• Title/Summary/Keyword: PSO (Particle Swarm Optimization) Algorithm

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Optimized Design of Intelligent White LED Dimming System Based on Illumination-Adaptive Algorithm (조도 적응 알고리즘 기반 지능형 White LED Dimming System의 최적화 설계)

  • Lim, Sung-Joon;Jung, Dae-Hyung;Kim, Hyun-Ki;Oh, Sung-Kwun
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.1956-1957
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    • 2011
  • 본 연구는 White LED를 이용하여 주변 밝기 변화에 빠르게 적응하는 퍼지 뉴로 Dimming Control System을 설계한다. 본 논문에서는 방사형기저함수 신경회로망(Radial Basis Function Neural Network: RBFNN)을 설계하여 실제 White LED Dimming Control System에 적용시켜 모델의 근사화 및 일반화 성능을 평가한다. 제안한 모델에서의 은닉층은 방사형기저함수를 사용하여 적합도를 구현하였고, 후반부의 연결가중치는 경사하강법을 사용한다. 이때 멤버쉽 함수의 중심점은 HCM 클러스터링 (Hard C-Means Clustering)을 적용하여 결정한다. 연결가중치는 4가지 형태의 다항식을 대입하여 출력을 평가하였다. 최종 출력의 최적화를 위하여 PSO(Particle Swarm Optimization)을 이용하여 은닉층 노드수 및 다항식 형태를 결정한다. 본 논문에서 제안한 LED Dimming Control System은 Atmega8535를 사용하여 PWM 제어 방식을 사용하고, 조도계(Cds)를 이용하여 LED의 밝기에 따른 주변의 밝기를 감지하여 조명에 적응시키는 방법을 적용하였다.

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Active Control of On-board Jitter Isolation for Spacecraft (인공위성의 내부 진동 분리를 위한 능동 제어 연구)

  • Oh, Se-Boung;Bang, Hyo-Choong;Tahk, Min-Jea
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.32 no.9
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    • pp.80-87
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    • 2004
  • Active control of on-orbit spacecraft jitter is a significant problem for future spacecraft mission requiring stringent pointing performance. Jitter is major disturbance source degrading payload pointing performance. Both passive and active jitter isolation techniques have been studied during the last decade. We present active jitter isolation for a model device in this work. The device provides active control capability by 3 degree-of-freedom control of payload in feedback control strategy. Mathematical modeling of the device is pursued which is naturally used for a baseline controller design. Simulation results are used to validate the designed control law.

A new approach for predicting sulfate ion concentration in concrete

  • Mohammad Ghanooni-Bagha;Mohsen Ali Shayanfar;Sajad Momen
    • Computers and Concrete
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    • v.33 no.1
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    • pp.1-11
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    • 2024
  • Aggressive environmental conditions, and especially the acidic effects of sulfate ion penetration, have reduced the lifetime of concrete structures in some areas, especially coastal and marine areas. In this research, at first, samples made of type II and V cement were kept in a solution of magnesium sulfate (MgSO4) for a period of 90 and 180 days, the change of appearance. Field Emission Scanning Electron Microscopy (FE-SEM) and X-Ray Diffraction (XRD), were used to analyze the microstructure and the complex mineral composition of the concrete after exposure to corrosive environments. Then solving the differential equation governing the sulfate ion penetration, which is based on the second Fick law, it has been tried to determine the concentration of sulfate ions inside the concrete. In the following, an attempt has been made to improve the prediction of sulfate ion concentration in concrete by using Crank's penetration equation. At the same time, the coefficient in the Crank's solution have been optimized by using the Particle Swarm Optimization (PSO algorithm). The comparison between the results shows that the values obtained from Crank's relation are closer to the experimental results than the equation obtained from Fick's second law and shows a more accurate prediction.

Research of Communication Coverage and Terrain Masking for Path Planning (경로생성 및 지형차폐를 고려한 통신영역 생성 방법)

  • Woo, Sang Hyo;Kim, Jae Min;Beak, InHye;Kim, Ki Bum
    • Journal of the Korea Institute of Military Science and Technology
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    • v.23 no.4
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    • pp.407-416
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    • 2020
  • Recent complex battle field demands Network Centric Warfare(NCW) ability to control various parts into a cohesive unit. In path planning filed, the NCW ability increases complexity of path planning algorithm, and it has to consider a communication coverage map as well as traditional parameters such as minimum radar exposure and survivability. In this paper, pros and cons of various propagation models are summarized, and we suggest a coverage map generation method using a Longley-Rice propagation model. Previous coverage map based on line of sight has significant discontinuities that limits selection of path planning algorithms such as Dijkstra and fast marching only. If there is method to remove discontinuities in the coverage map, optimization based path planning algorithms such as trajectory optimization and Particle Swarm Optimization(PSO) can also be used. In this paper, the Longley-Rice propagation model is used to calculate continuous RF strengths, and convert the strength data using smoothed leaky BER for the coverage map. In addition, we also suggest other types of rough coverage map generation using a lookup table method with simple inputs such as terrain type and antenna heights only. The implemented communication coverage map can be used various path planning algorithms, especially in the optimization based algorithms.

Ensemble deep learning-based models to predict the resilient modulus of modified base materials subjected to wet-dry cycles

  • Mahzad Esmaeili-Falak;Reza Sarkhani Benemaran
    • Geomechanics and Engineering
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    • v.32 no.6
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    • pp.583-600
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    • 2023
  • The resilient modulus (MR) of various pavement materials plays a significant role in the pavement design by a mechanistic-empirical method. The MR determination is done by experimental tests that need time and money, along with special experimental tools. The present paper suggested a novel hybridized extreme gradient boosting (XGB) structure for forecasting the MR of modified base materials subject to wet-dry cycles. The models were created by various combinations of input variables called deep learning. Input variables consist of the number of W-D cycles (WDC), the ratio of free lime to SAF (CSAFR), the ratio of maximum dry density to the optimum moisture content (DMR), confining pressure (σ3), and deviatoric stress (σd). Two XGB structures were produced for the estimation aims, where determinative variables were optimized by particle swarm optimization (PSO) and black widow optimization algorithm (BWOA). According to the results' description and outputs of Taylor diagram, M1 model with the combination of WDC, CSAFR, DMR, σ3, and σd is recognized as the most suitable model, with R2 and RMSE values of BWOA-XGB for model M1 equal to 0.9991 and 55.19 MPa, respectively. Interestingly, the lowest value of RMSE for literature was at 116.94 MPa, while this study could gain the extremely lower RMSE owned by BWOA-XGB model at 55.198 MPa. At last, the explanations indicate the BWO algorithm's capability in determining the optimal value of XGB determinative parameters in MR prediction procedure.

An Automatic Rhythm and Melody Composition System Considering User Parameters and Chord Progression Based on a Genetic Algorithm (유전알고리즘 기반의 사용자 파라미터 설정과 코드 진행을 고려한 리듬과 멜로디 자동 작곡 시스템)

  • Jeong, Jaehun;Ahn, Chang Wook
    • Journal of KIISE
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    • v.43 no.2
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    • pp.204-211
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    • 2016
  • In this paper, we propose an automatic melody composition system that can generate a sophisticated melody by adding non-harmony tone in the given chord progression. An overall procedure consists of two steps, which are the rhythm generation and melody generation parts. In the rhythm generation part, we designed new fitness functions for rhythm that can be controlled by a user setting parameters. In the melody generation part, we designed new fitness functions for melody based on harmony theory. We also designed evolutionary operators that are conducted by considering a musical context to improve computational efficiency. In the experiments, we compared four metaheuristics to optimize the rhythm fitness functions: Simple Genetic Algorithm (SGA), Elitism Genetic Algorithm (EGA), Differential Evolution (DE), and Particle Swarm Optimization (PSO). Furthermore, we compared proposed genetic algorithm for melody with the four algorithms for verifying performance. In addition, composition results are introduced and analyzed with respect to musical correctness.

Improved Resource Allocation Model for Reducing Interference among Secondary Users in TV White Space for Broadband Services

  • Marco P. Mwaimu;Mike Majham;Ronoh Kennedy;Kisangiri Michael;Ramadhani Sinde
    • International Journal of Computer Science & Network Security
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    • v.23 no.4
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    • pp.55-68
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    • 2023
  • In recent years, the Television White Space (TVWS) has attracted the interest of many researchers due to its propagation characteristics obtainable between 470MHz and 790MHz spectrum bands. The plenty of unused channels in the TV spectrum allows the secondary users (SUs) to use the channels for broadband services especially in rural areas. However, when the number of SUs increases in the TVWS wireless network the aggregate interference also increases. Aggregate interferences are the combined harmful interferences that can include both co-channel and adjacent interferences. The aggregate interference on the side of Primary Users (PUs) has been extensively scrutinized. Therefore, resource allocation (power and spectrum) is crucial when designing the TVWS network to avoid interferences from Secondary Users (SUs) to PUs and among SUs themselves. This paper proposes a model to improve the resource allocation for reducing the aggregate interface among SUs for broadband services in rural areas. The proposed model uses joint power and spectrum hybrid Firefly algorithm (FA), Genetic algorithm (GA), and Particle Swarm Optimization algorithm (PSO) which is considered the Co-channel interference (CCI) and Adjacent Channel Interference (ACI). The algorithm is integrated with the admission control algorithm so that; there is a possibility to remove some of the SUs in the TVWS network whenever the SINR threshold for SUs and PU are not met. We considered the infeasible system whereby all SUs and PU may not be supported simultaneously. Therefore, we proposed a joint spectrum and power allocation with an admission control algorithm whose better complexity and performance than the ones which have been proposed in the existing algorithms in the literature. The performance of the proposed algorithm is compared using the metrics such as sum throughput, PU SINR, algorithm running time and SU SINR less than threshold and the results show that the PSOFAGA with ELGR admission control algorithm has best performance compared to GA, PSO, FA, and FAGAPSO algorithms.

Design of RBFNN-based Emotional Lighting System Using RGBW LED (RGBW LED 이용한 RBFNN 기반 감성조명 시스템 설계)

  • Lim, Sung-Joon;Oh, Sung-Kwun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.62 no.5
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    • pp.696-704
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    • 2013
  • In this paper, we introduce the LED emotional lighting system realized with the aid of both intelligent algorithm and RGB LED combined with White LED. Generally, the illumination is known as a design factor to form the living place that affects human's emotion and action in the light- space as well as the purpose to light up the specific space. The LED emotional lighting system that can express emotional atmosphere as well as control the quantity of light is designed by using both RGB LED to form the emotional mood and W LED to get sufficient amount of light. RBFNNs is used as the intelligent algorithm and the network model designed with the aid of LED control parameters (viz. color coordinates (x and y) related to color temperature, and lux as inputs, RGBW current as output) plays an important role to build up the LED emotional lighting system for obtaining appropriate color space. Unlike conventional RBFNNs, Fuzzy C-Means(FCM) clustering method is used to obtain the fitness values of the receptive function, and the connection weights of the consequence part of networks are expressed by polynomial functions. Also, the parameters of RBFNN model are optimized by using PSO(Particle Swarm Optimization). The proposed LED emotional lighting can save the energy by using the LED light source and improve the ability to work as well as to learn by making an adequate mood under diverse surrounding conditions.

Computational estimation of the earthquake response for fibre reinforced concrete rectangular columns

  • Liu, Chanjuan;Wu, Xinling;Wakil, Karzan;Jermsittiparsert, Kittisak;Ho, Lanh Si;Alabduljabbar, Hisham;Alaskar, Abdulaziz;Alrshoudi, Fahed;Alyousef, Rayed;Mohamed, Abdeliazim Mustafa
    • Steel and Composite Structures
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    • v.34 no.5
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    • pp.743-767
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    • 2020
  • Due to the impressive flexural performance, enhanced compressive strength and more constrained crack propagation, Fibre-reinforced concrete (FRC) have been widely employed in the construction application. Majority of experimental studies have focused on the seismic behavior of FRC columns. Based on the valid experimental data obtained from the previous studies, the current study has evaluated the seismic response and compressive strength of FRC rectangular columns while following hybrid metaheuristic techniques. Due to the non-linearity of seismic data, Adaptive neuro-fuzzy inference system (ANFIS) has been incorporated with metaheuristic algorithms. 317 different datasets from FRC column tests has been applied as one database in order to determine the most influential factor on the ultimate strengths of FRC rectangular columns subjected to the simulated seismic loading. ANFIS has been used with the incorporation of Particle Swarm Optimization (PSO) and Genetic algorithm (GA). For the analysis of the attained results, Extreme learning machine (ELM) as an authentic prediction method has been concurrently used. The variable selection procedure is to choose the most dominant parameters affecting the ultimate strengths of FRC rectangular columns subjected to simulated seismic loading. Accordingly, the results have shown that ANFIS-PSO has successfully predicted the seismic lateral load with R2 = 0.857 and 0.902 for the test and train phase, respectively, nominated as the lateral load prediction estimator. On the other hand, in case of compressive strength prediction, ELM is to predict the compressive strength with R2 = 0.657 and 0.862 for test and train phase, respectively. The results have shown that the seismic lateral force trend is more predictable than the compressive strength of FRC rectangular columns, in which the best results belong to the lateral force prediction. Compressive strength prediction has illustrated a significant deviation above 40 Mpa which could be related to the considerable non-linearity and possible empirical shortcomings. Finally, employing ANFIS-GA and ANFIS-PSO techniques to evaluate the seismic response of FRC are a promising reliable approach to be replaced for high cost and time-consuming experimental tests.

A Study on Evaluation Method of Mixed Nash Equilibria by Using the Cournot Model for N-Genco. in Wholesale Electricity Market (도매전력시장에서 N명 발전사업자의 꾸르노 모델을 이용한 혼합 내쉬 균형점 도출 방법론 개발 연구)

  • Lim, Jung-Youl;Lee, Ki-Song;Yang, Kwang-Min;Park, Jong-Bae;Shin, Joong-Rin
    • Proceedings of the KIEE Conference
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    • 2003.07a
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    • pp.639-642
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    • 2003
  • This paper presents a method for evaluating the mixed nash equilibria of the Cournot model for N-Gencos. in wholesale electricity market. In the wholesale electricity market, the strategies of N-Genco. can be applied to the game model under the conditions which the Gencos. determine their stratgies to maximize their benefit. Generally, the Lemke algorithm is evaluated the mixed nash equlibria in the two-player game model. However, the necessary condition for the mixed equlibria of N-player are modified as the necessary condition of N-1 player by analyzing the Lemke algorithms. Although reducing the necessary condition for N-player as the one of N-1 player, it is difficult to and the mixed nash equilibria participated two more players by using the mathmatical approaches since those have the nonlinear characteristics. To overcome the above problem, this paper presents the generalized necessary condition for N-player and proposed the object function to and the mixed nash equlibrium. Also, to evaluate the mixed equilibrium through the nonlinear objective function, the Particle Swarm Optimization (PSO) as one of the heuristic algorithm are proposed in this paper. To present the mixed equlibria for the strategy of N-Gencos. through the proposed necessry condition and the evaluation approach, this paper proposes the mixed equilibrium in the cournot game model for 3-players.

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