• The KIPS Transactions:PartD
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• v.9D no.4
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• pp.603-612
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• 2002

Area of software measurement in software engineering is active more than thirty years. There is a huge collection of researches but still no concrete software development effort and cost estimation model. If we want to measure the effort and cost of a software project, we need to estimate the size of the software. A number of software metrics are identified in the literature; the most frequently cited measures are LOC (line of code) and FPA (function point analysis). The FPA approach has features that overcome the major problems with using LOC as a measure of system size. This paper presents simple linear regression model that related software development effort to software size measured in FP. The model is derived from the plotting of the effort and FP relation. The experimental data are collected from 789 software development projects that were recently developed under the various development environments and development methods. Also, the model is compare with other regression analysis model. The presented model has the best estimation ability among the software effort estimation models.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1000-1002
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• 2002

In electric motor coaches, the rolling stocks move by the adhesive effort between rail and driving wheel. Generally, the adhesive effort is defined by the function of both the weight of electric motor coach and the adhesive effort between rails and driving wheel. The characteristics of adhesive effort is strongly affected by the conditions between rails and driving wheel. When the adhesive effort decreases suddenly, the electric motor coach has slip phenomena. This paper proposes a re-adhesion control algorithm which uses the maximum adhesive effort by instantaneous estimation of adhesion force using disturbance observer. Based on this estimated adhesive effort, the re-adhesion control is performed to obtain the maximum transfer of the tractive effort.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.536-539
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• 2003

In electric motor coaches, the rolling stocks move by the adhesive effort between rail and driving wheel. Generally, the adhesive effort is defined by the function of both the weight of electric motor coach and the adhesive effort between rails and driving wheel. The characteristics of adhesive effort is strongly affected by the conditions between rails and driving wheel. When the adhesive effort decreases suddenly, the electric motor coach has slip phenomena. This paper proposes a re-adhesion control algorithm which uses the maximum adhesive effort by instantaneous estimation of adhesion force using load torque disturbance observer. Based on this estimated adhesive effort, the re-adhesion control is performed to obtain the maximum transfer of the tractive effort.

• 한국IT서비스학회:학술대회논문집
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• 2003.11a
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• pp.616-623
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• 2003

Since the computing environment changes very rapidly, the estimation of software effort is very difficult because it is not easy to collect a sufficient number of relevant cases from the historical data. If we pinpoint the cases, the number of cases becomes too small. However if we adopt too many cases, the relevance declines. So in this paper we attempt to balance the number of cases and relevance. Since many researches on software effort estimation showed that the neural network models perform at least as well as the other approaches, so we selected the neural network model as the basic estimator. We propose a search method that finds the right level of relevant cases for the neural network model. For the selected case set, eliminating the qualitative input factors with the same values can reduce the scale of the neural network model. Since there exists a multitude of combinations of case sets, we need to search for the optimal reduced neural network model and corresponding case set. To find the quasi-optimal model from the hierarchy of reduced neural network models, we adopted the beam search technique and devised the Case-Set Selection Algorithm. This algorithm can be adopted in the case-adaptive software effort estimation systems.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.397-400
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• 2005

SM 프로젝트는 SI 프로젝트와 달리 고객의 요청 사항(CSR)이 있을 때 마다 개발 계획을 세우고 관리를 하여야 하며 동시에 고객의 개발 요청 내용 외에도 운영업무에 대한 계획도 같이 세워 져야 한다. 하지만 대부분의 SM 프로젝트에서는 한 두 사람의 경험이나 판단으로 계획이 작성, 할당되며 운영업무에 대한 계획의 정확도도 떨어져 업무 load balancing 이 잘 되지 않는다. 본 논문에서는 이러한 문제 해결을 위해 효과적인 SM 프로젝트에서의 EFFROT ESTIMATION 프로세스를 제안하여 업무 load balancing 을 이루는 방안을 제시하고자 한다.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1575-1585
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• 2010

It is very important to forecast a back resource of a software development effort at the early stage of development life cycle for successful project processing, and it is carried out through software size estimation. The recent trend of software size estimation method is focused on the user's value such as FPA. We measure the actual development effort through case study and calculate CFP directly according to the cosmic-ffp manual V.3.0. in this paper. We also propose the software development effort estimation model by using the produced data. COSMIC-FFP does not use weights of necessary function elements, and so it has disadvantage in estimating sizes. This paper proposes the estimation model to estimate the precision software size by using system complexity as weight.

• The KIPS Transactions:PartD
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• v.8D no.2
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• pp.154-165
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• 2001

A number of attempts to develop methods for measuring software effort have been focused on the area of software engineering and many models have also been suggested to estimate the effort of software projects. Almost all current models use algorithmic or statistical mechanisms, but the existing algorithmic effort estimation models have failed to produce accurate estimates. Furthermore, they are unable to reflect the rapidly changing technical environment of software development such as module reuse, 4GL, CASE tool, etc. In addition, these models do not consider the paradigm shift of software engineering and information systems(i.e., Object Oriented system, Client-Server architecture, Internet/Intranet based system etc.). Thus, a new approach to software effort estimation is needed. After reviewing and analyzing the problems of the current estimation models, we have developed a model and a system architecture that will improve estimation performance. In this paper, we have adopted a neural network model to overcome some drawbacks and to increase estimation performance. We will also address the efficient system architecture and estimation procedure by a similar case-based approach and finally suggest the heuristic search method to find the best estimate of target project through empirical experiments. According to our experiment with the optimally parsimonious neural network model the mean error rate was significantly reduced to 14.3%.

• Journal of Internet Computing and Services
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• v.8 no.4
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• pp.105-117
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• 2007

In order to succeed in a bid or development, the project manager should estimate its cost and schedule more accurately in the early stage of the project. Usually, the nominal schedule of most projects can be derived from rule of thumb, first-order estimation practice, or ball-park schedule estimation table. But the rule-of-thumb models for the nominal schedule estimation are so various, and the first-order estimation practice does not provide sufficient information. So they do not help much to decide on the proper development effort and schedule for a particular size of project. This paper presents a statistical regression model for deciding the development effort and schedule of a project using the ball-park schedule estimation table. First, we have redefined such words suggested in the ballpark schedule estimation table as shortest possible schedule, efficient schedule and nominal schedule, Next, we have investigated the relationship between the development effort and the schedule. Finally, we have suggested a model for estimating the development effort and the more accurate schedule of such particular sizes of software as are not presented in the ball-park schedule estimation table. The experimental results show that our proposed regression analysis model decreases the mean magnitude of relative error by 2% at maximum. Also this model can estimated the development effort and schedule for a particular size of software.

• Journal of the Korea Computer Industry Society
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• v.3 no.3
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• pp.295-306
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• 2002

Successful project planning relies on a good estimation of the effort required to complete a project, together with the schedule options that may be available. Despite the extensive research done developing new and better models, existing software effort estimation models are present only the total effort and instantaneous effort function for the software life-cycle. Also, Putnam presents constant effort rate in each phase. However, the size of total effort are variable according to the software projects under the influence of its size, complexity and operational environment. As a result, the allocated effort in each phase also differ from project to project. This paper suggests the criteria for effort allocation in planning, specifying, building, testing and implementing phase followed by the project total effort. These criteria are derived from 183 different projects. This result can be considered as a practical guideline in management of project schedule and effort allocation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.376-376
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• 2000

Several algorithmic models have been proposed to estimate software cost and other management parameters. In particular, early prediction of completion time is absolutely essential for proper advance planning and a version of the possible ruin of a project. However, estimation is difficult because of its similarity to export judgment approaches and for its potential as an expert assistant in support of human judgment. Especially, the nature of the Norden/Rayleigh curve used by Putnam, renders it unreliable during the initial phases of the project, in projects involving a fast manpower buildup, as is the case with most software projects. Estimating software development effort is more complexity, because of infrastructure software related to target-machines hardware and process characteristics should be considered in software development for DCS (Distributed Control System). In this paper, we propose software development effort estimation technique using adaptive neural fuzzy inference system. The methods is applied to case-based projects and discussed.