• 제목/요약/키워드: optimization of experiments

검색결과 1,462건 처리시간 0.029초

An Efficient Optimization Technique for Node Clustering in VANETs Using Gray Wolf Optimization

  • Khan, Muhammad Fahad;Aadil, Farhan;Maqsood, Muazzam;Khan, Salabat;Bukhari, Bilal Haider
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권9호
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    • pp.4228-4247
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    • 2018
  • Many methods have been developed for the vehicles to create clusters in vehicular ad hoc networks (VANETs). Usually, nodes are vehicles in the VANETs, and they are dynamic in nature. Clusters of vehicles are made for making the communication between the network nodes. Cluster Heads (CHs) are selected in each cluster for managing the whole cluster. This CH maintains the communication in the same cluster and with outside the other cluster. The lifetime of the cluster should be longer for increasing the performance of the network. Meanwhile, lesser the CH's in the network also lead to efficient communication in the VANETs. In this paper, a novel algorithm for clustering which is based on the social behavior of Gray Wolf Optimization (GWO) for VANET named as Intelligent Clustering using Gray Wolf Optimization (ICGWO) is proposed. This clustering based algorithm provides the optimized solution for smooth and robust communication in the VANETs. The key parameters of proposed algorithm are grid size, load balance factor (LBF), the speed of the nodes, directions and transmission range. The ICGWO is compared with the well-known meta-heuristics, Multi-Objective Particle Swarm Optimization (MOPSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO) for clustering in VANETs. Experiments are performed by varying the key parameters of the ICGWO, for measuring the effectiveness of the proposed algorithm. These parameters include grid sizes, transmission ranges, and a number of nodes. The effectiveness of the proposed algorithm is evaluated in terms of optimization of number of cluster with respect to transmission range, grid size and number of nodes. ICGWO selects the 10% of the nodes as CHs where as CLPSO and MOPSO selects the 13% and 14% respectively.

Optimization of Ultrasound-assisted Extraction of Phenolic Compounds from Salicornia herbacea Powder

  • Kim, Hui-Jeong;Lee, Jun-Ho
    • Preventive Nutrition and Food Science
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    • 제14권2호
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    • pp.129-133
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    • 2009
  • Salicornia herbacea is rich in natural minerals, dietary fibers, and potentially health-promoting phenolic compounds. In this paper, an experimental design was applied for the optimization of the ultrasound-assisted extraction of phenolic compounds from lyophilized Salicornia herbacea powder. The experiments were conducted in accordance with a five-level, three-variable central composite rotatable design (CCRD), and the effects of solvent concentration, extraction time, and extraction temperature were evaluated via response surface methodology (RSM). The optimal extraction conditions were as follows: ethanol concentration, 76.80%; extraction time, 20 min; and extraction temperature, $33.21^{\circ}C$; and the solvent concentration was the most significant parameter in this process, under which the predicted total phenolic content was 49.91 mg GAE/g sample.

Optimizing the Friction Stir Spot Welding Parameters to Attain Maximum Strength in Al/Mg Dissimilar Joints

  • Sundaram, Manickam;Visvalingam, Balasubramanian
    • Journal of Welding and Joining
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    • 제34권3호
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    • pp.23-30
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    • 2016
  • This paper discusses the optimization of friction stir spot welding (FSSW) process parameters for joining Aluminum alloy (AA6061-T6) with Magnesium alloy (AZ31B) sheets. Prior to optimization an empirical relationship was developed to predict the Tensile Shear Fracture Load (TSFL) incorporating the four most important FSSW parameters, i.e., tool rotational speed, plunge rate, dwell time and tool diameter ratio, using response surface methodology (RSM). The experiments were conducted based on four factor, five levels central composite rotatable design (CCD) matrix. The maximum TSFL obtained was 3.61kN, with the tool rotation of 1000 rpm, plunge rate of 16 mm/min, dwell time of 5 sec and tool diameter ratio of 2.5.

직교배열표와 특성함수를 이용한 Butterfly Valve의 최적설계 (A Optimization of Butterfly Valve using the Orthogonal Array and the Characteristics Fuction)

  • 강진;최종섭;박영철
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2005년도 춘계학술대회 논문집
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    • pp.1967-1974
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    • 2005
  • The butterfly valve has been used to control a flow effectively in the industrial because of its lightweight, simple structure and the rapidity of its manipulation. However, it is difficult to have the existing structural optimization using field analysis from CFD to structure analysis when the structure is influenced by fluid. This paper is evaluated the specificity to get the flow characteristic and stability of the butterfly valve using FEM and CFD. Also, it accomplished the shape optimization design using the orthogonal arrangement and characteristic function. Research result, a few experiments showed the optimal results of three dimensional structures to be multi-objective.

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유도된 이진난수 생성법을 이용한 uDEAS의 Multi-start 성능 개선 (Performance Improvement of Multi-Start in uDEAS Using Guided Random Bit Generation)

  • 김은숙;김만석;김종욱
    • 전기학회논문지
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    • 제58권4호
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    • pp.840-848
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    • 2009
  • This paper proposes a new multi-start scheme that generates guided random bits in selecting initial search points for global optimization with univariate dynamic encoding algorithm for searches (uDEAS). The proposed method counts the number of 1 in each bit position from all the previously generated initial search matrices and, based on this information, generates 0 in proportion with the probability of selecting 1. This rule is simple and effective for improving diversity of initial search points. The performance improvement of the proposed multi-start is validated through implementation in uDEAS and function optimization experiments.

Validation of a CFD model for hydraulic seals

  • Roy, Vincent Le;Guibault, Francois;Vu, Thi C.
    • International Journal of Fluid Machinery and Systems
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    • 제2권4호
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    • pp.400-408
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    • 2009
  • Optimization of seal geometries can reduce significantly the energetic losses in a hydraulic seal [1], especially for high head runner turbine. In the optimization process, a reliable prediction of the losses is needed and CFD is often used. This paper presents numerical experiments to determine an adequate CFD model for straight, labyrinth and stepped hydraulic seals used in Francis runners. The computation is performed with a finite volume commercial CFD code with a RANS low Reynolds turbulence model. As numerical computations in small radial clearances of hydraulic seals are not often encountered in the literature, the numerical results are validated with experimental data on straight seals and labyrinth seals. As the validation is satisfactory enough, geometrical optimization of hydraulic seals using CFD will be studied in future works.

버의 최소화를 위한 실험조건 최적화 (Optimization of Experimental Parameters for Burr Minimization)

  • 이상헌;이성환
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2000년도 추계학술대회논문집 - 한국공작기계학회
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    • pp.225-229
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    • 2000
  • Burrs formed during face milling operations are very hard to characterize like other machining burrs because there are many parameters which affect the cutting process. Many researchers have tried to predict burr characteristics including burr size and shapes with various experimental conditions such as cutting speed, feed rate, in-plane exit angle, number of inserts, etc., but it still remains as a challenging problem for the complicated combination effects between the parameters. In this paper, Taguchi method, which is a systematic optimization application of design and analysis of experiments, is introduced to acquire optimum cutting parameters for burr minimization. Optimized experimental conditions are provided to show the effectiveness of this approach.

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민감도 해석을 이용한 로우어 컨트롤 암의 구조 최적설계 (Structure Optimization for a Lower Control Arm Using Sensitivity Analysis)

  • 송병철;조영직;김주형;이권희;박영철
    • 한국기계가공학회지
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    • 제7권1호
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    • pp.17-21
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    • 2008
  • Recently developed automotive components are of lightweight nature, providing automobiles with a high fuel efficiency and performance. In response to those trends of car developments, this study proposes a structural optimization method for the lower control ann. Lightweight design of lower control am can be achieved through two approaches: design and material technology. In this research, the former includes optimization technology, and the latter the technologies for selecting aluminum as a steel-substitute material. In this research, the design of experiments(DOE) built in ANSYS WORKBENCH are utilized to determine the optimum shape of a Lower Control Arm. And optimum design is compared first model and reduced design variable model that considered sensitivity using orthogonal array.

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PSO를 이용한 계통연계형 인버터 전류제어기의 자동조정에 관한 연구 (A Study on Tuning of Current Controller for Grid-connected Inverter Using Particle Swarm Optimization)

  • 안종보;김원곤;황기현;박준호
    • 대한전기학회논문지:전기기기및에너지변환시스템부문B
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    • 제53권11호
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    • pp.671-679
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    • 2004
  • This paper presents the on-line current controller tuning method of grid-connected inverter using PSO(particle swarm optimization) technique for minimizing the harmonic current. Synchronous frame PI current regulator is commonly used in most distributed generation. However, due to the source voltage distortion, specially in weak AC power system, current may contain large harmonic components, which increase THD(total harmonic distortion) and deteriorates power quality. Therefore, some tuning method is necessary to improve response of current controller. This paper used the PSO technique to tune the current regulator and through simulation and experiments, usefulness of the tuning method has been verified. Especially in simulating the tuning process, ASM(average switching model) of inverter is used to shorten execution time.

준정부호 스펙트럼의 군집화 (Semidefinite Spectral Clustering)

  • 김재환;최승진
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2005년도 한국컴퓨터종합학술대회 논문집 Vol.32 No.1 (A)
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    • pp.892-894
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    • 2005
  • Graph partitioning provides an important tool for data clustering, but is an NP-hard combinatorial optimization problem. Spectral clustering where the clustering is performed by the eigen-decomposition of an affinity matrix [1,2]. This is a popular way of solving the graph partitioning problem. On the other hand, semidefinite relaxation, is an alternative way of relaxing combinatorial optimization. issuing to a convex optimization[4]. In this paper we present a semidefinite programming (SDP) approach to graph equi-partitioning for clustering and then we use eigen-decomposition to obtain an optimal partition set. Therefore, the method is referred to as semidefinite spectral clustering (SSC). Numerical experiments with several artificial and real data sets, demonstrate the useful behavior of our SSC. compared to existing spectral clustering methods.

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