• Title/Summary/Keyword: Selection Time

Search Result 3,507, Processing Time 0.031 seconds

Feature Subset Selection Algorithm based on Entropy (엔트로피를 기반으로 한 특징 집합 선택 알고리즘)

  • 홍석미;안종일;정태충
    • Journal of the Institute of Electronics Engineers of Korea CI
    • /
    • v.41 no.2
    • /
    • pp.87-94
    • /
    • 2004
  • The feature subset selection is used as a preprocessing step of a teaming algorithm. If collected data are irrelevant or redundant information, we can improve the performance of learning by removing these data before creating of the learning model. The feature subset selection can also reduce the search space and the storage requirement. This paper proposed a new feature subset selection algorithm that is using the heuristic function based on entropy to evaluate the performance of the abstracted feature subset and feature selection. The ACS algorithm was used as a search method. We could decrease a size of learning model and unnecessary calculating time by reducing the dimension of the feature that was used for learning.

A Study on the Criteria and Trends in Selecting Viewpoint (조망점의 선정기준과 경향에 관한 연구)

  • Bang, Jae-Sung;Song, Byeong-Hwa;Yang, Byoung-E
    • Journal of the Korean Institute of Landscape Architecture
    • /
    • v.36 no.1
    • /
    • pp.70-79
    • /
    • 2008
  • The purpose of this study is to construct the fundamental data for setting a valid viewpoint as the base of landscape planning and management practices. To do this, we analyzed the preceding dissertations and landscape plan reports which presented the selection criteria of viewpoint. 37 research samples containing the criteria of viewpoint were investigated. The selection criteria and trends of viewpoint were analyzed as follows : Firstly, by analyzing the preceding researches we were able to grasp the criteria that had been used to set viewpoint. Secondly, we investigated the differences in criteria of selecting the viewpoint according to the research type, research time and view object. Finally, we analyzed the trends of viewpoint selection criteria and classified the characteristics and selection criteria of viewpoint based on an overview of the research content. It can be concluded that the criteria of viewpoint are intimately linked to the view object, the purpose and role of viewpoint which is related to the landscape planning and management practices. According to this study, we can find that the selection criteria and trends of viewpoint have been used in the research related to the view plane following the 1990's. Hereafter, additional research and the comparisons with researches abroad is necessary to set the objective selection criteria of viewpoint.

Selection probability of multivariate regularization to identify pleiotropic variants in genetic association studies

  • Kim, Kipoong;Sun, Hokeun
    • Communications for Statistical Applications and Methods
    • /
    • v.27 no.5
    • /
    • pp.535-546
    • /
    • 2020
  • In genetic association studies, pleiotropy is a phenomenon where a variant or a genetic region affects multiple traits or diseases. There have been many studies identifying cross-phenotype genetic associations. But, most of statistical approaches for detection of pleiotropy are based on individual tests where a single variant association with multiple traits is tested one at a time. These approaches fail to account for relations among correlated variants. Recently, multivariate regularization methods have been proposed to detect pleiotropy in analysis of high-dimensional genomic data. However, they suffer a problem of tuning parameter selection, which often results in either too many false positives or too small true positives. In this article, we applied selection probability to multivariate regularization methods in order to identify pleiotropic variants associated with multiple phenotypes. Selection probability was applied to individual elastic-net, unified elastic-net and multi-response elastic-net regularization methods. In simulation studies, selection performance of three multivariate regularization methods was evaluated when the total number of phenotypes, the number of phenotypes associated with a variant, and correlations among phenotypes are different. We also applied the regularization methods to a wild bean dataset consisting of 169,028 variants and 17 phenotypes.

A Study on the Selection Criteria for Home Economics Textbook in the Middle School (중학교 가정 교과서 선정 기준에 관한 연구)

  • 권리라;윤인경
    • Journal of Korean Home Economics Education Association
    • /
    • v.10 no.1
    • /
    • pp.41-57
    • /
    • 1998
  • The purpose of this study was to make a selection criteria for Home Economics textbooks in the middle school. For this purpose, first, the criteria were out by collecting, analyzing and synthesizing the literature. Second, questionnaire survey of the 6 selection criteria was performed. Questionnaire sent to Home Economics teachers of 401 middle school selected by systematic random sapling, 233 questionnaire were received and 220 questionnaire were analyzed for this study. As a statistical tool, SPSSWIN was used to analyze frequency, mean, standard deviation, and factor analysis. The research findings were as follows ; 1. Now for kinds of Home Economics textbooks are mainly used. At that time when textbooks were selected, these selections were made upon deliberation with the teachers in charge and in future this method will be desirable. Most home economics teachers realize that the selection criteria is needed to improve the objectivity of textbook selection. 2. As a result of making factor analysis, the selection criteria were revised that 52 items in 7 categories were chosen as textbook criteria plan. They consist of 5 items related to the outward form of textbook, 5 items related to the learning materials in textbook, 10 items related to the composition of textbook units, 11 items related to the guiding contents of textbook, 7 items related to the subject of experiment.practice, 9 items related to the composition of picture, photograph and diagram. and 7 items related to the use of instructional-learning method.

  • PDF

Link Adaptation and Selection Method for OFDM Based Wireless Relay Networks

  • Can, Basak;Yomo, Hiroyuki;Carvalho, Elisabeth De
    • Journal of Communications and Networks
    • /
    • v.9 no.2
    • /
    • pp.118-127
    • /
    • 2007
  • We propose a link adaptation and selection method for the links constituting an orthogonal frequency division multiplexing (OFDM) based wireless relay network. The proposed link adaptation and selection method selects the forwarding, modulation, and channel coding schemes providing the highest end-to-end throughput and decides whether to use the relay or not. The link adaptation and selection is done for each sub-channel based on instantaneous signal to interference plus noise ratio (SINR) conditions in the source-to-destination, source-to-relay and relay-to-destination links. The considered forwarding schemes are amplify and forward (AF) and simple adaptive decode and forward (DF). Efficient adaptive modulation and coding decision rules are provided for various relaying schemes. The proposed end-to-end link adaptation and selection method ensures that the end-to-end throughput is always larger than or equal to that of transmissions without relay and non-adaptive relayed transmissions. Our evaluations show that over the region where relaying improves the end-to-end throughput, the DF scheme provides significant throughput gain over the AF scheme provided that the error propagation is avoided via error detection techniques. We provide a frame structure to enable the proposed link adaptation and selection method for orthogonal frequency division multiple access (OFDMA)-time division duplex relay networks based on the IEEE 802.16e standard.

Fast Macroblock Mode Selection Algorithm for B Frames in Multiview Video Coding

  • Yu, Mei;He, Ping;Peng, Zongju;Zhang, Yun;Si, Yuehou;Jiang, Gangyi
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.5 no.2
    • /
    • pp.408-427
    • /
    • 2011
  • Intensive computational complexity is an obstacle of enabling multiview video coding for real-time applications. In this paper, we present a fast macroblock (MB) mode selection algorithm for B frames which are based on the computational complexity analyses between the MB mode selection and reference frame selection. Three strategies are proposed to reduce the coding complexity jointly. First, the temporal correlation of MB modes between current MB and its temporal corresponding MBs is utilized to reduce computational complexity in determining the optimal MB mode. Secondly, Lagrangian cost of SKIP mode is compared with that of Inter $16{\times}16$ modes to early terminate the mode selection process. Thirdly, reference frame correlation among different Inter modes is exploited to reduce the number of reference frames. Experimental results show that the proposed algorithm can promote the encoding speed by 3.71~7.22 times with 0.08dB PSNR degradation and 2.03% bitrate increase on average compared with the joint multiview video model.

Adaptive Learning Control of Neural Network Using Real-Time Evolutionary Algorithm (실시간 진화 알고리듬을 통한 신경망의 적응 학습제어)

  • Chang, Sung-Ouk;Lee, Jin-Kul
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.26 no.6
    • /
    • pp.1092-1098
    • /
    • 2002
  • This paper discusses the composition of the theory of reinforcement teaming, which is applied in real-time teaming, and evolutionary strategy, which proves its the superiority in the finding of the optimal solution at the off-line teaming method. The individuals are reduced in order to team the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It is possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because of the teaming process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes. In the future, studies are needed on the proof of the theory through experiments and the characteristic considerations of the robustness against the outside disturbances.

Development of an AGV Controller in Semiconductor and LCD Production Systems (반도체 및 LCD 제조 공정의 AGV Controller 개발)

  • Suh, Jungdae;Jang, Jaejin;Koo, Pyung-Hoi
    • Journal of Korean Institute of Industrial Engineers
    • /
    • v.29 no.1
    • /
    • pp.1-13
    • /
    • 2003
  • In this paper, LAC(Look-ahead AGV Controller) has been developed for efficient routing of parts in semiconductor and LCD production systems. Several procedures have been developed as sub-modules. LACP(Look-ahead AGV Control Procedure) which controls AGVs using the information on the current and future status of the systems is the main element of the LAC. To support LACP, DSP(Destination Selection Procedure) which determines a destination of a part and AGV call time, SSP(Source Selection Procedure)which selects a part coming next to a buffer when the buffer becomes available. and RTM(Response Time Model) which estimates empty travel time of AGVs and waiting time for an available AGV have been developed. A simulation experiment shows that LAC reduces part's flow time, AGV utilization, average and maximum inventory level of a central buffer, empty travel time of an AGV, and waiting time for an available AGV.

A comparison of mortality projection by different time period in time series (시계열 이용기간에 따른 사망률 예측 비교)

  • Kim, Soon-Young;Oh, Jinho;Kim, Kee-Whan
    • The Korean Journal of Applied Statistics
    • /
    • v.31 no.1
    • /
    • pp.41-65
    • /
    • 2018
  • In Korea, as the mortality rate improves in a shorter period of time than in developed countries, it is important to consider the selection of the time series as well as the model selection in the mortality projection. Therefore, this study proposed a method using the multiple regression model in respect to the selection of the time series period. In addition, we investigate the problems that arise when various time series are used based on the Lee-Carter (LC) model, the kinds of LC model along with Lee-Miller (LM) and Booth-Maindonald-Smith (BMS), and the non-parametric model such as functional data model (FDM) and Coherent FDM, and examine differences in the age-specific mortality rate and life expectancy projection. Based on the analysis results, the age-specific mortality rate and predicted life expectancy of men and women are calculated for the year 2030 for each model. We also compare the mortality rate and life expectancy of the next generation provided by Korean Statistical Information Service (KOSIS).

Hybrid Feature Selection Using Genetic Algorithm and Information Theory

  • Cho, Jae Hoon;Lee, Dae-Jong;Park, Jin-Il;Chun, Myung-Geun
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • v.13 no.1
    • /
    • pp.73-82
    • /
    • 2013
  • In pattern classification, feature selection is an important factor in the performance of classifiers. In particular, when classifying a large number of features or variables, the accuracy and computational time of the classifier can be improved by using the relevant feature subset to remove the irrelevant, redundant, or noisy data. The proposed method consists of two parts: a wrapper part with an improved genetic algorithm(GA) using a new reproduction method and a filter part using mutual information. We also considered feature selection methods based on mutual information(MI) to improve computational complexity. Experimental results show that this method can achieve better performance in pattern recognition problems than other conventional solutions.