• Journal of Electrical Engineering and Technology
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• 제2권4호
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• pp.413-419
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• 2007

The optimal power flow (OPF) problem was introduced by Carpentier in 1962 as a network constrained economic dispatch problem. Since then, it has been intensively studied and widely used in power system operation and planning. In the past few decades, many stochastic optimization methods such as Genetic Algorithm (GA), Evolutionary Programming (EP), and Particle Swarm Optimization (PSO) have been applied to solve the OPF problem. In particular, PSO is a newly proposed population based stochastic optimization algorithm. The main idea behind it is based on the food-searching behavior of birds and fish. Compared with other stochastic optimization methods, PSO has comparable or even superior search performance for some hard optimization problems in real power systems. Nowadays, some modifications such as breeding and selection operators are considered to make the PSO superior and robust. In this paper, we propose the Modified PSO (MPSO), in which the mutation operator of GA is incorporated into the conventional PSO to improve the search performance. To verify the optimal solution searching ability, the proposed approach has been evaluated on an IEEE 3D-bus test system. The results showed that performance of the proposed approach is better than that of the standard PSO.

• 혜화의학회지
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• 제10권2호
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• pp.1-10
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• 2002

In review of "invigorating spleen and supplementing qi" of clinical and experimental studies on malignant tumor, we obtained the conclusions as follows 1. Asthenic splenic qi is an important factor in mutation, occurrence and development of tumor. 2. The anti-tumor mechanism of "invigorating spleen and supplementing qi" is improvement of immune suveillance, controling cell proliferating period and enhancing body metabolism. 3. "Invigorating spleen and supplementing qi" is often used with "nourishing kidney" or "expelling pathogen" for treating cnacer. 4. In experimental studies, "invigorating spleen and supplementing qi" has effects on inhibiting occurrence and development of tumor, protecting mutation, inhibiting recurrence and metastasis, immune activity, enhancing metabolism, promoting bone marrow hemopoietic cell proliferation, increasing anti-tumor effect and protecting normal cells. 5. In clinical studies, "invigorating spleen and supplementing qi" has effects on prolonging the survival period of cancer patients, improving clinical symptoms and quality of life of cancer patients, degrading the side effects of western therapie(operation, chemotherapy and radiotherapy). 6. "Invigorating spleen and supplementing qi" is an extensive discipline of syndrome differentiation used to inhibit occurence, development, recurrence and metastasis.

• 한국잠사곤충학회지
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• 제49권1호
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• pp.1-7
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• 2007

누에의 가시 돌연변이 형질을 이용한 환경변이원 검색계의 연중검색 체계수립을 위하여 인공사료누에의 환경변이원에 대한 적품종 및 감수성을 조사하였다. 변이원에 대한 인공사료육 누에의 적합 품종 조사를 위해 누에품종 AT, 백옥잠, C5와 N12를 대상으로 변이원 MMC를 투여한 후 주요형질을 조사한 결과, AT는 암나방의 우화율에서, C5와 N12는 수나방의 수정률에서 높은 성적을 보였다. 반면에 백옥잠은 암나방 우화율, 암수나방의 정상산란비율, 암나방의 산란수 및 수정률에서 높은 성적을 나타내어 인공사료에 대한 적품종으로 선발되었다. 또한 변이원에 대한 감수성 조사 결과, 인공사료육에 적품종으로 선발된 백옥잠은 공시된 다른 품종보다 다소 감수성이 낮았으며, AT가 누에의 환경변이원 검색 시스템에 높은 감수성을 보였다. 변이원 감수성은 높으나, 산란성, 우화율 등 검색계로서 주요형질이 극히 불량한 AT를 연중 검색 체계수립을 위한 변이원 검색계로 이용하기 위해서는 백옥잠 등과의 교잡으로 주요형질을 개선할 필요가 있다고 판단되었다.

• 조명전기설비학회논문지
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• 제13권3호
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• pp.48-55
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• 1999

본 연구에서는 방사상 배전계통에 있어서 손실감소 및 전압보상을 위한 커패시터 최적배치 및 운용 방안을 제시하였다. 커패시터 배치와 관련된 비용함수를 실제 뱅크단위로 이산성을 고려하여 계단함수로 정식화하였다. 불연속이면서 미분 불가능한 함수인 커패시터 배치와 관련된 비용함수의 해를 효율적으로 구하기 위하여 전역적탐색기법인 GA를 이요하였다. 특히, GA의 스트링을 커패시터가 배치될 모선의 인덱스와 투입량인 뱅크단위로 동시에 구성하여 기존의 방법보다 효율적으로 해를 탐색하였다. 또한 스트링의 길이를 변화시킬 수 있는 길이 돌연변이(length mutation) 연산자를 사용하므로써 효과적으로 커패시터 설치위치의 수를 결정할 수 있었다. 제안한 커패시터 설치위치와 투입량을 동싱에 탐색할 수 있는 방안으로부터 커패시터의 최소 투입량으로 다양한 부하레벨에서 전력손실을 감소시키고, 전압강하를 적절히 보강시킬수 있다. 이에 대한 효용성을 입증하기 위하여 22kV-9-section feeler로 구성된 방사상 배전계통에 적용하였다.

• 정보처리학회논문지B
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• 제9B권5호
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• pp.673-680
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• 2002

이 논문은 진화 프로그래밍과 개선된 역전파 알고리즘을 이용한 에지 검출 방법을 제안한다. 진화 프로그래밍은 알고리즘의 성능저하와 계산비용을 고려하여 교차 연산은 수행하지 않고, 선택연산자와 돌연변이 연산자를 사용한다. 개선된 역전파 알고리즘은 학습단계에서 연결강도를 변화시킬 때 이전학습단계의 연결강도를 보조적으로 활용하는 방법이다. 이 개선된 역전파 알고리즘은 학습률 $\alpha$를 작은값으로 설정하기 때문에 각 학습단계에서의 연결강도 변화량이 기존의 방법에 비해 상대적으로 줄어들게 되어 학습이 느려지는 문제점을 해결하였다. 실험결과 학습시간과 검출률에 있어서 GA-BP(GA : Genetic Algorithm BP : Back-Propagation)를 이용한 방법보다 제안한 EP-MBP(EP : Evolutionary Programming, MBP :Momentum Back-Propagation)를 이용하여 학습시킨 방법이 학습시간의 단축과 효율적인 에지 검출 결과를 얻을 수 있었다.

• Journal of Electrical Engineering and Technology
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• 제10권1호
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• pp.56-63
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• 2015

The optimization is an important role in wide geographical distribution of electrical power market, finding the optimum solution for the operation and design of power systems has become a necessity with the increasing cost of raw materials, depleting energy resources and the ever growing demand for electrical energy. In this paper, the real coded biogeography based optimization is proposed to minimize the operating cost with optimal setting of equality and inequality constraints of thermal power system. The proposed technique aims to improve the real coded searing ability, unravel the prematurity of solution and enhance the population assortment of the biogeography based optimization algorithm by using adaptive Gaussian mutation. This algorithm is demonstrated on the standard IEEE-30 bus system and the comparative results are made with existing population based methods.

• Journal of Advanced Marine Engineering and Technology
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• 제25권2호
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• pp.383-394
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• 2001

The stabilization control of inverted pendulum (IP) system is difficult because of its nonlinearity and structural unstability. In this paper, an Evolving Neural Network Controller (ENNC) without Error Back Propagation (EBP) is presented. An ENNC is described simply by genetic representation using an encoding strategy for types and slope values of each active functions, biases, weights and so on. By an evolutionary programming which has three genetic operation; selection, crossover and mutation, the predetermine controller is optimally evolved by updating simultaneously the connection patterns and weights of the neural networks. The performances of the proposed ENNC(PENNC)are compared with the one of conventional optimal controller and the conventional evolving neural network controller (CENNC) through the simulation and experimental results. And we showed that the finally optimized PENNC was very useful in the stabilization control of an IP system.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.609-612
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• 2000

Job-shop scheduling problem(JSSP) is one of the best-known machine scheduling problems and essentially an ordering problem. A new encoding scheme which always give a feasible schedule is presented, by which a schedule directly corresponds to an assigned-operation ordering string. It is initialized with G&T algorithm and improved using the developed genetic operator; APMX or BPMX crossover operator and mutation operator. and the problem of infeasibility in genetic generation is naturally overcome. Within the framework of the newly designed genetic algorithm, the NP-hard classical job-shop scheduling problem can be efficiently solved with high quality. Moreover the optimal solutions of the famous benchmarks, the Fisher and Thompson's 10${\times}$10 and 20${\times}$5 problems, are found.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.524-524
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• 2000

We have been developing a method to build one-step-ahead prediction models for time series using genetic programming (GP). Our model building method consists of two stages. In the first stage, functional forms of the models are inherited from their parent models through crossover operation of GP. In the second stage, the parameters of the newborn model arc optimized based on an iterative method just like the back propagation. The proposed method has been applied to various kinds of time series problems. An application to the seismic ground motion was presented in the KACC'99, and since then the method has been improved in many aspects, for example, additions of new node functions, improvements of the node functions, and new exploitations of many kinds of mutation operators. The new ideas and trials enhance the ability to generate effective and complicated models and reduce CPU time. Today, we will present a couple of financial applications, espc:cially focusing on gold price prediction in Tokyo market.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 추계학술대회 논문집 전력기술부문
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• pp.330-332
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• 2001

Distribution systems is consist of network in physical and radial in electrical aspect. Therefore radial operation is realized by changing the status of sectionalizing switches, and is usually done for loss reduction in the system. In this paper, we propose a optimal method for distribution systems reconfiguration. Specifically we use genetic algorithm method to solve distribution systems reconfiguration for loss minimization problem. A genetic algorithm(GA) is set up, in which some improvements are made on string coding, fitness function and mutation pattern. As a result, premature convergence is avoided.