• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.2269-2275
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• 2010

The performance of Genetic Algorithms (GA) is affected by various factors such as parameters, genetic operators and strategies. The traditional approach with random initial population is efficient however the whole initial population may contain many infeasible solutions. Thus it would take a long time for GA to produce a good solution. The GA have been modified in various ways to achieve faster convergence and it was particularly recognized by researchers that initial population greatly affects the performance of GA. This study proposes modified GA with sorted initial population and applies it to solving Travelling Salesman Problem (TSP). Normally, the bigger the initial the population is the more computationally expensive the calculation becomes with each generation. New approach allows reducing the size of the initial problem and thus achieve faster convergence. The proposed approach is tested on a simulator built using object-oriented approach and the test results prove the validity of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.177-183
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• 2008

The particle swarm optimization(PSO) has been shown to converge rapidly during the initial stages of a global search, but around global optimum, the search process becomes very slow. On the other hand, the genetic algorithm is very sensitive to the initial population. In fact, the random nature of the GA operators makes the algorithm sensitive to initial population. This dependence to the initial population is in such a manner that the algorithm may not converge if the initial population is not well selected. In this paper, we have proposed a new algorithm which combines PSO and GA in such a way that the new algorithm is more effective and efficient and can find the optimal solution more accurately and with less computational time. Optimal location of SVC using this hybrid PSO-GA algorithm is found. We have also found the optimal place of SVC using GA and PSO separately and have compared the results. It has been shown that the new algorithm is more effective and efficient. An IEEE 68 bus test system is used for simulation.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.4
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• pp.324-333
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• 2013

The purpose of this paper is to improve the efficiency of multi-objective topology optimization using a genetic algorithm (GA) with bar-system representation. We proposed a new GA using an elite initial population obtained from a Solid Isotropic Material with Penalization (SIMP) using a weighted sum method. SIMP with a weighted sum method is one of the most established methods using sensitivity analysis. Although the implementation of the SIMP method is straightforward and computationally effective, it may be difficult to find a complete Pareto-optimal set in a multi-objective optimization problem. In this study, to build a more convergent and diverse global Pareto-optimal set and reduce the GA computational cost, some individuals, with similar topology to the local optimum solution obtained from the SIMP using the weighted sum method, were introduced for the initial population of the GA. The proposed method was applied to a structural topology optimization example and the results of the proposed method were compared with those of the traditional method using standard random initialization for the initial population of the GA.

• Korean journal of applied entomology
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• v.36 no.3
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• pp.237-242
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• 1997

Comparative studies on suppression possibility with three phytoseiid mite species (An.thly,seiu,sw omersleyi Schicha. A. ,fidIrrc~i.Gs arman and T\ulcornerphlorlrotiiu.s oc~c~idetitaliNs esbit) to the two-spotted spider mite (Te~trrrt~yc.Iir~l~l\ulcorner.i\c .(re Kwh) on kidney bean leaves in field and greenhouse were carried out. In the field experiments with the initial prey -predator ratio of 4 : 1. I0 : I and 20: I . A. ,firllrrcis suppressed successfully the prey populations at all three ratios 17 days after the initial infestation. A. wornc,r-;leyi \uppressed the prey population only at the ratio of 4 : 1, while T. oc~c~ideritcr1iw.s as unable to suppress the prey population at all tested ratios. In the greenhouse experiments with the initial prey-predator ratio of 10: 1, A. jil1ltrci.s could suppress the prey population continuously during the infestation period. A. ~~otnc~r,slceoyuil d suppress the prey population for 13 days after the initial infestation, while T. occie1mttrli.s could suppress the prey population for 8 - 23 days after the initial infestation.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.8 no.1
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• pp.1-13
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• 1972

Yellow croacker, Tseudociaena manchurica Jordan et Thompson in the Yellow Sea and East China Sea are subjected to be caught by trawl nets throughout the year. First indices of population size in every period 8re calculated. Considering present status of the yellow croacker fishery and ecology of the fish, mathematical models must have been established in order to determine catchability coefficient, natural m ortali ty, fishing mortality, recrui ting coefficient of the fish ing ground, and dispersion coefficienl from the fishing ground. The results an, summmarized as follows: Catchabil i ty coefficient $(C) = 2. 2628 {\times} 10^{-5}$ Natural mortality (M)=0.3293 Population for lhe first half season(July 1st to the following January 3lst) Initial population = 14, 621 $/\frac{M}{T}$ Recruitment =45, 597 $/\frac{M}{T}$ Natural mortality = 8, 660 $/\frac{M}{T}$ Final population =42, 970 $/\frac{M}{T}$ Population for the latter 1131f scason(February 1st to June 30th) Initial population = 69, 170 $/\frac{M}{T}$ Dispersion =51, 688 $/\frac{M}{T}$ Natural mortality = 6, 082 $/\frac{M}{T}$ Final population = 1, 802 $/\frac{M}{T}$.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.11
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• pp.4677-4683
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• 2015

When there is no sampling frame within a certain group or the group is concerned that making its population public would bring social stigma, we say the population is hidden. It is difficult to approach this kind of population survey-methodologically because the response rate is low and its members are not quite honest with their responses when probability sampling is used. The only alternative known to address the problems caused by previous methods such as snowball sampling is respondent-driven sampling (RDS), which was developed by Heckathorn and his colleagues. RDS is based on a Markov chain, and uses the social network information of the respondent. This characteristic allows for probability sampling when we survey a hidden population. We verified through computer simulation whether RDS can be used on a hidden population of cancer survivors. According to the simulation results of this thesis, the chain-referral sampling of RDS tends to minimize as the sample gets bigger, and it becomes stabilized as the wave progresses. Therefore, it shows that the final sample information can be completely independent from the initial seeds if a certain level of sample size is secured even if the initial seeds were selected through convenient sampling. Thus, RDS can be considered as an alternative which can improve upon both key informant sampling and ethnographic surveys, and it needs to be utilized for various cases domestically as well.

• Journal of Environmental Health Sciences
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• v.22 no.3
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• pp.49-55
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• 1996

Water parsley(Oenanthe javanica(Blume) DC) was raised with varying population density(S) in the laboratory aquarium unit to determine the growth equation. The population density was measure after 7 days. The resultant growth curve was well fit to the equation 1/S = A+B (1/S0) with a high correlation coefficient ($R^2$ = 0.999). The maximum specific absorption rate was $9.011 \times 10^{-5}$ kg $NO_x-N/kg$ water parsley$\cdot$day and $1.31 \times 10^{-5}$ kg $PO_4-P/kg$ water parsley$\cdot$day when the average population density was $2.62 kg/m^2$. The relationship between population density and nutrient absorption rate, the absorption rate of $NO_x-N$ was 5.04~5.24 mg/l$\cdot$day when the population density was $7.51~10.0 $mg/m^2\cdot day$ and the absorption rate of $PO_4-P$ was 0.56~0.78 mg/l$\cdot$day when the population density was 5.02~10.0 $kg/m^2\cdot day$. Taking into account the nutrient absorption rate and growth rate, the population density between $7.0 kg/m^2\cdot day$ and $8.0 kg/m^2 \cdot day$ was selected. The removal rate of nutrient was investigated after 7 days culture. Removal rate of $NO_x-N$ was 95.6~99.95% with initial concentration of 35 mg $NO_x-N/l$, and the removal rate of $PO_4-P$ was also high, indicating 80.24~98.9% with initial concentration of 5.95 mg $PO_x-P/l$.

• Korean journal of applied entomology
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• v.18 no.1 s.38
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• pp.15-21
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• 1979

To determine the population regulation mechanism of the Green rice leafhopper (Nephotettix cincticeps Uhler), the responses of the population increase to initial densities and the effect of host conditions and temperatures during developmental period were investigated. In the out door experiment, the increasing ratio of population density of this pest was reduced as initial density increased and this density-dependent effect was differ in accordance with host condition. Host conditioning through feeding resulted in reduction in numbers of eggs produced and it seemed to be affected by some inhibiting materials secreted by the pest during feeding. though the direct effect of feeding can't be excluded. The population growth was related with population density and host stage. Thus in late planted units, the host stage was favourable to the growth of population at low initial insect density but unfavourable at relatively high initial insect density and in early planted units, vice versa. The temperature during developmental stages definitely affected the determination of sex ratio of adult population and reduced numbers of eggs produced. The most favourable temperature to the population increase was $290^{\circ}C$, and at high temperature, $33^{\circ}C$, severe reduction of fecundity was shown ana it seemed to be caused by the simple reduction in numbers of eggs produced.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.330-333
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• 2003

Initial cluster size for clustering of partitioning methods is very important to the clustering result. In K-means algorithm, the result of cluster analysis becomes different with optimal cluster size K. Usually, the initial cluster size is determined by prior and subjective information. Sometimes this may not be optimal. Now, more objective method is needed to solve this problem. In our research, we propose a hybrid genetic algorithm, a tree induction based evolution algorithm, for determination of optimal cluster size. Initial population of this algorithm is determined by the number of terminal nodes of tree induction. From the initial population based on decision tree, our optimal cluster size is generated. The fitness function of ours is defined an inverse of dissimilarity measure. And the bagging approach is used for saying computational time cost.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.1
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• pp.59.1-59.1
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• 2017

Massive Population III black hole binary systems are one of the suggested candidate sources of the recently detected gravitational wave radiation (GWR). GWR detection from a black hole binary system requires a sufficiently short orbital separation at the time of their formation, such that they would undergo coalescence within the Hubble time. This condition cannot be simply fulfilled by a short initial period, because binary interactions such as mass transfer and common envelope evolution can largely change the orbital parameters and the masses of stellar components. Here, we discuss the possibility of black hole binary mergers from massive Pop III binary systems, using a new grid of Pop III binary evolutionary models with various initial primary masses ($20M_{\odot}{\leq}M{\leq}100M_{\odot}$) and initial separations, for different initial mass ratios (q = 0.5 - 0.9).