• Computers and Concrete
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• v.19 no.5
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• pp.457-465
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• 2017

The Taiwanese liquid crystal display (LCD) industry has traditionally produced a huge amount of waste glass that is placed in landfills. Waste glass recycling can reduce the material costs of concrete and promote sustainable environmental protection activities. Concrete is always utilized as structural material; thus, the concrete compressive strength with a variety of mixtures must be studied using predictive models to achieve more precise results. To create an efficient waste LCD glass concrete (WLGC) design proportion, the related studies utilized a multivariable regression analysis to develop a compressive strength waste LCD glass concrete equation. The mix design proportion for waste LCD glass and the compressive strength relationship is complex and nonlinear. This results in a prediction weakness for the multivariable regression model during the initial growing phase of the compressive strength of waste LCD glass concrete. Thus, the R ratio for the predictive multivariable regression model is 0.96. Neural networks (NN) have a superior ability to handle nonlinear relationships between multiple variables by incorporating supervised learning. This study developed a multivariable prediction model for the determination of waste LCD glass concrete compressive strength by analyzing a series of laboratory test results and utilizing a neural network algorithm that was obtained in a related prior study. The current study also trained the prediction model for the compressive strength of waste LCD glass by calculating the effects of several types of factor combinations, such as the different number of input variables and the relevant filter for input variables. These types of factor combinations have been adjusted to enhance the predictive ability based on the training mechanism of the NN and the characteristics of waste LCD glass concrete. The selection priority of the input variable strategy is that evaluating relevance is better than adding dimensions for the NN prediction of the compressive strength of WLGC. The prediction ability of the model is examined using test results from the same data pool. The R ratio was determined to be approximately 0.996. Using the appropriate input variables from neural networks, the model validation results indicated that the model prediction attains greater accuracy than the multivariable regression model during the initial growing phase of compressive strength. Therefore, the neural-based predictive model for compressive strength promotes the application of waste LCD glass concrete.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.343-350
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• 2000

In this paper, we propose the Multi-FPNN(Fuzzy Polynomial Neural Networks) model based on FNN and PNN(Polyomial Neural Networks) for optimal system identifacation. Here FNN structure is designed using fuzzy input space divided by each separated input variable, and urilized both in order to get better output performace. Each node of PNN structure based on GMDH(Group Method of Data handing) method uses two types of high-order polynomials such as linearane and quadratic, and the input of that node uses three kinds of multi-variable inputs such as linear and quadratic, and the input of that node and Genetic Algorithms(GAs) to identify both the structure and the prepocessing of parameters of a Multi-FPNN model. Here, HCM clustering method, which is carried out for data preproessing of process system, is utilized to determine the structure method, which is carried out for data preprocessing of process system, is utilized to determance index with a weighting factor is used to according to the divisions of input-output space. A aggregate performance inddex with a wegihting factor is used to achieve a sound balance between approximation and generalization abilities of the model. According to the selection and adjustment of a weighting factor of this aggregate abjective function which it is acailable and effective to design to design and optimal Multi-FPNN model. The study is illustrated with the aid of two representative numerical examples and the aggregate performance index related to the approximation and generalization abilities of the model is evaluated and discussed.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.7
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• pp.378-388
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• 2000

In this paper, we propose Fuzzy Polynomial Neural Networks(FPNN) based on Polynomial Neural Networks(PNN) and Fuzzy Neural Networks(FNN) for model identification of complex and nonlinear systems. The proposed FPNN is generated from the mutually combined structure of both FNN and PNN. The one and the other are considered as the premise part and consequence part of FPNN structure respectively. As the consequence part of FPNN, PNN is based on Group Method of Data Handling(GMDH) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and self-organizing networks that can be generated. FPNN is available effectively for multi-input variables and high-order polynomial according to the combination of FNN with PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get better output performance with superb predictive ability. As the premise part of FPNN, FNN uses both the simplified fuzzy inference as fuzzy inference method and error back-propagation algorithm as learning rule. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using genetic algorithms. And we use two kinds of FNN structure according to the division method of fuzzy space of input variables. One is basic FNN structure and uses fuzzy input space divided by each separated input variable, the other is modified FNN structure and uses fuzzy input space divided by mutually combined input variables. In order to evaluate the performance of proposed models, we use the nonlinear function and traffic route choice process. The results show that the proposed FPNN can produce the model with higher accuracy and more robustness than any other method presented previously. And also performance index related to the approximation and prediction capabilities of model is evaluated and discussed.

• Journal of Environmental Science International
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• v.25 no.6
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• pp.799-815
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• 2016

In this study, according to the reference setting based on the runoff video of 9:00 where the highest water level of 3.94 m has been recorded during the runoff of Cheon-mi Stream in Jeju Island by the attack of Typhoon no. 16 Sanba on September $17^{th}$, 2012, the error rate of long-distance and short-distance velocimetry and real-distance change rate by input error have been calculated and the input range value of reference point by stream has been suggested. In the reference setting process, if a long-distance reference point input error occurs, the real-distance change rate of 0.35 m in the x-axis direction and 1.35 m in y-axis direction is incurred by the subtle input error of 2~11 pixels, and if a short-distance reference point input error occurs, the real-distance change rate of 0.02 m in the x-axis direction and 0.81 m in y-axis direction is incurred by the subtle input error of 1~11 pixels. According to the long-distance reference point setting variable, the velocity error rate showed the range of fluctuation of at least 14.36% to at most 76.06%, and when calculating flux, it showed a great range of fluctuation of at least 20.48% to at most 78.81%.

• Journal of Power Electronics
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• v.17 no.4
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• pp.1048-1057
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• 2017

An indirect matrix converter (IMC) is a modern power generation system that enables a direct ac/ac conversion without the need for any bulky and limited lifetime electrolytic capacitor. This system also allows four-quadrant operation, generation of sinusoidal output voltage waveforms with variable frequency and amplitude, and control of input power factor. This study proposes a pulse-width modulation-based sliding-mode controller to achieve unity input-power factor operation of the IMC independently of the active power exchanged with the grid, as well as a fast dynamic response. The designed equivalent control law determines, at each sampling period, the appropriate q-axis component of the modulated input current to be injected into the grid through the LC input filter. An integral term of the error is included in the expression of the sliding surface to increase the accuracy of the control method. A double space vector modulation method is used to synthesize the direction of the space vector of the input currents as required by the sliding-mode controller and the space vectors of the target output voltages. Simulation and experimental results are provided to show the effectiveness and evaluate the performance of the proposed control method.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4195-4208
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• 2022

In this study, operator habitability was numerically evaluated in the event of a fire at the main control bench board (MCB) in a reference main control room (MCR). It was investigated if evacuation variables including hot gas layer temperature (HGLT), heat flux (HF), and optical density (OD) at 1.8 m from the MCR floor exceed the reference evacuation criteria provided in NUREG/CR-6850. For a fire model validation, the simulation results of the reference MCR were compared with existing experimental results on the same reference MCR. In the simulation, various input parameters were applied to the MCB panel fire scenario: MCR height, peak heat release rate (HRR) of a panel, number of panels where fire propagation occurs, fire propagation time, door open/close conditions, and mechanical ventilation operation. A specialized-average HRR (SAHRR) concept was newly devised to comprehensively investigate how the various input parameters affect the operator's habitability. Peak values of the evacuation variables normalized by evacuation criteria of NUREG/CR-6850 were well-correlated as the power function of the SAHRR for the various input parameters. In addition, the evacuation time map was newly utilized to investigate how the evacuation time for different SAHRR was affected by changing the various input parameters. In the previous studies, it was found that the OD is the most dominant variable to determine the MCR evacuation time. In this study, however, the evacuation time map showed that the HF is the most dominant factor at the condition of without-mechanical ventilation for the MCR with a partially-open false ceiling, but the OD is the most dominant factor for all the other conditions. Therefore, the method using the SAHRR and the evacuation time map was very useful to effectively and comprehensively evaluate the operator habitability for the various input parameters in the event of MCB fires for the reference MCR.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.533-541
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• 2005

In this paper, a wind turbine with power splitting transmission, which is realized through a novel three-shaft planetary, is presented. The input shaft of the transmission is driven by the rotor of the wind turbine, the output shaft is connected to the grid via the main generator (asynchronous generator), and the third shaft is driven by a control motor with variable speed. The dynamic models of the sub systems of this wind turbine, e.g. the rotor aerodynamics, the drive train dynamics and the power generation unit dynamics, were given and linearized at an operating point. These sub models were integrated in a multidisciplinary dynamic model, which is suitable for control syntheses to optimize the utilization of wind energy and to reduce the excessive dynamic loads. The important dynamic behaviours were investigated and a wind turbine with a soft main shaft was recommend.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.5
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• pp.285-292
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• 2014

The commonly used Newton-Raphson's floating-point number divider algorithm performs two multiplications in one iteration. In this paper, a tentative K'th Newton-Raphson's floating-point number divider algorithm which performs K times multiplications in one iteration is proposed. Since the number of multiplications performed by the proposed algorithm is dependent on the input values, the average number of multiplications per an operation in single precision and double precision divider is derived from many reciprocal tables with varying sizes. In addition, an error correction algorithm, which consists of one multiplication and a decision, to get exact result in divider is proposed. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a floating point number divider unit. Also, it can be used to construct optimized approximate reciprocal tables.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.4
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• pp.55-61
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• 1995

Variable structure control (VSC) can be used for the control of power plants required stability and robustness such as elevator control. It has no overshoot and is insensitive to parameter variations and disturbances in the sliding mode where the system structure is changed with the sliding surface in the center. But in the real system, VSC has a high frequency chattering which has a bad influence upon the control system proformances. In this paper, to alleviate the high frequency chattering, a binary controller (BC) with inertial type external loop is implemented by DSP and applied to position control of brushless DC motor. Binary controller has external loop to generate the continuous control input with the flexible variation of primary loop gain. Thus it has the property of chattering alleviation in addition to advantages of the conventional variable structure control.

• New & Renewable Energy
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• v.7 no.4
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• pp.58-65
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• 2011

In variable-speed variable-pitch wind turbines, the conventional approach for controlling power-production operation relies on a generator-torque controller and a rotor-collective blade-pitch controller. Both controllers use the generator speed measurement as the sole feedback input. In order to mitigate unwanted excitation of the control system, many filters are adopted. In this study, the characteristics of some filters for signal processing are investigated based on frequency response function. They include low-pass filters, band-pass filters, and notch filters. Especially, this study focuses on design parameters of their filters.