• Journal of the military operations research society of Korea
• /
• v.25 no.1
• /
• pp.133-140
• /
• 1999

Preprocessing for the -01 integer programming can reduce the size of problem instance as well as tighten its linear programming relaxations. In this research, the preprocessing techniques are classified into two categories. First, for the reduction of problem size, there are variable fixing and constraint elimination techniques. Second, for the reduction of feasible region, there are coefficient reduction and Euchidean reduction techniques. These methods are implemented and the effects are shown by experimental results.

• Communications for Statistical Applications and Methods
• /
• v.28 no.1
• /
• pp.89-97
• /
• 2021

Due to boundedness and sum constraint, compositional data are often transformed by logratio transformation and their transformed data are put into traditional binary classification or discriminant analysis. However, it may be problematic to directly apply traditional multivariate approaches to the transformed data because class distributions are not Gaussian and Bayes decision boundary are not polynomial on the transformed space. In this study, we propose to use flexible classification approaches to transformed data for compositional data classification. Empirical studies using synthetic and real examples demonstrate that flexible approaches outperform traditional multivariate classification or discriminant analysis.

• Journal of KIISE:Software and Applications
• /
• v.37 no.7
• /
• pp.584-589
• /
• 2010

The dynamic time warping algorithm generally used in time series pattern recognition spends most of the time in generating the correlation table, and it establishes the global path constraint to reduce the corresponding time complexity. However, the constraint restrains just in terms of the time axis, not considering the contents of input patterns. In this paper, we therefore propose an efficient branch and bound dynamic time warping algorithm which sets the global constraints by adaptively reflecting the patterns. The experimental results show that the proposed method outperforms conventional methods in terms of the speed and accuracy.

• ETRI Journal
• /
• v.39 no.4
• /
• pp.592-604
• /
• 2017

Intrusion detection is very important for network situation awareness. While a few methods have been proposed to detect network intrusion, they cannot directly and effectively utilize semi-quantitative information consisting of expert knowledge and quantitative data. Hence, this paper proposes a new detection model based on a directed acyclic graph (DAG) and a belief rule base (BRB). In the proposed model, called DAG-BRB, the DAG is employed to construct a multi-layered BRB model that can avoid explosion of combinations of rule number because of a large number of types of intrusion. To obtain the optimal parameters of the DAG-BRB model, an improved constraint covariance matrix adaption evolution strategy (CMA-ES) is developed that can effectively solve the constraint problem in the BRB. A case study was used to test the efficiency of the proposed DAG-BRB. The results showed that compared with other detection models, the DAG-BRB model has a higher detection rate and can be used in real networks.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.17 no.5
• /
• pp.1183-1192
• /
• 1993

Since the punching time is strongly related to the productivity in sheet metal stamping, there have been a lot of efforts to obtain the optimal tool path. However, most of the conventional efforts have the basic limitations to provide the global optimal solution because of the inherent difficulties of the NP hard combinatorial optimization problem. The existing methods search the optimal tool path with limiting tool changes to the minimal number, which proves not to be a global optimal solution. In this work, the turret rotation time is also considered in addition to the bed translation time of the NCT machine, and the total punching time is minimized by the simulated annealing algorithm. Some manufacturing constraints in punching sequences such as punching priority constraint and punching accuracy constraint are incorporated automatically in optimization, while several user-interactions to edit the final tool path are usually required in commercial systems.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.33 no.12
• /
• pp.1464-1470
• /
• 2009

RBDO approach based on a sampling method with the Kriging metamodel and Constraint Boundary Sampling (CBS), which is sequential sampling method to generate metamodels is proposed. The major advantage of the proposed RBDO approach is that it does not require Most Probable failure Point (MPP) which is essential for First-Order Reliability Method (FORM)-based RBDO approach. The Monte Carlo Sampling (MCS), most well-known method of the sampling methods for the reliability analysis is used to assess the reliability of constraints. In addition, a Cumulative Distribution Function (CDF) of the constraints is approximated using Moving Least Square (MLS) method from empirical distribution function. It is possible to acquire a probability of failure and its analytic sensitivities by using an approximate function of the CDF for the constraints. Moreover, a concept of inactive design is adapted to improve a numerical efficiency of the proposed approach. Computational accuracy and efficiency of the proposed RBDO approach are demonstrated by numerical and engineering problems.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.21 no.5
• /
• pp.726-732
• /
• 2012

Pipe and Pressure Vessels that is used in power plant and chemical industry have many Internal Defects that is corrosion caused by the flow of fluid. These Internal Defects that have possibility of explosion are very dangerous because it can not see from the outside. This days many companys using NDT method to find an Internal Defect. Most of the NDT methods have limitations that are constraint of shape and materials. But Sheargoraphy have many advantages compared conventional NDT method. It has very fast measuring speed, non-destructive and non contacting measurement. As well as it hasn't constraint of shape and materials. As a paper on the analysis of measurement of error, the important factors were the Shearing Amount and pressure, and discovered measurement of the Internal Defect of the object by using shearography. The optimal Shearing Amount and pressure was discovered and utilized.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.7
• /
• pp.3594-3607
• /
• 2017

The traditional feature extraction methods such as principal component analysis (PCA) cannot obtain the local structure of the samples, and locally linear embedding (LLE) cannot obtain the global structure of the samples. However, a common drawback of existing PCA and LLE algorithm is that they cannot deal well with the sparse problem of the samples. Therefore, by integrating the globality of PCA and the locality of LLE with a sparse constraint, we developed an improved and unsupervised difference algorithm called Sparse Difference Embedding (SDE), for dimensionality reduction of high-dimensional data in small sample size problems. Significantly differing from the existing PCA and LLE algorithms, SDE seeks to find a set of perfect projections that can not only impact the locality of intraclass and maximize the globality of interclass, but can also simultaneously use the Lasso regression to obtain a sparse transformation matrix. This characteristic makes SDE more intuitive and more powerful than PCA and LLE. At last, the proposed algorithm was estimated through experiments using the Yale and AR face image databases and the USPS handwriting digital databases. The experimental results show that SDE outperforms PCA LLE and UDP attributed to its sparse discriminating characteristics, which also indicates that the SDE is an effective method for face recognition.

• Journal of the Korean Society for Precision Engineering
• /
• v.23 no.4 s.181
• /
• pp.116-123
• /
• 2006

During the last two decades, many researchers investigated influences of stress triaxiality on ductile fracture for various specimens and structures. With respect to a transferability issue, the local approach reflecting micro-mechanical specifics is one of effective methods to predict constraint effects. In this paper, the applicability of the local approach was examined through a series of finite element analyses incorporating modified GTN (Gurson-Tvergaard-Needleman) and Rousselier models as well as fracture toughness tests. To achieve this goal, fracture resistance (J-R) curves of several types of compact tension (CT) specimens with various crack length, with various thickness and with/without 20% side- grooves were estimated. Then. the constraint effects were examined by comparing the numerically estimated J-R curves with experimentally determined ones. The assessment results showed that the damage models might be used as useful tool for fracture toughness estimation and both the crack length and thickness effects should be considered for realistic structural integrity evaluation.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.16 no.3
• /
• pp.166-171
• /
• 2008

In this paper, the optimization design module for the brake system of a vehicle is developed. As using this module, design variables, that minimize an object function and satisfy nonlinear constraint conditions, can be found easily. Before an optimization is operated, Plackett-Burman design, one of the factorial design methods, is used to choose the design variables which affect a response function significantly. Using the response surface analysis, second order recursive model function, which informs a relation between design variables and response function, is estimated. In order to verify the reliability of the model function, analysis of variances(ANOVA) table is used. The value of design variables which minimize the model function and satisfy the constraint conditions is predicted through Sequential Quadratic-Programming (SQP) method. As applying the above procedure to a real vehicle simulation model and comparing the values of object functions of a current and optimized system, the optimization results are verified.