• Title/Summary/Keyword: Index Optimization

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Coordinated Control Strategy and Optimization of Composite Energy Storage System Considering Technical and Economic Characteristics

  • Li, Fengbing;Xie, Kaigui;Zhao, Bo;Zhou, Dan;Zhang, Xuesong;Yang, Jiangping
    • Journal of Electrical Engineering and Technology
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    • v.10 no.3
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    • pp.847-858
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    • 2015
  • Control strategy and corresponding parameters have significant impacts on the overall technical and economic characteristics of composite energy storage systems (CESS). A better control strategy and optimized control parameters can be used to improve the economic and technical characteristics of CESS, and determine the maximum power and stored energy capacity of CESS. A novel coordinated control strategy is proposed considering the coordination of various energy storage systems in CESS. To describe the degree of coordination, a new index, i.e. state of charge coordinated response margin of supercapacitor energy storage system, is presented. Based on the proposed control strategy and index, an optimization model was formulated to minimize the total equivalent cost in a given period for two purposes. The one is to obtain optimal control parameters of an existing CESS, and the other is to obtain the integrated optimal results of control parameters, maximum power and stored energy capacity for CESS in a given period. Case studies indicate that the developed index, control strategy and optimization model can be extensively applied to optimize the economic and technical characteristics of CESS. In addition, impacts of control parameters are discussed in detail.

Group Search Optimization Data Clustering Using Silhouette (실루엣을 적용한 그룹탐색 최적화 데이터클러스터링)

  • Kim, Sung-Soo;Baek, Jun-Young;Kang, Bum-Soo
    • Journal of the Korean Operations Research and Management Science Society
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    • v.42 no.3
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    • pp.25-34
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    • 2017
  • K-means is a popular and efficient data clustering method that only uses intra-cluster distance to establish a valid index with a previously fixed number of clusters. K-means is useless without a suitable number of clusters for unsupervised data. This paper aimsto propose the Group Search Optimization (GSO) using Silhouette to find the optimal data clustering solution with a number of clusters for unsupervised data. Silhouette can be used as valid index to decide the number of clusters and optimal solution by simultaneously considering intra- and inter-cluster distances. The performance of GSO using Silhouette is validated through several experiment and analysis of data sets.

Fuzzy Identification by Means of an Auto-Tuning Algorithm and a Weighted Performance Index

  • Oh, Sung-Kwun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.8 no.6
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    • pp.106-118
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    • 1998
  • The study concerns a design procedure of rule-based systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient from of "IF..., THEN..." statements, and exploits the theory of system optimization and fuzzy implication rules. The method for rule-based fuzzy modeling concerns the from of the conclusion part of the the rules that can be constant. Both triangular and Gaussian-like membership function are studied. The optimization hinges on an autotuning algorithm that covers as a modified constrained optimization method known as a complex method. The study introduces a weighted performance index (objective function) that helps achieve a sound balance between the quality of results produced for the training and testing set. This methodology sheds light on the role and impact of different parameters of the model on its performance. The study is illustrated with the aid of two representative numerical examples.

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Reliability-Based Optimization using Sensitivity Analysis of Reliability Index (신뢰성 지수의 민감도 해석을 이용한 신뢰성에 기초한 최적설계)

  • 조효남;민대홍;권우성
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2000.10a
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    • pp.101-108
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    • 2000
  • An optimum design algorithm using efficient reanalysis is proposed for reliability-based optimization problems formulated as the minimization of initial cost and expected failure cost with reliability constraints. The reliability-based optimization is high cost to evaluate objective function and constraints needed reliability analysis. Therefore the sensitivity analysis of reliability index for approximated reanalysis is necessary. In this paper, three solution approaches are suggested and tested. The approaches include : (1) sensitivity analysis using finite difference; (2) sensitivity analysis using automatic differentiation (AD); and (3) sensitivity analysis with respect to intermediate variables using AD. Numerical example is optimized to show the reliability and effectiveness of the new algorithm.

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A Comparative Study on Reliability Index and Target Performance Measure Based Probabilistic Structural Design Optimizations (신뢰도지수와 목표성능치에 기반한 확률론적 구조설계 최적화기법에 대한 비교연구)

  • 양영순;이재옥
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2000.10a
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    • pp.32-39
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    • 2000
  • Probabilistic structural design optimization, which is characterized by the so-called probabilistic. constraints which introduce permissible probability of violation, is preferred to deterministic design optimization since unpredictable inherent uncertainties and randomness in structural and environmental properties are to be taken quantitatively into account by probabilistic design optimization. In this paper, the well-known reliability index based MPFP(Most Probable Failure Point) search approach and the newly introduced target performance measure based MPTP(Minimum Performance Target Point) search approach are summarized and compared. The present comparison focuses on the number of iterations required for the estimation of probabilistic constraints and a technique for improvement which removes exhaustive iterations is presented as well. A 10 bar truss problem is examined for this.

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A Study on the Gait Optimization of a Biped Robot (이족보행로봇의 걸음세 변화에 관한 최적화 연구)

  • Noh, Kyung-Kon;Kim, Jin-Geol
    • Proceedings of the KIEE Conference
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    • 2003.07d
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    • pp.2405-2407
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    • 2003
  • This study deals with the gait optimization of via points on biped robot. ZMP(Zero Moment Point) is most important index in a biped robot's dynamic walking stability. To stable walking of a biped robot, legs's trajectory and a desired ZMP trajectory is required, balancing weight's movement is solved by FDM(Finite Difference Method). In this study, optimal index is defined to dynamically static walking of a biped robot, and optimization of via points is applied by GA(Genetic Algorithm).

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An Optimal Design of the Rotor of BLDC Motors for Noise Reduction (BLDC 모터의 소음 저감을 위한 로터부 구조 최적설계)

  • Kim, Ji-Hoon;Ko, Kang-Ho;Kim, Min-Soo;Heo, Seoung-Jin
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2004.11a
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    • pp.972-975
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    • 2004
  • In order to reduce the noise of BLDC motor, a systematic optimization procedure for rotor structure is presented. The noise index is defined as the sum of volume velocity of FE-model that are calculated at the dominant frequencies during dehydration process, which is based on the principle of radiation simple volume source. Then, the five design variables are selected to represent the shape and layout or rotor structure. This discrete design optimization problem for minimizing the noise index is solved by 3-level orthogonal array based effect analysis. Finally, the response surface method (RSM) combined optimization approach is employed for more refining the approximate optimum.

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Query Optimization on Large Scale Nested Data with Service Tree and Frequent Trajectory

  • Wang, Li;Wang, Guodong
    • Journal of Information Processing Systems
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    • v.17 no.1
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    • pp.37-50
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    • 2021
  • Query applications based on nested data, the most commonly used form of data representation on the web, especially precise query, is becoming more extensively used. MapReduce, a distributed architecture with parallel computing power, provides a good solution for big data processing. However, in practical application, query requests are usually concurrent, which causes bottlenecks in server processing. To solve this problem, this paper first combines a column storage structure and an inverted index to build index for nested data on MapReduce. On this basis, this paper puts forward an optimization strategy which combines query execution service tree and frequent sub-query trajectory to reduce the response time of frequent queries and further improve the efficiency of multi-user concurrent queries on large scale nested data. Experiments show that this method greatly improves the efficiency of nested data query.

Study on the improvement of Search Engine Optimization

  • Sunhee Yoon
    • International Journal of Advanced Culture Technology
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    • v.11 no.2
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    • pp.358-365
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    • 2023
  • As the Internet is used as a major channel for marketing and sales, the top ranking of search engine results is becoming a key competitor among websites. Various methods exist to maintain the top ranking of websites in search engines, typically investing heavily in organic coding or search engine optimization. The purpose of this paper, we present the ranking by recognizing factors that should be removed as negative factors when designing a web page in consideration of website visibility (SEO) because if website visibility is not met, the ranking may fall behind or be completely removed from the search engine index. The experiments that recognized and ranked the negative factors of website visibility proposed in this paper were provided through theory and experiments based on the existing website visibility analysis model. The models analyzed in this paper, we expressed or quantified as scores based on the methodology of each model, and 10 items were selected as negative factors through experiments and ranked as high scores. Therefore, when designing a website, it should be considered that the website is not removed from the search engine index as it is designed by excluding high-ranking items, which are negative factors.

Robust Optimization of a Resonant-type Micro-probe Using Gradient Index Based Robust Optimal Design Method (구배 지수에 근거한 강건 최적 설계 기법을 이용한 공진형 미소탐침의 강건 최적화)

  • Han, Jeong-Sam;Kwak, Byung-Man
    • Proceedings of the KSME Conference
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    • 2003.04a
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    • pp.1254-1261
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    • 2003
  • In this paper we present a simple and efficient robust optimal design formulation and its application to a resonant-type micro probe. The basic idea is to use the Gradient Index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-efficient and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation.

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