• Journal of the Korean Mathematical Society
• /
• v.56 no.2
• /
• pp.311-327
• /
• 2019

The aim of this paper is to extend the applicability of Gauss-Newton method for solving underdetermined nonlinear least squares problems in cases not covered before. The novelty of the paper is the introduction of a restricted convergence domain. We find a more precise location where the Gauss-Newton iterates lie than in earlier studies. Consequently the Lipschitz constants are at least as small as the ones used before. This way and under the same computational cost, we extend the local as well the semilocal convergence of Gauss-Newton method. The new developmentes are obtained under the same computational cost as in earlier studies, since the new Lipschitz constants are special cases of the constants used before. Numerical examples further justify the theoretical results.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.7
• /
• pp.2154-2168
• /
• 2022

Our work addresses the issues associated with usage of the semantic features by Bag of Words model, which requires construction of the dictionary. Extracting the relevant features and clustering them into code book or dictionary is computationally intensive and requires large storage area. Hence we propose to use a simple distribution of multiple shape based features, which is a mixture of gradients, radius and slope angles requiring very less computational cost and storage requirements but can serve as an equivalent image representative. The experimental work conducted on PASCAL VOC 2007 dataset exhibits marginally closer performance in terms of accuracy with the Bag of Word model using Self Organizing Map for clustering and very significant computational gain.

• Journal of information and communication convergence engineering
• /
• v.21 no.1
• /
• pp.82-89
• /
• 2023

Various machine-learning models may yield high predictive power for massive time series for time series prediction. However, these models are prone to instability in terms of computational cost because of the high dimensionality of the feature space and nonoptimized hyperparameter settings. Considering the potential risk that model training with a high-dimensional feature set can be time-consuming, we evaluate a feature-importance-based feature selection method to derive a tradeoff between predictive power and computational cost for time series prediction. We used two machine learning techniques for performance evaluation to generate prediction models from a retail sales dataset. First, we ranked the features using impurity- and Local Interpretable Model-agnostic Explanations (LIME) -based feature importance measures in the prediction models. Then, the recursive feature elimination method was applied to eliminate unimportant features sequentially. Consequently, we obtained a subset of features that could lead to reduced model training time while preserving acceptable model performance.

• Korean Journal of Computational Design and Engineering
• /
• v.20 no.2
• /
• pp.124-132
• /
• 2015

When Building Information Modeling (BIM) was introduced at the early stage, it was only utilized as a three-dimensional visualization tool. Nowadays, however, BIM is being studied for increasing design productivity and managing enormous information on building life cycle. One of the representative research is developing 'common prototype BIM libraries'. BIM data made of common prototype libraries should be utilized in various ways, quantity takeoff, code checking, energy analysis and so on. However, common prototype BIM libraries are not enough to estimate accurate cost. For example, composite wall libraries should be divided into several single objects, wall structure and finishes, for the quantity takeoff and construction cost calculation. In this paper, we are suggesting an automated division algorithm of composite wall and developing a system prototype for it. This study is expected to reduce extra modeling work and contribute to fast and accurate cost calculation in the construction.

• Korean Journal of Computational Design and Engineering
• /
• v.16 no.4
• /
• pp.260-267
• /
• 2011

Nowadays, automobile manufacturers are faced with increasing global competition which is required low cost as well as high quality. To reduce shipping and handling cost and delivery time, lots of automobile manufactures tried to build their new factory in the neighborhood of market. Simultaneously, many factories are under construction in developing countries to make efficient use of low-wage workers. However, because systems are installed in developing countries as the same type of domestic facilities, systems have lots of problems such as high installation cost and inefficient use of manpower. To find core problems and generate optimal solution of these problems, thinking process of TOC(Theory Of Constrains) is used. In case of transmission gear machining system, semi-auto system is proposed as the best solution to increase manpower efficiency and system utilization. Semi-auto system consists of automatic machining process and manual transporting process. The system layout is generated based on semi-auto process concept. And, 3D simulation method using QUEST is used to verify production volume of generated system.

• Korean Journal of Computational Design and Engineering
• /
• v.16 no.1
• /
• pp.61-72
• /
• 2011

As the customer's needs for diverse colors, the process of bus painting shop is becoming more and more complex. In particular, frequent changes of paint colors in each spray process require the cleaning of the painting nozzles and setting them up for the new paints, which results in increased time and cost and reduced production. This also increases environmental influences. This paper proposes, as a solution to this issue, the use of color selection field (CSF). CSF is physically a system of conveyors that are used to rearrange objects in a flow line. CSF is proposed, in this paper, to be introduced right before the spray process so that buses are better grouped according to their desired colors. Various parameters of the CSF, such as the number of conveyors and algorithms to determine the rearranged sequence of buses, have been determined by running simulations using the digital manufacturing technology, and investigating the simulation results. As an outcome of the proposed solution, the CSF system is expected to reduce approximately 30% of the nozzle cleaning cost for a Korean motor company case, which will not only benefit the company economically, but will also benefit the environment.

• Journal of Korean Institute of Industrial Engineers
• /
• v.30 no.2
• /
• pp.93-106
• /
• 2004

This paper studied a maximal covering location problem with cost restrictions, to maximize level of service within predetermined cost. It is assumed that all demand have to be met. If the demand node is located within a given range, then its demand is assumed to be covered, but if it is not, then its demand is assumed to be uncovered. An uncovered demand is received a service but at an unsatisfactory level. The objective function is to maximize the sum of covered demand, Two heuristics based on the Lagrangean relaxation of allocation and decoupling are presented and tested. Upper bounds are found through a subgradient optimization and lower bounds are by a cutting algorithm suggested in this paper. The cutting algorithm enables the Lagrangean relaxation to be proceeded continually by allowing infeasible solution temporarily when the feasible solution is not easy to find through iterations. The performances are evaluated through computational experiments. It is shown that both heuristics are able to find the optimal solution in a relatively short computational time for the most instances, and that decoupling relaxation outperformed allocation relaxation.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.21 no.48
• /
• pp.37-52
• /
• 1998

In many distribution systems important cost reductions and/or service improvements may be achieved by adopting an efficient inventory policy and proper selection of facilities. These efficiency improvements and service enhancements clearly require an integrated approach towards various logistical planning functions. The areas of inventory control and transportation planning need to be closely coordinated. The purpose of this paper is to construct an integrated model that can minimize the total cost of the transportation and inventory systems between multiple origin and destination points, where in origin point i has the supply of commodities and in destination point j requires the commodities. In this case, demands of the destination points are assumed random variables which have a known probability distribution. Using the lot-size reorder-point policy and the safety stock level that minimize total cost we find optimal distribution centers which transport the commodities to the destination points and suggest an optimal inventory policy to the selected distribution center. We also show if a demand greater than one unit will occur at a particular time, we describe the approximate optional replenishment policy from computational results of this lot-size reorder-point policy. This model is formulated as a 0-1 nonlinear integer programming problem. To solve the problem, this paper proposes heuristic computational procedures and a computer program with UNIX C language. In the usefulness review, we show the meaning and validity of the proposed model and exhibit the results of a comparison between our approach and the traditional approach, respectively.

• Journal of Power Electronics
• /
• v.17 no.1
• /
• pp.76-87
• /
• 2017

Finite-set predictive current control (FS-PCC) is advantageous for power converters due to its high dynamic performance and has received increasing interest in multilevel inverters. Among multilevel inverter topologies, the cascaded H-bridge (CHB) inverter is popular and mature in the industry. However, a main drawback of FS-PCC is its large computational burden, especially for the application of CHB inverters. In this paper, an FS-PCC method based on a deadbeat solution for three-phase zero-common-mode-voltage CHB inverters is proposed. In the proposed method, an inverse model of the load is utilized to calculate the reference voltage based on the reference current. In addition, a cost function is directly expressed in the terms of the voltage errors. An optimal control actuation is selected by minimizing the cost function. In the proposed method, only three instead of all of the control actuations are used for the calculations in one sampling period. This leads to a significant reduction in computations. The proposed method is tested on a three-phase 5-level CHB inverter. Simulation and experimental results show a very similar and comparable control performance from the proposed method compared with the traditional FS-PCC method which evaluates the cost function for all of the control actuations.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.17 no.2
• /
• pp.141-150
• /
• 2004

Recently, it is really concerned about corrosion and aging of reinforced concrete bridges. Corrosional steel reinforcing in concrete affects not only safety of bridges structure but also bending strength of reinforced concrete's member. Rate of corrosion, characteristic of bending strength, and economical evaluation aren't clear in reinforced concrete, considering performance evaluation. The purpose of study is as follows. It studies about ability of resistance's strength and cost of life cycle according to reduction of steel reinforcing's corrosion. Moreover, it shows calculating formula of bending strength with corrosion of current rate and exactly evaluates about the rest life at corrosional reinforced concrete bridges.