• 제목/요약/키워드: probability constraints

검색결과 183건 처리시간 0.034초

Market Opportunities and Constraints Confronting Resource-Poor Pig Farmers in South Africa's Eastern Cape Province

  • Madzimure, James;Bovula, Ntombizodwa;Ngorora, Grace P.K.;Tada, Obert;Kagande, Shelton M.;Bakare, Archibold G.;Chimonyo, Michael
    • 산경연구논집
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    • 제5권2호
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    • pp.29-35
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    • 2014
  • Purpose - The study aimed to evaluate the market opportunities and constraints confronting resource-poor pig farmers in South Africa. Research design, data, and methodology - Information was collected from 292 households in three municipalities through interviews with key informants. The data collected included socio-economic characteristics, major market channels, prices for different pig classes, average weight of the pigs on sale, number of pigs sold annually, and preferred meat quality attributes. Results - In Ngqushwa, 96% of respondents sold pigs as compared to Elundini (81%) and Ntabankulu (65%). Less resource-poor households and those with market-oriented production had large herdsizes (P < 0.05) when compared to more resource-poor farmers. The probability of selling pigs was high for the backyard production system and educated farmers. For all farmers, opportunities included high pork demand, good prices, employment creation, and a niche market for organically produced indigenous pork. Constraints include disease, feed shortages for large herds, distances to formal markets, lack of training, and drugs. Conclusions - Constraints outnumbered opportunities for the resource-poor pig farmers.

순차적 샘플링과 크리깅 메타모델을 이용한 신뢰도 기반 최적설계 (Reliability-Based Design Optimization Using Kriging Metamodel with Sequential Sampling Technique)

  • 최규선;이갑성;최동훈
    • 대한기계학회논문집A
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    • 제33권12호
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    • pp.1464-1470
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    • 2009
  • RBDO approach based on a sampling method with the Kriging metamodel and Constraint Boundary Sampling (CBS), which is sequential sampling method to generate metamodels is proposed. The major advantage of the proposed RBDO approach is that it does not require Most Probable failure Point (MPP) which is essential for First-Order Reliability Method (FORM)-based RBDO approach. The Monte Carlo Sampling (MCS), most well-known method of the sampling methods for the reliability analysis is used to assess the reliability of constraints. In addition, a Cumulative Distribution Function (CDF) of the constraints is approximated using Moving Least Square (MLS) method from empirical distribution function. It is possible to acquire a probability of failure and its analytic sensitivities by using an approximate function of the CDF for the constraints. Moreover, a concept of inactive design is adapted to improve a numerical efficiency of the proposed approach. Computational accuracy and efficiency of the proposed RBDO approach are demonstrated by numerical and engineering problems.

Multiperiod Mean Absolute Deviation Uncertain Portfolio Selection

  • Zhang, Peng
    • Industrial Engineering and Management Systems
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    • 제15권1호
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    • pp.63-76
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    • 2016
  • Multiperiod portfolio selection problem attracts more and more attentions because it is in accordance with the practical investment decision-making problem. However, the existing literature on this field is almost undertaken by regarding security returns as random variables in the framework of probability theory. Different from these works, we assume that security returns are uncertain variables which may be given by the experts, and take absolute deviation as a risk measure in the framework of uncertainty theory. In this paper, a new multiperiod mean absolute deviation uncertain portfolio selection models is presented by taking transaction costs, borrowing constraints and threshold constraints into account, which an optimal investment policy can be generated to help investors not only achieve an optimal return, but also have a good risk control. Threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Based on uncertain theories, the model is converted to a dynamic optimization problem. Because of the transaction costs, the model is a dynamic optimization problem with path dependence. To solve the new model in general cases, the forward dynamic programming method is presented. In addition, a numerical example is also presented to illustrate the modeling idea and the effectiveness of the designed algorithm.

Reliability-Based Topology Optimization with Uncertainties

  • Kim Chwa-Il;Wang Se-Myung;Bae Kyoung-Ryun;Moon Hee-Gon;Choi Kyung-K.
    • Journal of Mechanical Science and Technology
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    • 제20권4호
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    • pp.494-504
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    • 2006
  • This research proposes a reliability-based topology optimization (RBTO) using the finite element method. RBTO is a topology optimization based on probabilistic (or reliability) constraints. Young's modulus, thickness, and loading are considered as the uncertain variables and RBTO is applied to static and eigenvalue problems. The RBTO problems are formulated and a sensitivity analysis is performed. In order to compute probability constraints, two methods-RIA and PMA-are used. Several examples show the effectiveness of the proposed method by comparing the classical safety factor method.

Controller optimization with constraints on probabilistic peak responses

  • Park, Ji-Hun;Min, Kyung-Won;Park, Hong-Gun
    • Structural Engineering and Mechanics
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    • 제17권3_4호
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    • pp.593-609
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    • 2004
  • Peak response is a more suitable index than mean response in the light of structural safety. In this study, a controller optimization method is proposed to restrict peak responses of building structures subject to earthquake excitations, which are modeled as partially stationary stochastic process. The constraints are given with specified failure probabilities of peak responses. LQR is chosen to assure stability in numerical process of optimization. Optimization problem is formulated with weightings on controlled outputs as design variables and gradients of objective and constraint functions are derived. Full state feedback controllers designed by the proposed method satisfy various design objectives and output feedback controllers using LQG also yield similar results without significant performance deterioration.

Development of an Item Selection Method for Test-Construction by using a Relationship Structure among Abilities

  • Kim, Sung-Ho;Jeong, Mi-Sook;Kim, Jung-Ran
    • Communications for Statistical Applications and Methods
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    • 제8권1호
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    • pp.193-207
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    • 2001
  • When designing a test set, we need to consider constraints on items that are deemed important by item developers or test specialists. The constraints are essentially on the components of the test domain or abilities relevant to a given test set. And so if the test domain could be represented in a more refined form, test construction would be made in a more efficient way. We assume that relationships among task abilities are representable by a causal model and that the item response theory (IRT) is not fully available for them. In such a case we can not apply traditional item selection methods that are based on the IRT. In this paper, we use entropy as an uncertainty measure for making inferences on task abilities and developed an optimal item selection algorithm which reduces most the entropy of task abilities when items are selected from an item pool.

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Constraining Cosmological Parameters with Gravitational Lensed Quasars in the Sloan Digital Sky Survey

  • Han, Du-Hwan;Park, Myeong-Gu
    • 천문학회보
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    • 제39권1호
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    • pp.34-34
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    • 2014
  • We investigate the constraints on the matter density ${\Omega}m$ and the cosmological constant ${\Omega}{\Lambda}$ using the gravitational lensed QSO (Quasi Stellar Object) systems from the Sloan Digital Sky Survey (SDSS) by analyzing the distribution of image separation. The main sample consists of 16 QSO lens systems with measured source and lens redshifts. We use a lensing probability that is simply defined by the gaussian distribution. We perform the curvature test and the constraints on the cosmological parameters as the statistical tests. The statistical tests have considered well-defined selection effects and adopt parameter of velocity dispersion function. We also applied the same analysis to Monte-Carlo generated mock gravitational lens samples to assess the accuracy and limit of our approach. As the results of these statistical tests, we find that only the excessively positively curved universe (${\Omega}m+{\Omega}{\Lambda}$ > 1) are rejected at 95% confidence level. However, if the informations of the galaxy as play a lens are measured accurately, we confirm that the gravitational lensing statistics would be the most powerful tool.

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신뢰도지수와 목표성능치에 기반한 확률론적 구조설계 최적화기법에 대한 비교연구 (A Comparative Study on Reliability Index and Target Performance Measure Based Probabilistic Structural Design Optimizations)

  • 양영순;이재옥
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 2000년도 가을 학술발표회논문집
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    • pp.32-39
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    • 2000
  • Probabilistic structural design optimization, which is characterized by the so-called probabilistic. constraints which introduce permissible probability of violation, is preferred to deterministic design optimization since unpredictable inherent uncertainties and randomness in structural and environmental properties are to be taken quantitatively into account by probabilistic design optimization. In this paper, the well-known reliability index based MPFP(Most Probable Failure Point) search approach and the newly introduced target performance measure based MPTP(Minimum Performance Target Point) search approach are summarized and compared. The present comparison focuses on the number of iterations required for the estimation of probabilistic constraints and a technique for improvement which removes exhaustive iterations is presented as well. A 10 bar truss problem is examined for this.

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Worst Closed-Loop Controlled Bulk Distributions of Stochastic Arrival Processes for Queue Performance

  • Lee Daniel C.
    • Journal of Communications and Networks
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    • 제7권1호
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    • pp.87-92
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    • 2005
  • This paper presents basic queueing analysis contributing to teletraffc theory, with commonly accessible mathematical tools. This paper studies queueing systems with bulk arrivals. It is assumed that the number of arrivals and the expected number of arrivals in each bulk are bounded by some constraints B and (equation omitted), respectively. Subject to these constraints, convexity argument is used to show that the bulk-size probability distribution that results in the worst mean queue performance is an extremal distribution with support {1, B} and mean equal to A. Furthermore, from the viewpoint of security against denial-of-service attacks, this distribution remains the worst even if an adversary were allowed to choose the bulk-size distribution at each arrival instant as a function of past queue lengths; that is, the adversary can produce as bad queueing performance with an open-loop strategy as with any closed-loop strategy. These results are proven for an arbitrary arrival process with bulk arrivals and a general service model.

An efficient Ambiguity searching method with constraints for attitude finding GPS receivers

  • Nam, Sung-Il;Son, Seok-Bo;Park, Chan-Sik;Lee, Sang-Jeong
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.61.1-61
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    • 2001
  • This paper describes an efficient ambiguity searching method using additional constraints in 3-dimentional attitude finding GPS receiver design. For determining the integer ambiguity, the baseline length constraint, the angle constraint, the velocity constraint and the attitude constraint can be used for reducing the searching space. This paper describes the searching space algebraically and graphically. It is confirmed that the described restrictions are reasonable and the speed and the probability of ambiguity fixing are improved when the restricted searching spaces are applied Moreover, it is possible to design receivers of better quality by applying the method proposed in this paper.

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