• Title/Summary/Keyword: Hybrid adaptive

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A hybrid simulated annealing and optimality criteria method for optimum design of RC buildings

  • Li, Gang;Lu, Haiyan;Liu, Xiang
    • Structural Engineering and Mechanics
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    • v.35 no.1
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    • pp.19-35
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    • 2010
  • This paper proposes a hybrid heuristic and criteria-based method of optimum design which combines the advantages of both the iterated simulated annealing (SA) algorithm and the rigorously derived optimality criteria (OC) for structural optimum design of reinforced concrete (RC) buildings under multi-load cases based on the current Chinese design codes. The entire optimum design procedure is divided into two parts: strength optimum design and stiffness optimum design. A modified SA with the strategy of adaptive feasible region is proposed to perform the discrete optimization of RC frame structures under the strength constraints. The optimum stiffness design is conducted using OC method with the optimum results of strength optimum design as the lower bounds of member size. The proposed method is integrated into the commercial software packages for building structural design, SATWE, and for finite element analysis, ANSYS, for practical applications. Finally, two practical frame-shear-wall structures (15-story and 30-story) are optimized to illustrate the effectiveness and practicality of the proposed optimum design method.

A Design of Acoustic-based Underwater Image Transmission System Based on the Multipath Analysis. (Multipath를 고려한 수중영상 전송 시스템 설계)

  • 임용곤;박종원;최영철
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.5 no.1
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    • pp.202-211
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    • 2001
  • This paper deals with an analysis of multipath which affect a transmission performance in underwater acoustic channel. Underwater acoustic channel with multipath structure is introduced to mathematical modelling for a basin environment. In this paper, SMR(Signal to Multipath Ratio) which is defined as a parameter of multipath's effect is presented as a mathematical equation, and the equation of SMR is simulated by MATLAB program. Furthermore, this paper is also dealt with an implementation of modulation and demodulation system for acoustic transmission. Acoustic Transmission is limited by frequency bandwidth, so $\pi/4 QPSK$(Quadrature Phase Shift Keying) methods which is very useful at frequency ]imitation and FM(Frequency Modulation) are used at acoustic communication system. This implemented hybrid modulation/demodulation system is used as an analog board of image transmission system. In this system, adaptive equalization for reducing the multipath effect and baseline JPEG used for an image compressing are also stated.

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Improving the Training Performance of Multilayer Neural Network by Using Stochastic Approximation and Backpropagation Algorithm (확률적 근사법과 후형질과 알고리즘을 이용한 다층 신경망의 학습성능 개선)

  • 조용현;최흥문
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.4
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    • pp.145-154
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    • 1994
  • This paper proposes an efficient method for improving the training performance of the neural network by using a hybrid of a stochastic approximation and a backpropagation algorithm. The proposed method improves the performance of the training by appliying a global optimization method which is a hybrid of a stochastic approximation and a backpropagation algorithm. The approximate initial point for a stochastic approximation and a backpropagation algorihtm. The approximate initial point for fast global optimization is estimated first by applying the stochastic approximation, and then the backpropagation algorithm, which is the fast gradient descent method, is applied for a high speed global optimization. And further speed-up of training is made possible by adjusting the training parameters of each of the output and the hidden layer adaptively to the standard deviation of the neuron output of each layer. The proposed method has been applied to the parity checking and the pattern classification, and the simulation results show that the performance of the proposed method is superior to that of the backpropagation, the Baba's MROM, and the Sun's method with randomized initial point settings. The results of adaptive adjusting of the training parameters show that the proposed method further improves the convergence speed about 20% in training.

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Optimal Speed Control of Hybrid Electric Vehicles

  • Yadav, Anil Kumar;Gaur, Prerna;Jha, Shyama Kant;Gupta, J.R.P.;Mittal, A.P.
    • Journal of Power Electronics
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    • v.11 no.4
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    • pp.393-400
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    • 2011
  • The main objective of this paper is to control the speed of Nonlinear Hybrid Electric Vehicle (HEV) by controlling the throttle position. Various control techniques such as well known Proportional-Integral-Derivative (PID) controller in conjunction with state feedback controller (SFC) such as Pole Placement Technique (PPT), Observer Based Controller (OBC) and Linear Quadratic Regulator (LQR) Controller are designed. Some Intelligent control techniques e.g. fuzzy logic PD, Fuzzy logic PI along with Adaptive Controller such as Self Organizing Controller (SOC) is also designed. The design objective in this research paper is to provide smooth throttle movement, zero steady-state speed error, and to maintain a Selected Vehicle (SV) speed. A comparative study is carried out in order to identify the superiority of optimal control technique so as to get improved fuel economy, reduced pollution, improved driving safety and reduced manufacturing costs.

FE MODEL UPDATING OF ROTOR SHAFT USING OPTIMIZATION TECHNIQUES (최적화 기법을 이용한 로터 축 유한요소모델 개선)

  • Kim, Yong-Han;Feng, Fu-Zhou;Yang, Bo-Suk
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.11a
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    • pp.104-108
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    • 2003
  • Finite element (FE) model updating is a procedure to minimize the differences between analytical and experimental results, which can be usually posed as an optimization problem. This paper aims to introduce a hybrid optimization algorithm (GA-SA), which consists of a Genetic algorithm (GA) stage and an Adaptive Simulated Annealing (ASA) stage, to FE model updating for a shrunk shaft. A good agreement of the first four natural frequencies has been achieved obtained from GASA based updated model (FEgasa) and experiment. In order to prove the validity of GA-SA, comparisons of natural frequencies obtained from the initial FE model (FEinit), GA based updated model (FEga) and ASA based updated model (FEasa) are carried out. Simultaneously, the FRF comparisons obtained from different FE models and experiment are also shown. It is concluded that the GA, ASA, GA-SA are powerful optimization techniques which can be successfully applied to FE model updating, the natural frequencies and FRF obtained from all the updated models show much better agreement with experiment than that obtained from FEinit model. However, FEgasa is proved to be the most reasonable FE model, and also FEasa model is better than FEga model.

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A Study on the New Hybrid Interference Cancellation Scheme for Multirate DS-CDMA (다중전송률 DS-CDMA 시스템을 위한 새로운 하이브리드 간섭제거기)

  • Kim, Nam-Sun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.9C
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    • pp.1219-1226
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    • 2004
  • The objective of this paper is to proposed a new Hybrid Interference Cancellation(HlC) receiver to cancel MAI in a multirate DS-CDMA system based on multiple processing gain(MPG). We propose a new improved HIC scheme that divides the active users with different data rates split into a number of groups for effectives cancellation Between each group, GW-PIC is performed to cancel other group signals and within them, SIC is carried out to remove multiple access interference in group. We analyze the performance of the proposed receiver in terms of the bit error rate(BER) and examine its performance. As a conclusion, computer simulations show that the proposed schemes outperforms adaptive multistage PIC and conventional SIC receiver over AWGN channel.

Layered Turbo codes combined with space time codes for satellite systems (위성 시스템에서의 시공간 부호 기술과 결합된 계층적 터보 부호)

  • Kim, Young-Min;Kim, Soo-Young
    • Journal of Satellite, Information and Communications
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    • v.5 no.2
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    • pp.40-44
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    • 2010
  • A layered coding scheme is one of the adaptive receiving techniques for unidirectional services such as multimedia broadcasting and multicasting services (MBMS), where we cannot utilize feedback information. The layered coding scheme can be used with hierarchical modulations by combining suitable code rates and modulation orders of each. In addition, it has been reported that hybrid and/or integrated satellite systems can effectively achieve transmit diversity gains by appropriate utilization of space time coding combined with turbo codes. This paper proposes a layered turbo coding schemes for hybrid and/or integrated satellite systems. We first introduce the system architecture and operational principle of the proposed scheme, and discuss the applicability.

Hybrid Rule-Interval Variation(HRIV) Method for Stabilization a Class of Nonlinear Systems (비선형 시스템의 안정을 위한 HRIV 방법의 제안)

  • Myung, Hwan-Chun;Z. Zenn Bien
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.05a
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    • pp.249-255
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    • 2000
  • HRIV(Hybrid Rule-Interval Variation) method is presented to stabilize a class of nonlinear systems, where SMC(Sliding Mode Control) and ADC (ADaptive Control) schemes are incorporated to overcome the unstable characteristics of a conventional FLC(Fuzzy Logic Control). HRIV method consists of two modes: I-mode (Integral Sliding Mode PLC) and R-mode(RIV method). In I-mode, SMC is used to compensate for MAE(Minimum Approximation Error) caused by the heuristic characteristics of FLC. In R-mode, RIV method reduces interval lengths of rules as states converge to an equilibrium point, which makes the defined Lyapunov function candidate negative semi-definite without considering MAE, and the new uncertain parameters generated in R-mode are compensated by SMC. In RIV method, the overcontraction problem that the states are out of a rule-table can happen by the excessive reduction of rule intervals, which is solved with a dynamic modification of rule-intervals and a transition to I-mode. Especially, HRIV method has advantages to use the analytic upper bound of MAE and to reduce Its effect in the control input, compared with the previous researches. Finally, the proposed method is applied to stabilize a simple nonlinear system and a modified inverted pendulum system in simulation experiments.

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Efficiency Optimization Control of SynRM with Hybrid Artificial Intelligent Controller (하이브리드 인공지능 제어기에 의한 SynRM의 효율 최적화 제어)

  • Choi, Jung-Sik;Ko, Jae-Sub;Lee, Jung-Ho;Chung, Dong-Hwa
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2006.05a
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    • pp.321-326
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    • 2006
  • This paper is proposed an efficiency optimization control algorithm for a synchronous reluctance motor which minimizes the copper and iron losses. The design of the speed controller based on adaptive fuzzy-neural networks(AFNN) controller that is implemented using fuzzy control and neural networks. There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization controller is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. It is shown that the current components which directly govern the torque production have been very well regulated by the efficiency optimization control scheme. The proposed algorithm allows the electromagnetic losses in variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of the hybrid artificial intelligent controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

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On-Line Travel Time Estimation Methods using Hybrid Neuro Fuzzy System for Arterial Road (검지자료합성을 통한 도시간선도로 실시간 통행시간 추정모형)

  • 김영찬;김태용
    • Journal of Korean Society of Transportation
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    • v.19 no.6
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    • pp.171-182
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    • 2001
  • Travel Time is an important characteristic of traffic conditions in a road network. Currently, there are so many road users to get a unsatisfactory traffic information that is provided by existing collection systems such as, Detector, Probe car, CCTV and Anecdotal Report. This paper presents the results achieved with Data Fusion Model, Hybrid Neuro Fuzzy System for on - line estimation of travel times using RTMS(Remote Traffic Microwave Sensor) and Probe Data in the signalized arterial road. Data Fusion is the most important process to compose the various of data which can present real value for traffic situation and is also the one of the major process part in the TIC(Traffic Information Center) for analyzing and processing data. On-line travel time estimation methods(FALEM) on the basis of detector data has been evaluated by real value under KangNam Test Area.

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