• Title/Summary/Keyword: Optimal weights,

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A NEW ALGORITHM OF EVOLVING ARTIFICIAL NEURAL NETWORKS VIA GENE EXPRESSION PROGRAMMING

  • Li, Kangshun;Li, Yuanxiang;Mo, Haifang;Chen, Zhangxin
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.9 no.2
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    • pp.83-89
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    • 2005
  • In this paper a new algorithm of learning and evolving artificial neural networks using gene expression programming (GEP) is presented. Compared with other traditional algorithms, this new algorithm has more advantages in self-learning and self-organizing, and can find optimal solutions of artificial neural networks more efficiently and elegantly. Simulation experiments show that the algorithm of evolving weights or thresholds can easily find the perfect architecture of artificial neural networks, and obviously improves previous traditional evolving methods of artificial neural networks because the GEP algorithm imitates the evolution of the natural neural system of biology according to genotype schemes of biology to crossover and mutate the genes or chromosomes to generate the next generation, and the optimal architecture of artificial neural networks with evolved weights or thresholds is finally achieved.

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Effects of Hydrogen Peroxide Concentration on the Polymerization of p-Phenylphenol in Organic Solvent by Peroxidase

  • Yoo, Young-Je;Yeo, Joo-Sang;Park, Tae-In
    • Journal of Microbiology and Biotechnology
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    • v.5 no.3
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    • pp.177-180
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    • 1995
  • In horseradish peroxidase-catalyzing polymerization of phenol under the water/dioxane solvent system, the optimal concentration of hydrogen peroxide was found to be 10 mmol/I. Feeding of hydrogen peroxide at its optimal concentration improved the polymerization performance by reducing reaction time and increasing molecular weights. Monomer conversions and the molecular weights of the enzymatically produced polymer were in the ranges of 83.1~94.2$%$ and 58000~68000, respectively.

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A Data-Mining-based Methodology for Military Occupational Specialty Assignment (데이터 마이닝 기반의 군사특기 분류 방법론 연구)

  • 민규식;정지원;최인찬
    • Journal of the military operations research society of Korea
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    • v.30 no.1
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    • pp.1-14
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    • 2004
  • In this paper, we propose a new data-mining-based methodology for military occupational specialty assignment. The proposed methodology consists of two phases, feature selection and man-power assignment. In the first phase, the k-means partitioning algorithm and the optimal variable weighting algorithm are used to determine attribute weights. We address limitations of the optimal variable weighting algorithm and suggest a quadratic programming model that can handle categorical variables and non-contributory trivial variables. In the second phase, we present an integer programming model to deal with a man-power assignment problem. In the model, constraints on demand-supply requirements and training capacity are considered. Moreover, the attribute weights obtained in the first phase for each specialty are used to measure dissimilarity. Results of a computational experiment using real-world data are provided along with some analysis.

A method for deciding weighting matrices in a linear discrete time optimal regulator problems to locate all poles in the specified region

  • Shin, Jae-Woong;Shimemura, Etsujiro;Kawasaki, Naoya
    • 제어로봇시스템학회:학술대회논문집
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    • 1988.10b
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    • pp.729-733
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    • 1988
  • In this paper, a new procedure for selecting weighting matrices in linear discrete time quadratic optimal control problems (LQ-problem) is proposed. In LQ problems, the quadratic weighting matrices are usually decided on trial and error in order to get a good response. But using the proposed method, the quadratic weights are decided in such a way that all poles of the closed loop system are located in a desired area for good responses as well as for stability and values of the quadratic cost functional are kept less then a specified value. The closed loop systems constructed by this method have merits of LQ problems as well as those of pole assignment problems. Taking into consideration that little is known about the relationship among the quadratic weights, the poles and the values of cost functional, this procedure is also interesting from the theoretical point of view.

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Multi user interference cancellation in satellite to ground uplink system Based on improved WPIC algorithm

  • Qingyang, Guan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.11
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    • pp.5497-5512
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    • 2016
  • An improved optimal weights based on parallel interference cancellation algorithm has been proposed to cancel for interference induced by multi-user access satellite to ground uplink system. Due to differences in elevation relative motion between the user and the satellite, as well as access between users, resulting in multi-user access interference (Multi-user Access Interference, MUI), which significantly degrade system performance when multi-user access. By steepest gradient method, it obtained based on the MMSE criterion, parallel interference cancellation adjust optimal weights to obtain the maximum SINR. Compared to traditional parallel interference cancellation (Parallel Interference Cancellation, PIC) algorithm or serial interference cancellation ( Successive interference Cancellation, SIC), the accuracy of which is not high and too many complex iterations, we establish the multi-user access to the satellite to ground up link system to demonstrate that the improved WPIC algorithm could be provided with high accuracy and relatively low number of iterations.

Non-Data-Aided Weighted Non-Coherent Receiver for IR-UWB PPM Signals

  • Shen, Bin;Yang, Rumin;Cui, Taiping;Kwak, Kyung-Sup
    • ETRI Journal
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    • v.32 no.3
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    • pp.460-463
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    • 2010
  • This letter proposes an energy-detection-based non-data-aided weighted non-coherent receiver (NDA-WNCR) scheme for impulse radio ultra-wideband (IR-UWB) pulse-position modulated signals. Compared to the conventional WNCR, the optimal weights of the proposed NDA-WNCR are tremendously simplified as the maximum eigenvector of the IR-UWB signal energy sample autocorrelation matrix. The NDA-WNCR serves to blindly obtain the optimal weights and entirely circumvent the transmission of training symbols or channel estimation in practice. Analysis and simulation results verify that the bit error rate (BER) performance of the NDA-WNCR closely approaches the ideal BER of the conventional WNCRs.

Worst case analysis of circulating type ropeway using optimal design technique (최적설계 기법을 이용한 순환식 삭도 선로의 최악조건 해석)

  • 최수진;신재균
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.13 no.3
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    • pp.554-560
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    • 1989
  • An optimal design technique is used as a systematic approach to analyze the worst case of a circulating type ropeway for a given geometry and operating conditions. Worst case is meant here the case when the positions and weights of the cars are so conditioned that the minimum of all the reaction forces between the main rope and the towers is minimum. In the course of this study, a general theory for the deflections and tensions of the main rope were also derived taking into account of the variation of the weights and positions of the individual cars. And through an analysis of example ropeways, some general conditions for the worst case are deduced.

Homing Guidance Law for Alleviating Sensitivity to Initial Heading Errors (초기 헤딩오차 민감도 완화 호밍 유도법칙)

  • Lee, Jin-Ik;Jeon, In-Soo
    • Journal of the Korea Institute of Military Science and Technology
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    • v.11 no.4
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    • pp.29-35
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    • 2008
  • In this paper, a new guidance law to reduce sensitivity to the initial heading errors is proposed. In order for shaping the input weights over the flight, we introduce the distribution functions expressed in terms of time-to-go and its inverse term. By applying the optimal control theory with the synthesized weights, the homing guidance law is derived. Also the characteristics of the proposed law are examined. Various computer simulations show the good performance of the proposed guidance.

Development of a Personalized Similarity Measure using Genetic Algorithms for Collaborative Filtering

  • Lee, Soojung
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.12
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    • pp.219-226
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    • 2018
  • Collaborative filtering has been most popular approach to recommend items in online recommender systems. However, collaborative filtering is known to suffer from data sparsity problem. As a simple way to overcome this problem in literature, Jaccard index has been adopted to combine with the existing similarity measures. We analyze performance of such combination in various data environments. We also find optimal weights of factors in the combination using a genetic algorithm to formulate a similarity measure. Furthermore, optimal weights are searched for each user independently, in order to reflect each user's different rating behavior. Performance of the resulting personalized similarity measure is examined using two datasets with different data characteristics. It presents overall superiority to previous measures in terms of recommendation and prediction qualities regardless of the characteristics of the data environment.

Cut-Off Values of the Post-Intensive Care Syndrome Questionnaire for the Screening of Unplanned Hospital Readmission within One Year

  • Kang, Jiyeon;Jeong, Yeon Jin;Hong, Jiwon
    • Journal of Korean Academy of Nursing
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    • v.50 no.6
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    • pp.787-798
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    • 2020
  • Purpose: This study aimed to assign weights for subscales and items of the Post-Intensive Care Syndrome questionnaire and suggest optimal cut-off values for screening unplanned hospital readmissions of critical care survivors. Methods: Seventeen experts participated in an analytic hierarchy process for weight assignment. Participants for cut-off analysis were 240 survivors who had been admitted to intensive care units for more than 48 hours in three cities in Korea. We assessed participants using the 18-item Post-Intensive Care Syndrome questionnaire, generated receiver operating characteristic curves, and analysed cut-off values for unplanned readmission based on sensitivity, specificity, and positive likelihood ratios. Results: Cognitive, physical, and mental subscale weights were 1.13, 0.95, and 0.92, respectively. Incidence of unplanned readmission was 25.4%. Optimal cut-off values were 23.00 for raw scores and 23.73 for weighted scores (total score 54.00), with an area of under the curve (AUC) of .933 and .929, respectively. There was no significant difference in accuracy for original and weighted scores. Conclusion: The optimal cut-off value accuracy is excellent for screening of unplanned readmissions. We recommend that nurses use the Post-Intensive Care Syndrome Questionnaire to screen for readmission risk or evaluating relevant interventions for critical care survivors.