• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2891-2893
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• 2005

In this paper, we introduce a new category of Self-Organizing Fuzzy Polynomial Neural Networks (SOFPNN) that is based on a genetically optimized multi-layer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. The conventional SOFPNN algorithm leads to a tendency to produce overly complex networks as well as a repetitive computation load by the trial and error method and/or the a repetitive parameter adjustment by designer. In order to generate a structurally and parametrically optimized network, such parameters need to be optimal. In this study, in solving the problems with the conventional SOFPNN, we introduce a new design approach of evolutionary optimized SOFPNN. Optimal parameters design available within FPN (viz. the no. of input variables, the order of the polynomial, input variables, and the no. of membership function) lead to structurally and parametrically optimized network which is more flexible as well as simpler architecture than the conventional SOFPNN. In addition, we determine the initial apexes of membership functions by genetic algorithm.

• Structural Engineering and Mechanics
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• v.60 no.4
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• pp.547-565
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• 2016

In this work a new 3-unknown non-polynomial shear deformation theory for the buckling and vibration analyses of functionally graded material (FGM) sandwich plates is presented. The present theory accounts for non-linear in plane displacement and constant transverse displacement through the plate thickness, complies with plate surface boundary conditions, and in this manner a shear correction factor is not required. The main advantage of this theory is that, in addition to including the shear deformation effect, the displacement field is modelled with only 3 unknowns as the case of the classical plate theory (CPT) and which is even less than the first order shear deformation theory (FSDT). The plate properties are assumed to vary according to a power law distribution of the volume fraction of the constituents. Equations of motion are derived from the Hamilton's principle. Analytical solutions of natural frequency and critical buckling load for functionally graded sandwich plates are obtained using the Navier solution. The results obtained for plate with various thickness ratios using the present non-polynomial plate theory are not only substantially more accurate than those obtained using the classical plate theory, but are almost comparable to those obtained using higher order theories with more number of unknown functions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9A
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• pp.909-916
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• 2008

In this paper, we propose and analyze M-ary pulse order time hopping multiple access ultra wideband (PO-THMA UWB) system using modified Hermite polynomial (MHP). The MHP pulses have a mutually orthogonal property between different ordered pulses and that property makes simultaneous transmission at the same time slot regardless of collision in the THMA-UWB system. Therefore, we derive the cross-correlation furlction of MHP pulses and analyze the BER of the proposed system and show that the BER performance and the transmission capacity are improved dramatically when compared with those of conventional THMA-UWB system.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.701-706
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• 2002

A set of color features has been efficiently used to measure the similarity of given images. However, the size of the color features is too large to implement an indexing scheme effectively. In this paper a new method is proposed to retrieve similar images using an interpolated color histogram. The idea is similar to the already reported methods that use the distributions of color histograms. The new method is different in that simplified color histograms decide the similarity between a query image and target images. In order to represent the distribution of the color histograms, the best order of interpolated polynomial has been simulated. After a histogram distribution is represented in a polynomial form, only a few number of polynomial coefficients are indexed and stored in a database as a color descriptor. The new method has been applied to real images and achieved satisfactory results.

• Journal of Information Technology Application
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• v.3 no.3
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• pp.25-40
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• 2001

This paper deals with the problem of generating optimal polynomials using Genetic Programming(GP). The polynomial should approximate nonlinear response surfaces. Also, there should be a consideration regarding the size of the polynomial, It is not desirable if the polynomial is too large. To build small or medium size of polynomials that enable to model nonlinear response surfaces, we use the low order Tailor series in the function set of GP, and put the constrain on generating GP tree during the evolving process in order to prevent GP trees from becoming too large size of polynomials. Also, GAGPT(Group of Additive Genetic Programming Trees) is adopted to help achieving such purpose. Two examples are given to demonstrate our method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.862-870
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• 2011

In this paper, we introduce a new topology of Radial Basis Function-based Polynomial Neural Networks (RPNN) that is based on a genetically optimized multi-layer perceptron with Radial Polynomial Neurons (RPNs). This study offers a comprehensive design methodology involving mechanisms of optimization algorithms, especially Fuzzy C-Means (FCM) clustering method and Particle Swarm Optimization (PSO) algorithms. In contrast to the typical architectures encountered in Polynomial Neural Networks (PNNs), our main objective is to develop a design strategy of RPNNs as follows : (a) The architecture of the proposed network consists of Radial Polynomial Neurons (RPNs). In here, the RPN is fully reflective of the structure encountered in numeric data which are granulated with the aid of Fuzzy C-Means (FCM) clustering method. The RPN dwells on the concepts of a collection of radial basis function and the function-based nonlinear (polynomial) processing. (b) The PSO-based design procedure being applied at each layer of RPNN leads to the selection of preferred nodes of the network (RPNs) whose local characteristics (such as the number of input variables, a collection of the specific subset of input variables, the order of the polynomial, and the number of clusters as well as a fuzzification coefficient in the FCM clustering) can be easily adjusted. The performance of the RPNN is quantified through the experimentation where we use a number of modeling benchmarks - NOx emission process data of gas turbine power plant and learning machine data(Automobile Miles Per Gallon Data) already experimented with in fuzzy or neurofuzzy modeling. A comparative analysis reveals that the proposed RPNN exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1587-1592
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• 2004

In the area of tracking control, it is important to design not only the controllers but also the trajectories to which a system has to follow. Position in the form of the $5^{th}$ order polynomial is often used with constraints of initial and final states. Smooth ending with possible minimum time is important for many systems to be away from vibrations or jerky motions. A simple polynomial-like trajectory generation method based on zero final state constraints is suggested and named ZSPOT. The effects of suggested method are shown through experiments in which a system follows an easy and computationally light reference trajectory.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.101-106
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• 2003

In the area of tracking control, it is important to design not only the controllers but also the trajectories to which a system has to follow. $5^{th}$ order polynomial is often used with constraints of initial and final states. Smooth ending with possible minimum time is important for many systems because of vibration or jerky motions. Examples are increased with development of technology in smaller, more accurate systems. On the base of a polynomial like trajectory generation method from a paper in ACC2002 and RIC(Robust Internal-loop Compensator) control scheme of Robotics and Bio-mechanics lab. of POSTECH, generalized and expanded polynomial like trajectory generation method is showed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.3
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• pp.460-466
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• 2018

For the efficient energy consumption in an urban railway station, it is necessary to know the patterns of electrical loads for each usage in detail. The electrical loads in an urban railway station have different characteristics from other normal electrical load, such as the peak load timing during a day. The lighting, HVAC, communication, and commercial loads make up large amount of electrical load for equipment in an urban railway station, and each of them has the unique specificity. These loads for each usage were estimated without measuring device by the polynomial regression method with big data such as total amount of electrical load and weather data. In the simulation with real data, the optimal polynomial regression model was third order polynomial regression model with 9 or 10 independent variables.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.567-572
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• 2004

In this research, a stable walking pattern generation method for a biped robot is presented. A biped robot is considered as constrained multibody system by several kinematic joints. The proposed method is based on the optimized polynomial approximation of the trunk motion along the moving direction. Foot motions can be designed according to the ground condition and walking speed. To minimize the deviation from the desired ZMP, the trunk motion is generated by the fifth order polynomial approximation. Walking simulation for a virtual biped robot is performed to demonstrate the effectiveness and validity of the proposed method. The method can be applied to the biped robot for stable walking pattern generation.