its high spectral efficiency. This paper considers an optimal power allocation scheme to minimize the outage probability of a user relay based cooperative NOMA system. We first derive the outage probabilities of the relay user (RU) and the destination user (DU) with selection combining. Based on these probabilities, the outage probability of the cooperative NOMA system is obtained. The analytical results are verified by Monte Carlo simulation. It is noticed that the outage probability of cooperative NOMA system has a convex function, the optimum power allocation coefficient, which satisfied the minimum outage probability, is calculated. Numerical examples show that the optimal power allocation coefficient increases with the required capacity of DU. While the capacity of DU is fixed, we noticed that the increase of the required capacity of RU decreases the optimal power allocation coefficient.

Optimal Design of Water Distribution Networks using the Genetic Algorithms: (I) -Cost optimization- (Genetic Algorithm을 이용한 상수관망의 최적설계: (I) -비용 최적화를 중심으로-)

  • Shin, Hyun-Gon;Park, Hee-Kyung
    • Journal of Korean Society of Water and Wastewater
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    • v.12 no.1
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    • pp.70-80
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    • 1998
  • Many algorithms to find a minimum cost design of water distribution network (WDN) have been developed during the last decades. Most of them have tried to optimize cost only while satisfying other constraining conditions. For this, a certain degree of simplification is required in their calculation process which inevitably limits the real application of the algorithms, especially, to large networks. In this paper, an optimum design method using the Genetic Algorithms (GA) is developed which is designed to increase the applicability, especially for the real world large WDN. The increased to applicability is due to the inherent characteristics of GA consisting of selection, reproduction, crossover and mutation. Just for illustration, the GA method is applied to find an optimal solution of the New York City water supply tunnel. For the calculation, the parameter of population size and generation number is fixed to 100 and the probability of crossover is 0.7, the probability of mutation is 0.01. The yielded optimal design is found to be superior to the least cost design obtained from the Linear Program method by $4.276 million.

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