• Title/Summary/Keyword: Extreme Programming

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Enhancement of Signal-to-noise Ratio Based on Multiplication Function for Phi-OTDR

  • Li, Meng;Xiong, Xinglong;Zhao, Yifei;Ma, Yuzhao
    • Current Optics and Photonics
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    • v.2 no.5
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    • pp.413-421
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    • 2018
  • We propose a novel methodology based on the multiplication function to improve the signal-to-noise ratio (SNR) for vibration detection in a phi optical time-domain reflectometer system (phi-OTDR). The extreme-mean complementary empirical mode decomposition (ECEMD) is designed to break down the original signal into a set of inherent mode functions (IMFs). The multiplication function in terms of selected IMFs is used to determine a vibration's position. By this method, the SNR of a phi-OTDR system is enhanced by several orders of magnitude. Simulations and experiments applying the method to real data prove the validity of the proposed approach.

Design and Implementation of Distributed Pair Programming System based on IDE (IDE 기반의 분산 페어 프로그래밍 시스템의 설계 및 구현)

  • Park, Ji-Hoon;Lee, Kyung-Hwan
    • The KIPS Transactions:PartD
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    • v.11D no.6
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    • pp.1301-1310
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    • 2004
  • In distributed office, the pairs can program together using a distributed pair programming system. Many CSCW tools featuring remote screen sharing function have insufficient usability, accessibility to introduce many developers to distributed pair programming. In this paper, we suggest a distributed pair programming system based on IDE, which many developers will accept and use easily. We have do#eloped a user scenario and GUI of the system, making distributed pair programming easier and designed with high extensibility by adapting design patterns and implemented in Java language. Our findings will be of significant help to developers dealing with implementation of distributed pair programming function into some commercial IDE.

Compromise possibility portfolio selections

  • Tanaka, Hideo;Guo, Peijun
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.659-662
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    • 1998
  • In this paper, lower and upper possibility distributions are identified to reflect two extreme opinions in portfolio selection problems based on upper and lower possibility distributions are formalized as quadratic programming problems. Portfolios for compromising two extreme opinions from upper and lower possibility distributions and balancing the opinions of a group of experts can be obtained by quadratic optimization problems, respectively.

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다목적 선형계획 문제의 특성에 관한 소고

  • Park Sun-Dal;So Yeong-Seop
    • Journal of the military operations research society of Korea
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    • v.14 no.1
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    • pp.33-41
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    • 1988
  • In Multiple Objective Linear Programming (MOLP), it is well known that efficient solution and weight are correspondent to each other. The purpose of this paper is to study relationships between efficient face and the region of weight in MOLP. It is shown that the regions of weights corresponding to two efficient extreme points are also neighbor if two efficient extreme points are neighbor each other, and that the set of the efficient solutions corresponding to the common part of weight regions is efficient face. Using the above, we present a method to find the efficient solutions corresponding to a given weight and vice versa.

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다목적 선형계획 문제의 특성에 관한 소고

  • Park Sun-Dal;So Yeong-Seop
    • Journal of the military operations research society of Korea
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    • v.13 no.2
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    • pp.33-41
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    • 1987
  • In Multiple Objective Linear Programming (MOLP), it is well known that efficient solution and weight are correspondent to each other. The purpose of this paper is to study relationships between efficient face and the region of weight in MOLP. It is shown that the regions of weights corresponding to two efficient extreme points are also neighbor if two efficient extreme points are neighbor each other, and that the set of the efficient solutions corresponding to the common part of weight regions is efficient face. Using the above, we present a method to find the efficient solutions corresponding to a given weight and vice versa.

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Application of Extreme Learning Machine (ELM) and Genetic Programming (GP) to design steel-concrete composite floor systems at elevated temperatures

  • Shariati, Mahdi;Mafipour, Mohammad Saeed;Mehrabi, Peyman;Zandi, Yousef;Dehghani, Davoud;Bahadori, Alireza;Shariati, Ali;Trung, Nguyen Thoi;Salih, Musab N.A.;Poi-Ngian, Shek
    • Steel and Composite Structures
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    • v.33 no.3
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    • pp.319-332
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    • 2019
  • This study is aimed to predict the behaviour of channel shear connectors in composite floor systems at different temperatures. For this purpose, a soft computing approach is adopted. Two novel intelligence methods, including an Extreme Learning Machine (ELM) and a Genetic Programming (GP), are developed. In order to generate the required data for the intelligence methods, several push-out tests were conducted on various channel connectors at different temperatures. The dimension of the channel connectors, temperature, and slip are considered as the inputs of the models, and the strength of the connector is predicted as the output. Next, the performance of the ELM and GP is evaluated by developing an Artificial Neural Network (ANN). Finally, the performance of the ELM, GP, and ANN is compared with each other. Results show that ELM is capable of achieving superior performance indices in comparison with GP and ANN in the case of load prediction. Also, it is found that ELM is not only a very fast algorithm but also a more reliable model.

A Study for the Land-cover Classification of Remote Sensed Data Using Quadratic Programming (원격탐사 데이터의 이차계획법에 의한 토지피복분류에 관한 연구)

  • 전형섭;조기성
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.19 no.2
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    • pp.163-172
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    • 2001
  • This study present the quadratic programming as the classification method of remote sensed data applying to the extraction of landcover and examine it's applicable capability by comparing the classification accuracy of quadratic programming with that of neural network and maximum likelihood method which are used in the extraction of thematic layer. As the results, as drawing the more improved classification results by 6% than maximum likelihood method, we could discern that the method of quadratic programming is appliable to classifying the remote sensed data. Also, in the classification of quadratic programming method, we could definitely indicate the results which was ignored in the previous extreme(binary) classification method by affecting the class decision with the class composition proportion.

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On the Relationship between $\varepsilon$-sensitivity Analysis and Sensitivity Analysis using an Optimal Basis

  • Park, Chan-Kyoo;Kim, Woo-Je;Park, Soondal
    • Management Science and Financial Engineering
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    • v.10 no.2
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    • pp.103-118
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    • 2004
  • $\epsilon$-sensitivity analysis is a kind of methods for performing sensitivity analysis for linear programming. Its main advantage is that it can be directly applied for interior-point methods with a little computation. Although $\epsilon$-sensitivity analysis was proposed several years ago, there have been no studies on its relationship with other sensitivity analysis methods. In this paper, we discuss the relationship between $\epsilon$-sensitivity analysis and sensitivity analysis using an optimal basis. First. we present a property of $\epsilon$-sensitivity analysis, from which we derive a simplified formula for finding the characteristic region of $\epsilon$-sensitivity analysis. Next, using the simplified formula, we examine the relationship between $\epsilon$-sensitivity analysis and sensitivity analysis using optimal basis when an $\epsilon$-optimal solution is sufficiently close to an optimal extreme solution. We show that under primal nondegeneracy or dual non degeneracy of an optimal extreme solution, the characteristic region of $\epsilon$-sensitivity analysis converges to that of sensitivity analysis using an optimal basis. However, for the case of both primal and dual degeneracy, we present an example in which the characteristic region of $\epsilon$-sensitivity analysis is different from that of sensitivity analysis using an optimal basis.

OPTIMALITY CONDITIONS AND AN ALGORITHM FOR LINEAR-QUADRATIC BILEVEL PROGRAMMING

  • Malhotra, Neelam;Arora, S.R.
    • Management Science and Financial Engineering
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    • v.7 no.1
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    • pp.41-56
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    • 2001
  • This linear fractional - quadratic bilevel programming problem, in which the leader's objective function is a linear fractional function and the follower's objective function is a quadratic function, is studied in this paper. The leader's and the follower's variables are related by linear constraints. The derivations of the optimality conditions are based on Kuhn-Tucker conditions and the duality theory. It is also shown that the original linear fractional - quadratic bilevel programming problem can be solved by solving a standard linear fractional program and the optimal solution of the original problem can be achieved at one of the extreme point of a convex polyhedral formed by the new feasible region. The algorithm is illustrated with the help of an example.

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An interactive face search procedure for multiple objective linear programming

  • Lee, Dong-Yeup
    • Korean Management Science Review
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    • v.10 no.2
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    • pp.11-26
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    • 1993
  • This paper presents a new interactive procedure for multiple objective linear programming problem (MOLP). In practical multiple objective linear programming applications, there is usually no need for the decision maker to consider solutions which are not efficient. Therefore, the interactive procedure presented here searches only among efficient solutions and terminates with a solution that is guaranteed to be efficient. It also can converge to nonextreme efficient final solutions rather than being restricted to only extreme efficient points of the feasible set. The procedure does not require sophisticated judgements or inputs from the decision maker. One of the most attractive features of the procedure however, is that the method allows the DM to examine the efficient faces it finds. As iteration goes, the DM can explore a wide variety of efficient faces rather than efficient faces confined to only certain subregion of the feasible set of problem MOLP since the efficient faces that the procedure finds need not be adjacent. This helps the DM explore the nature of the efficient set of problem MOLP and also helps the DM have confidence with a final solution. For these reasons, I feel that the procedure offer significant promise in solving multiple objective linear programs rapidly and in a satisfying manner to the DM.

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