• Earthquakes and Structures
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• v.11 no.2
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• pp.347-369
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• 2016

The main objective of this paper is the robust multi-objective optimization design of semi-active tuned mass damper (STMD) system using genetic algorithms and fuzzy logic. For optimal design of this system, it is required that the uncertainties which may exist in the system be taken into account. This consideration is performed through the robust design optimization (RDO) procedure. To evaluate the optimal values of the design parameters, three non-commensurable objective functions namely: normalized values of the maximum displacement, velocity, and acceleration of each story level are considered to minimize simultaneously. For this purpose, a fast and elitist non-dominated sorting genetic algorithm (NSGA-II) approach is used to find a set of Pareto-optimal solutions. The torsional effects due to irregularities of the building and/or unsymmetrical placements of the dampers are taken into account through the 3-D modeling of the building. Finally, the comparison of the results shows that the probabilistic robust STMD system is capable of providing a reduction of about 52%, 42.5%, and 37.24% on the maximum displacement, velocity, and acceleration of the building top story, respectively.

• Industrial Engineering and Management Systems
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• v.10 no.1
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• pp.54-64
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• 2011

The purpose of this study is to optimally allocate the human resources to tasks while minimizing the total daily human resource costs and smoothing the human resource usage. The human resource allocation problem (hRAP) under consideration contains two kinds of special constraints, i.e. operational precedence and skill constraints in addition to the ordinary constraints. To deal with the multiple objectives and the special constraints, first we designed this hRAP as a network problem and then proposed a Pareto multistage decisionbased genetic algorithm (P-mdGA). During the evolutionary process of P-mdGA, a Pareto evaluation procedure called generalized Pareto-based scale-independent fitness function approach is used to evaluate the solutions. Additionally, in order to improve the performance of P-mdGA, we use fuzzy logic controller for fine-tuning of genetic parameters. Finally, in order to demonstrate the applicability and to evaluate the performance of the proposed approach, P-mdGA is applied to solve a case study in a hotel, where the managers usually need helpful automatic support for effectively allocating hotel staff to hotel tasks.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.115-121
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• 2002

This paper presents an evolutionary design of digital IIR filters using the genetic algorithm (GA) with modified genetic operators and real-valued encoding. Conventional digital IIR filter design methods involve algebraic transformations of the transfer function of an analog low-pass filter (LPF) that satisfies prescribed filter specifications. Other types of frequency-selective digital fillers as high-pass (HPF), band-pass (BPF), and band-stop (BSF) filters are obtained by appropriate transformations of a prototype low-pass filter. In the GA-based digital IIR filter design scheme, filter coefficients are represented as a set of real-valued genes in a chromosome. Each chromosome represents the structure and weights of an individual filter. GA directly finds the coefficients of the desired filter transfer function through genetic search fur given filter specifications of minimum filter order. Crossover and mutation operators are selected to ensure the stability of resulting IIR filters. Other types of filters can be found independently from the filter specifications, not from algebraic transformations.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.10
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• pp.584-592
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• 2003

This paper presents a fuzzy-GA method for the allocation and operation of dispersed generator systems(DGs) based on load model in composite distribution systems. Groups of each individual load model consist of residential, industrial, commercial, official and agricultural load. The problem formulation considers an objective to reduce power loss of distribution systems and the constraints such as the number or total capacity of DGs and the deviation of the bus voltage. The main idea of solving fuzzy goal programming is to transform the original objective function and constraints into the equivalent multi-objectives functions with fuzzy sets to evaluate their imprecise nature for the criterion of power loss minimization, the number or total capacity of DGs and the bus voltage deviation, and then solve the problem using genetic algorithm. The method proposed is applied to IEEE 12 bus and 33 bus test systems to demonstrate its effectiveness. .

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.137-139
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• 2001

In this paper, we design a GA-fuzzy precompensator for enhancement of power system stability. Here, a fuzzy precompensator is designed as a fuzzy logic-based precompensation approach for Power System Stabilizer(PSS). This scheme is easily implemented simply by adding a fuzzy precompensator to an existing PSS. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, name1y, scaling factor, membership function and control rules. Simulation results show that the proposed control technique is superior to a conventional PSS in dynamic responses over the wide range of operating conditions and is convinced robustness and reliableness in view of structure.

• Journal of Korea Multimedia Society
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• v.10 no.10
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• pp.1284-1294
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• 2007

In this paper, a blind nonlinear channel equalization is implemented by using a Modified Fuzzy C-Means (MFCM) algorithm. The proposed MFCM searches the optimal channel output states of a nonlinear channel from the received symbols, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. Next, the desired channel states of a nonlinear channel are constructed with the elements of estimated channel output states, and placed at the center of a Radial Basis Function (RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

• Journal of Korean Association for Spatial Structures
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• v.11 no.2
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• pp.89-99
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• 2011

In this study, a smart base isolation system has been proposed to reduce dynamic responses of a spacial structure subjected to seismic excitation. MR dampers and low damping elastomeric bearings were used to compose a smart base isolation system and its vibration control performance has been investigated compared to that of the optimally designed lead-rubber bearing (LRB) isolation system. Control performance of smart base isolation system depends on control algorithm. Fuzzy controller was used in this study to effectively control the spacial structure having a smart base isolation system. Dynamic responses of the spacial structure with isolation system is conflict with base drifts and thus these two responses are selected as objective functions to apply multi-objective genetic algorithm to optimization of fuzzy controller. Based on numerical simulation results, it has been shown that the smart base isolation system proposed in this study can drastically reduce base drifts and seismic responses of the example spacial structure in comparison with the optimally designed LRB isolation system.

• International Journal of Control, Automation, and Systems
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• v.5 no.4
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• pp.436-443
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• 2007

In this paper, an intelligent method called BELBIC (Brain Emotional Learning Based Intelligent Controller) is used to control of Locally Linear Neuro-Fuzzy Model (LOLIMOT) of Washing Machine. The Locally Linear Neuro-Fuzzy Model of Washing Machine is obtained based on previously extracted data. One of the important issues in using BELBIC is its parameters setting. On the other hand, the controller design for Washing Machine is a multi objective problem. Indeed, the two objectives, energy consumption and effectiveness of washing process, are main issues in this problem, and these two objectives are in contrast. Due to these challenges, a Multi Objective Genetic Algorithm is used for tuning the BELBIC parameters. The algorithm provides a set of non-dominated set points rather than a single point, so the designer has the advantage of selecting the desired set point. With considering the proper parameters after using additional assumptions, the simulation results show that this controller with optimal parameters has very good performance and considerable saving in energy consumption.

• Journal of Korean Association for Spatial Structures
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• v.16 no.1
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• pp.43-51
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• 2016

A novel vibration control method for vibration reduction of a spacial structure subjected to earthquake excitation was proposed in this study. Generally, spatial structures have various vibration modes involving high-order modes and their natural frequencies are closely spaced. Therefore, in order to control these modes, a spatially distributed MTMDs (Multiple TMDs) method is proposed previously. MR (Magnetorheological) damper were used to enhance the control performance of the MTMDs. Accordingly, MSTMDs (Multiple Smart TMDs) were proposed in this study. An arch structure was used as an example structure because it has primary characteristics of spatial structures and it is a comparatively simple structure. MSTMDs were applied to the example arch structure and the seismic control performance were evaluated based on the numerical simulation. Fuzzy logic control algorithm (FLC) was used to generate command voltages sent for MSTMSs and the FLC was optimized by genetic algorithm. Based on the analytical results, it has been shown that the MSTMDs effectively decreased the dynamic responses of the arch structure subjected to earthquake loads.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.502-503
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• 2006

If the fault occurs on the underground Power cable system, the fault current on the sheath has the influence on all sections because it's returned through earth at the directly grounded point and operation point of SVL(Sheath Voltage Limiter) at joint box. Therefore, the earth resistance and the operation of SVL have an effect on the zero-sequence current. Then the impedance between relaying point and fault point is Increased. That causes the overreach of distance relay. For these reasons, the distance relay algorithm for protecting of the underground power cable systems was developed. It effectively advance the errors using ACI(Advanced Computing Intelligence) technique. In this algorithm, the optimization was performed by fuzzy inference system and genetic algorithm.