• Title/Summary/Keyword: optimization-based framework

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Development of Framework of Linkage between Geometric Modeling and Finite Element Analysis for Shape Optimization of Shell Surfaces (쉘 곡면 형상의 최적 설계를 위한 유한요소해석과 기하학적 모델링의 연동)

  • Kim,Hyeon-Cheol;No,Hui-Yeol;Jo,Maeng-Hyo
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.31 no.8
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    • pp.27-35
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    • 2003
  • Geometric modeling tool and analysis tool of shell surface have been developed in the different environments and purposes. Thus they cannot be naturally fitted to each other for the integrated design and analysis. In the present study, an integrated framework of geometric modeling, analysis, and design optimization is proposed. It is based on the common representation of B-spline surface patch. In the analysis module, a geometrically-exact shell finite element is implemented. In shape optimization module, control points of the surface are selected as design variables. For the computation of shape sensitivities, semi-analytical method is used. Sequential linear programming(SLP) is adopted for the shape optimization of surfaces. The developed integrated framework should serve as a powerful tool for the geometric modeling, analysis, and shape design of surfaces.

Trust Predicated Routing Framework with Optimized Cluster Head Selection using Cuckoo Search Algorithm for MANET

  • Sekhar, J. Chandra;Prasad, Ramineni Sivarama
    • IEIE Transactions on Smart Processing and Computing
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    • v.4 no.2
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    • pp.115-125
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    • 2015
  • This paper presents a Cuckoo search algorithm to secure adversaries misdirecting multi-hop routing in Mobile ad hoc networks (MANETs) using a robust Trust Predicated Routing Framework with an optimized cluster head selection. The clustering technique designed in this framework leads to efficient routing in MANETs. The heavy work load in the node causes an energy drop in cluster head, which leads to re-clustering of the group, and another cluster head is selected to avoid packet loss during data transmission. The problem in the re-clustering process is that the overall efficiency of the routing process is reduced and the processing time is increased. A Cuckoo search based optimization algorithm is proposed to solve the problem of re-clustering by selecting the secondary cluster head within the initially formed cluster group and eliminating the reclustering process. The proposed framework enables a node to select a reliable and secure route for MANET and the performance can be evaluated by comparing the simulated results with the AODV routing protocol, which shows that the performance of the proposed routing protocol are improved significantly.

Optimization Driven MapReduce Framework for Indexing and Retrieval of Big Data

  • Abdalla, Hemn Barzan;Ahmed, Awder Mohammed;Al Sibahee, Mustafa A.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.5
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    • pp.1886-1908
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    • 2020
  • With the technical advances, the amount of big data is increasing day-by-day such that the traditional software tools face a burden in handling them. Additionally, the presence of the imbalance data in big data is a massive concern to the research industry. In order to assure the effective management of big data and to deal with the imbalanced data, this paper proposes a new indexing algorithm for retrieving big data in the MapReduce framework. In mappers, the data clustering is done based on the Sparse Fuzzy-c-means (Sparse FCM) algorithm. The reducer combines the clusters generated by the mapper and again performs data clustering with the Sparse FCM algorithm. The two-level query matching is performed for determining the requested data. The first level query matching is performed for determining the cluster, and the second level query matching is done for accessing the requested data. The ranking of data is performed using the proposed Monarch chaotic whale optimization algorithm (M-CWOA), which is designed by combining Monarch butterfly optimization (MBO) [22] and chaotic whale optimization algorithm (CWOA) [21]. Here, the Parametric Enabled-Similarity Measure (PESM) is adapted for matching the similarities between two datasets. The proposed M-CWOA outperformed other methods with maximal precision of 0.9237, recall of 0.9371, F1-score of 0.9223, respectively.

Development of NASTRAN-based Optimization Framework for Vibration Optimum Design of Ship Structure. (선박 구조물의 진동 최적설계를 위한 NASTRAN 기반 최적화 프레임웍의 제안)

  • Kong, Y.M.;Choi, S.H.;Chae, S.I.;Song, J.D.;Kim, Y.H.;Yang, B.S.
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.15 no.11 s.104
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    • pp.1223-1231
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    • 2005
  • Recently, the issue of ship nitration due to the large scale, high speed and lightweight of ship is emerging. For pleasantness in the cabin, shipbuilders are asked for strict vibration criteria and the degree of nitration level at a deckhouse became an important condition for taking order from customers. This study proposes a new optimization framework that is NASTRAN external call type optimization method (OptShip) and applies to an optimum design to decrease the nitration level of a deckhouse. The merits of this method are capable of using of global searching method and selecting of various objective function and design variables. The global optimization algorithms used here are random tabu search method which has fast converging speed and searches various size domains and genetic algorithm which searches multi-point solutions and has a good search capability in a complex space. By adapting OptShip to full-scale model, the validity of the suggested method was investigated.

Using Ant Colony Optimization to Find the Best Precautionary Measures Framework for Controlling COVID-19 Pandemic in Saudi Arabia

  • Alshamrani, Raghad;Alharbi, Manal H.
    • International Journal of Computer Science & Network Security
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    • v.22 no.10
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    • pp.352-358
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    • 2022
  • In this paper, we study the relationship between infection rates of covid 19 and the precautionary measures and strict protocols taken by Saudi Arabia to combat the spread of the coronavirus disease and minimize the number of infected people. Based on the infection rates and the timetable of precautionary measures, the best framework of precautionary measures was identified by applying the traveling salesman problem (TSP) that relies on ant colony optimization (ACO) algorithms. The proposed algorithm was applied to daily infected cases data in Saudi Arabia during three periods of precautionary measures: partial curfew, whole curfew, and gatherings penalties. The results showed the partial curfew and the whole curfew for some cities have the minimum total cases over other precautionary measures. The gatherings penalties had no real effect in reducing infected cases as the other two precautionary measures. Therefore, in future similar circumstances, we recommend first applying the partial curfew and the whole curfew for some cities, and not considering the gatherings penalties as an effective precautionary measure. We also recommend re-study the application of the grouping penalty, to identify the reasons behind the lack of its effectiveness in reducing the number of infected cases.

Development of Agent Module of Integrated Design System for Centrifugal Pump Design Optimization (원심펌프 최적설계를 위한 통할설계 시스템의 Agent 모듈 개발)

  • Choi, Bum-Seog;Kim, Myung-Bae;Lee, Kong-Hoon
    • 유체기계공업학회:학술대회논문집
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    • 2005.12a
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    • pp.491-496
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    • 2005
  • A pump design system was constructed by several integrating in-house programs and commercial softwares to design and evaluate centrifugal pumps. An agent-based prototype framework has been developed for collaborative design and optimization of a centrifugal pump. This paper introduces the feasible technology needed to construct a pump design system based on software agents. The integrated design system, developed in the present study, was used in designing a centrifugal pump and modifying its impeller shape by using optimization processes to increase the pump performance.

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Hull Form Optimization Based on From Parameter Design (Form Parameter Design 을 이용한 선형최적화)

  • Lee, Yeon-Seung;Choi, Young-Bok
    • Journal of the Society of Naval Architects of Korea
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    • v.46 no.6
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    • pp.562-568
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    • 2009
  • Hull form generation and variation methods to be mainly discussed in this study are based on the fairness optimized B-Spline form parameter curves (FOBFC). These curves can be used both as indirect modification function for variation and as geometric entities for hull form generation. The flexibility and functionality of geometric control technique play the most important role for the success of hull form optimization. This study shows the hydrodynamic optimization process and the characteristics of optimum design hull forms of a 14,000TEU containership and 60K LPG carrier. SHIPFLOW has been used as a CFD solver and FS-Framework as a geometric modeler and optimizer.

Personalized Web Service Recommendation Method Based on Hybrid Social Network and Multi-Objective Immune Optimization

  • Cao, Huashan
    • Journal of Information Processing Systems
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    • v.17 no.2
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    • pp.426-439
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    • 2021
  • To alleviate the cold-start problem and data sparsity in web service recommendation and meet the personalized needs of users, this paper proposes a personalized web service recommendation method based on a hybrid social network and multi-objective immune optimization. The network adds the element of the service provider, which can provide more real information and help alleviate the cold-start problem. Then, according to the proposed service recommendation framework, multi-objective immune optimization is used to fuse multiple attributes and provide personalized web services for users without adjusting any weight coefficients. Experiments were conducted on real data sets, and the results show that the proposed method has high accuracy and a low recall rate, which is helpful to improving personalized recommendation.

SEQUENTIAL MINIMAL OPTIMIZATION WITH RANDOM FOREST ALGORITHM (SMORF) USING TWITTER CLASSIFICATION TECHNIQUES

  • J.Uma;K.Prabha
    • International Journal of Computer Science & Network Security
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    • v.23 no.4
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    • pp.116-122
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    • 2023
  • Sentiment categorization technique be commonly isolated interested in threes significant classifications name Machine Learning Procedure (ML), Lexicon Based Method (LB) also finally, the Hybrid Method. In Machine Learning Methods (ML) utilizes phonetic highlights with apply notable ML algorithm. In this paper, in classification and identification be complete base under in optimizations technique called sequential minimal optimization with Random Forest algorithm (SMORF) for expanding the exhibition and proficiency of sentiment classification framework. The three existing classification algorithms are compared with proposed SMORF algorithm. Imitation result within experiential structure is Precisions (P), recalls (R), F-measures (F) and accuracy metric. The proposed sequential minimal optimization with Random Forest (SMORF) provides the great accuracy.

Spacecraft Radiator Design Optimization Approach of Combining Optimization Algorithm with Thermal Analysis (최적화알고리즘과 열해석을 통합한 위성방열판 설계의 최적화 방법에 관한 연구)

  • Kim, Hui-Kyung
    • Aerospace Engineering and Technology
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    • v.12 no.2
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    • pp.24-29
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    • 2013
  • A spacecraft radiator is a thermal control method to eject internally dissipated heat into the space generated from operation of unit boxes. The efficiency of thermal design may be improved by optimizing radiator design. In this paper, the optimization approach method of node-based radiator design was suggested which is to combine numerical thermal analysis with optimization algorithm. This method has meaning that it can be used practically to implement the spacecraft radiator design regardless of thermal analysis and optimization algorithm software and maintain the same basic concept of an ordinary radiator design approach based on node division of a thermal model. The overall analysis framework with thermal analysis and optimization algorithm would be presented.