• 한국건설관리학회논문집
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• 제5권4호
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• pp.79-86
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• 2004

One of the most difficult tasks in pavement management information systems is establishing the links between performance measures of a structure and the design and construction inputs. In-situ pavement performance can be considered a response variable to many project input variables, such as design, construction, and traffic loading effects. If we are to fully understand the component of pavement performance and specify the inputs through design and construction specifications to achieve that performance we must develop quantitative relationship between input and response variables through a scientific, fully integrated Pavement Performance Analysis System (PPAS). Hence, the objective of this study is to design a database model required for developing an effective database template that will allow analysis of pavement performance measures based on design and construction information linked by location. In order to select the most appropriate database model, a conceptual database model (Entity Relationship Model) and dimensional model, which is believed to be the most effective modeling technique for data warehouse project, are designed and compared. It is believed that other state highway agencies could adopt the proposed design strategy for implementing a PPAS at the discretion of the state highway agencies.

• International Journal of Naval Architecture and Ocean Engineering
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• 제7권4호
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• pp.739-749
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• 2015

A new conceptual dual-buoy Wave Energy Converter (WEC) for the enhancement of energy extraction efficiency is suggested. Based on actual wave data, the design process for the suggested WEC is conducted in such a way as to ensure that it is suitable in real sea. Actual wave data measured in Korea's East Sea (position: $36.404N^{\circ}$ and $129.274E^{\circ}$) from May 1, 2002 to March 29, 2005 were used as the input wave spectrum for the performance estimation of the dual-buoy WEC. The suggested WEC, a point absorber type, consists of two concentric floating circular cylinders (an inner and a hollow outer buoy). Multiple resonant frequencies in proposed WEC affect the Power Ttake-off (PTO) performance of the WEC. Based on the numerical results, several design strategies are proposed to further enhance the extraction efficiency, including intentional mismatching among the heave natural frequencies of dual buoys, the natural frequency of the internal fluid, and the peak frequency of the input wave spectrum.

• 전기학회논문지
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• 제61권2호
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• pp.312-320
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• 2012

In this study, we introduce a new design methodology of a granular-oriented self-organizing polynomial neural networks (GoSOPNNs) that is based on multi-layer perceptron with Context-based Polynomial Neurons (CPNs) or Polynomial Neurons (PNs). In contrast to the typical architectures encountered in polynomial neural networks (PNN), our main objective is to develop a methodological design strategy of GoSOPNNs as follows : (a) The 1st layer of the proposed network consists of Context-based Polynomial Neuron (CPN). In here, CPN is fully reflective of the structure encountered in numeric data which are granulated with the aid of Context-based Fuzzy C-Means (C-FCM) clustering method. The context-based clustering supporting the design of information granules is completed in the space of the input data while the build of the clusters is guided by a collection of some predefined fuzzy sets (so-called contexts) defined in the output space. (b) The proposed design procedure being applied at each layer of GoSOPNN leads to the selection of preferred nodes of the network (CPNs or PNs) whose local characteristics (such as the number of contexts, the number of clusters, a collection of the specific subset of input variables, and the order of the polynomial) can be easily adjusted. These options contribute to the flexibility as well as simplicity and compactness of the resulting architecture of the network. For the evaluation of performance of the proposed GoSOPNN network, we describe a detailed characteristic of the proposed model using a well-known learning machine data(Automobile Miles Per Gallon Data, Boston Housing Data, Medical Image System Data).

• Structural Engineering and Mechanics
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• 제85권5호
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• pp.635-644
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• 2023

The design of honeycomb sandwich structures is often challenging because these structures can be tailored from a variety of possible cores and face sheets configurations, therefore, the design of sandwich structures is characterized as a time-consuming and complex task. A data-driven computational approach that integrates the analytical method and Artificial Neural Network (ANN) is developed by the authors to rapidly predict the design of sandwich structures for a targeted maximum structural deflection. The elaborated ANN reverse design approach is applied to obtain the thickness of the sandwich core, the thickness of the laminated face sheets, and safety factors for composite sandwich structure. The required data for building ANN model were obtained using the governing equations of sandwich components in conjunction with the Monte Carlo Method. Then, the functional relationship between the input and output features was created using the neural network Backpropagation (BP) algorithm. The input variables were the dimensions of the sandwich structure, the applied load, the core density, and the maximum deflection, which was the reverse input given by the designer. The outstanding performance of reverse ANN model revealed through a low value of mean square error (MSE) together with the coefficient of determination (R2) close to the unity. Furthermore, the output of the model was in good agreement with the analytical solution with a maximum error 4.7%. The combination of reverse concept and ANN may provide a potentially novel approach in designing of sandwich structures. The main added value of this study is the elaboration of a reverse ANN model, which provides a low computational technique as well as savestime in the design or redesign of sandwich structures compared to analytical and finite element approaches.

• 전기학회논문지
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• 제63권5호
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• pp.676-682
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• 2014

In this paper, precipitation echo(PRE) and non-precipitaion echo(N-PRE)(including ground echo and clear echo) through weather radar data are identified with the aid of neuro-fuzzy algorithm. The accuracy of the radar information is lowered because meteorological radar data is mixed with the PRE and N-PRE. So this problem is resolved by using RBFNN and judgement module. Structure expression of weather radar data are analyzed in order to classify PRE and N-PRE. Input variables such as Standard deviation of reflectivity(SDZ), Vertical gradient of reflectivity(VGZ), Spin change(SPN), Frequency(FR), cumulation reflectivity during 1 hour(1hDZ), and cumulation reflectivity during 2 hour(2hDZ) are made by using weather radar data and then each characteristic of input variable is analyzed. Input data is built up from the selected input variables among these input variables, which have a critical effect on the classification between PRE and N-PRE. Echo judgment module is developed to do echo classification between PRE and N-PRE by using testing dataset. Polynomial-based radial basis function neural networks(RBFNNs) are used as neuro-fuzzy algorithm, and the proposed neuro-fuzzy echo pattern classifier is designed by combining RBFNN with echo judgement module. Finally, the results of the proposed classifier are compared with both CZ and DZ, as well as QC data, and analyzed from the view point of output performance.

• 한국산업정보학회논문지
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• 제17권3호
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• pp.43-49
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• 2012

현재 운용되고 있는 리가시 시스템에 대한 요구명세서는 대부분 자료흐름도를 사용하고 있어, 시스템의 유지 보수를 위해서는 자료흐름도로부터 획득한 정보에 의존하지 않을 수 없다. 본 논문에서는 자료흐름도로부터 데이터베이스 테이블 설계순서를 추출하는 추출기를 설계, 구현하였다. 추출기는 자료흐름도를 입력 받아 저장하고, 이를 방향그래프로 변환하여 데이터베이스 테이블 설계순서를 추출하여 제시한다. 구현된 추출기는 실제 운용 중인 소프트웨어 시스템에 적용함으로써 실제 적용가능성을 보였다.

• Asia pacific journal of information systems
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• 제6권1호
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• pp.165-194
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• 1996

Data distribution is one of the most important steps in distributed database design. This paper proposes a methodology for distributing database by using a relational schema as an input. A design support system called DBDD (Database Distribution Design) is implemented within the framework of this methodology. The methodology consists of three phases such as (i) schema analysis, (ii) fragmentation, and (iii) allocation. In the schema analysis phase, all the table names are acquired from a global relational schema. In the fragmentation phase, fragments are generated according to transaction retrieval patterns. Furthermore, DBDD enhances the design quality by allocating fragments in a progressive manner. A real-life case is illustrated to demonstrate the practical usefulness of the DBDD.

• Journal of Advanced Marine Engineering and Technology
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• 제19권4호
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• pp.72-78
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• 1995

The diffusion of fuzzy logic techniques into real applications requires specific software supports which save development time and reduce the programming effort. But we has been lack of a tool devoted to support the design of fuzzy controllers. In this paper, on the basis of the general fuzzy set and .alpha.-cut set decomposition of fuzzy sets, a set of fuzzy reasoning tool(FRT) devoted to support the design of fuzzy dontroller for servo systems is developed. The major features of this tool are: 1) It supports users to analyze fuzzy ingerence status based on input deta and expected results by three-D graphic display. 2) It supports users to prepare input data and expected result. 3) It supports users to tuned scaling factor of membership functions, rules and fuzzy inference. The paper shows how the suggested design tools are suitable to give a consistent answer to the tuning of fuzzy control system. This FRT is expected to exert good performance and devoted to support which the design of fuzzy controller is illustrated in the servo systems.

• 한국태양에너지학회 논문집
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• 제23권4호
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• pp.11-20
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• 2003

This study aims to develop the program for active solar heating system design & analysis. The program, named ASOLis, is consisted of three user's interface like as system input/output, library, and utilities and used TRNSYS as a calculation engine for the system analysis. ASOLis simplifies user's input data through the database and can design 37 different types of solar systems. Solar system is configurated by two separated parts "solar thermal collecting part" and "load supplying part". Due to the user-friendly layout, all design parameters can be changed quickly and easily for the influence on system efficiency. For the reliability, ASOLis compared with experimental result. As a result, ASOLis is expected to be used as a vital tool for the design and analysis of active solar heating system.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2009년도 세계 도시지반공학 심포지엄
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• pp.1250-1257
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• 2009

Due to the improvement of the seismic hazard analysis method and the design code, dynamic analysis method is widely used. To conduct dynamic analysis, various coefficients should be designated. The time history acceleration is one of the most essential factor. However, strong earthquake motion data from the outside of the country have been used to conduct dynamic analysis without considering of the ground motion parameters. In this study, the methodology to choose appropriate input motion is developed by using time domain design spectrum matching procedure. Two examples are applied to verify the methodology. The Result shows that the methodology satisfies seismic circumstances and the design code.