• Journal of applied mathematics & informatics
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• 제9권1호
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• pp.61-76
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• 2002

The robust non-fragile guaranteed cost control problem is studied in this paper for class of uncertain linear large-scale systems with time-varying delays in subsystem interconnections and given quadratic cost functions. The uncertainty in the system is assumed to be norm-hounded arid time-varying. Also, the state-feedback gains for subsystems of the large-scale system are assumed to have norm-bounded controller gain variations. The problem is to design state feedback control laws such that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound far all admissible uncertainties. Sufficient conditions for the existence of such controllers are derived based on the linear matrix inequality (LMI) approach combined with the Lyapunov method. A parameterized characterization of the robust non-fragile guaranteed cost contrellers is 7iven in terms of the feasible solution to a certain LMI. Finally, in order to show the application of the proposed method, a numerical example is included.

• Journal of Electrical Engineering and Technology
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• 제7권4호
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• pp.501-512
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• 2012

Social welfare maximization in a double-sided auction market is performed by implementing an aggregation-based particle swarm optimization (CAPSO) algorithm for optimal placement and sizing of one Static Synchronous Series Compensator (SSSC) device. Dallied simulation results (without/with line flow constraints and without/with SSSC) are generated to demonstrate the impact of SSSC on the congestion levels of the modified IEEE 14-bus test system. The proposed CAPSO algorithm employs conventional quadratic smooth and augmented quadratic nonsmooth generator cost curves with sine components to improve the accurate of the model by incorporating the valve loading effects. CAPSO also employs quadratic smooth consumer benefit functions. The proposed approach relies on particle swarm optimization to capture the near-optimal GenCos and DisCos, as well as the location and rating of SSSC while the Newton based load flow solution minimizes the mismatch equations. Simulation results of the proposed CAPSO algorithm are compared to solutions obtained by sequential quadratic programming (SQP) and a recently implemented Fuzzy based genetic algorithm (Fuzzy-GA). The main contributions are inclusion of customer benefit in the congestion management objective function, consideration of nonsmooth generator characteristics and the utilization of a coordinated aggregation-based PSO for locating/sizing of SSSC.

• 대한산업공학회지
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• 제2권1호
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• pp.85-92
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• 1976

In this paper, the employment planning model is developed which is a decision-making model for determining the optimum employment level with respect to varying net manpower requirement for each planing period such that total cost in a planning horizon is minimized. It is constructed as a nonlinear programming model and a dynamic programming model on the basis of studies in the areas of production smoothing and manpower scheduling. Costs for a planning period are categorized into regular wage cost, hiring cost, and overtime cost. The first is a linear function. The other two cost functions are of quadratic nature. The planning horizon of this planning model is intermediate range (five years) for which a fair planning accuracy can be guaranteed. The model considers learning period for each job class. It is simple and an optimum solution can be easily obtained by direct search techniques.

• 대한산업공학회지
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• 제25권4호
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• pp.517-526
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• 1999

This paper deals with two economic optimal designs of constant-stress accelerated life test(ALT) where failure distribution follows one of location-scale family, i. e., exponential, Weibull, and lognormal distributions which have been ones of the popular choices of failure distributions. Two optimization criteria to develop ALT plans are the statistical efficiency per unit expected cost which consists of the fixed test cost, cost being proportional to the number of test units, and variable test cost depending on test period and stress level, and the expected loss which combines Taguchi's quadratic loss function and expected test cost. Optimum plan determines the low stress level, test units allocated to each stress, and censoring times at two stress levels under Type I censoring. The proposed ALT plans are illustrated with a numerical example and sensitivity analyses are conducted to study effects of pre-estimates of design parameters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권8호
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• pp.3519-3533
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• 2020

Tuberculosis is a chronic and delayed infection which is easily experienced by young people. According to the statistics of the World Health Organization (WHO), there are nearly ten million fell ill with tuberculosis and a total of 1.5 million people died from tuberculosis in 2018 (including 251000 people with HIV). Tuberculosis is the largest single infectious pathogen that leads to death. In order to help doctors with tuberculosis diagnosis, we compare the tuberculosis classification abilities of six popular convolutional neural network (CNN) models in the same data set to find the best model. Before training, we optimize three parts of CNN to achieve better results. We employ sigmoid function to replace the step function as the activation function. What's more, we use binary cross entropy function as the cost function to replace traditional quadratic cost function. Finally, we choose stochastic gradient descent (SGD) as gradient descent algorithm. From the results of our experiments, we find that Densenet121 is most suitable for tuberculosis diagnosis and achieve a highest accuracy of 0.835. The optimization and expansion depend on the increase of data set and the improvements of Densenet121.

• 한국인터넷방송통신학회논문지
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• 제15권5호
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• pp.155-162
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• 2015

본 논문은 운전금지영역을 가진 이차 볼록 발전비용 함수를 적용하는 경제급전의 최적화 문제에 대한 결정론적 최적화 알고리즘을 제안하였다. 제안된 알고리즘은 운전금지구역을 가진 발전기는 운전금지구역을 벗어나도록 분할하고, 초기치 $P_i{\leftarrow}P_i^{max}$에 대해 발전단가가 큰 순서대로 발전량을 감소시키고, $_{max}\{F(P_i)-F(P_i-{\beta})\}$ > $_{min}\{F(P_j+{\beta})-F(P_j)\}$, $i{\neq}j$, ${\beta}=1.0,0.1,0.01,0.001$에 대해 $P_i{\leftarrow}P_i-{\beta}$, $P_j{\leftarrow}P_j+{\beta}$의 교환 최적화 과정을 수행하였다. 제안된 방법을 15-발전기의 3가지 사례에 적용한 결과 간단하면서도 항상 동일한 결과로 휴리스틱 알고리즘들에 비해 최적의 결과를 나타내었다.

• 한국인터넷방송통신학회논문지
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• 제17권4호
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• pp.219-224
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• 2017

경제급전 최적화 문제를 해결하는 결정론적인 알고리즘에 존재하지 않아 지금까지는 비결정론적인 휴리스틱 알고리즘들이 제안되고 있다. 이와 더불어 실시간 급전문제에 대한 연구는 거의 없는 실정이다. 본 논문은 발전정지 개념을 도입하여 실시간 급전의 최적화 문제를 풀 수 있는 알고리즘을 제안하였다. 제안된 알고리즘은 단위 발전량당 최대 비용이 소요되는 발전기는 발전을 중지시키는 기준을 적용하였다. 본 논문에서 제안한 발전정지 기준은 발전비용함수에서 밸브효과에 따른 비선형 절대치 함수를 제외한 2차 함수만을 대상으로 하였다. 경제급전 문제의 시험사례로 빈번히 활용되고 있는 데이터에 대해 제안된 알고리즘을 적용한 결과 기존 알고리즘들의 해를 크게 감소시킬 수 있었다.

• 산업경영시스템학회지
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• 제38권2호
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• pp.40-46
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• 2015

The modular assembly system can make it possible for the variety of products to be assembled in a short lead time. In this system, necessary components are assembled to optional components tailor to customers' orders. Budget for inventory investments composed of inventory and purchasing costs are practically limited and the purchasing cost is often paid when an order is arrived. Service cost is assumed to be proportional to service level and it is included in budget constraint. We develop a heuristic procedure to find a good solution for a continuous review inventory system of the modular assembly system with a budget constraint. A regression analysis using a quadratic function based on the exponential function is applied to the cumulative density function of a normal distribution. With the regression result, an efficient heuristics is proposed by using an approximation for some complex functions that are composed of exponential functions only. A simple problem is introduced to illustrate the proposed heuristics.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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• pp.65-68
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• 2000

It is well-known that the decision rule in the mini-mum mean-squares-error decision feedback equalizer(MMSE-DFE) is biased, and therefore suboptimum with respect to error probability. We present a new family of algorithms that solve the bias problem in the adaptive DFE. A novel constraint, called the constant-norm con-straint, is introduced unifying the quadratic constraint and the monic one. A new cost function based on the constant-norm constraint and Lagrange multiplier is defined. Minimizing the cost function gives birth to a new family of unbiased adaptive DFE. The simula-tion results demonstrate that the proposed method in-deed produce unbiased solution in the presence of noise while keeping very simple both in computation and im-plementation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.333-336
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• 1992

In this paper, We propose a PID-type of self-tuning algorithm which is based on the parameter estimation and the minimization of the cost function. We use the CARIMA model for parameter estimation and determine the discrete PID controller parameters by minimizing the cost function which considers the quadratic deviations of the predicted output over the set-point as well as the control efforts. Also, The algorithm is extended by incorporating constraints of the control signal. Simulations are performed to illustrate the efficiency of the proposed method.