• 한국수자원학회논문집
• /
• 제41권7호
• /
• pp.737-746
• /
• 2008

강우-유출 및 저수지운영 모형의 최종 개발 목적은 가용한 관측자료를 이용하여 실무자가 하천의 유량예측 및 저수지운영 업무를 쉽고 정확하게 수행할 수 있도록 분석도구를 제공하는데 있다. 본 연구에서는 물관리 실무에서 홍수량 예측업무에 활용중인 단기 강우-유출 저류함수 모형을 확장하여 장기유출에 모의에 기여도가 높은 유효우량 및 침투량 산정기법을 개선하여 장기 유출분석이 가능하도록 저류함수기반의 장기 유출모형을 구축하였다. 개발된 모형의 적용가능성을 검토하기 위하여 낙동강 유역내 3개 댐유역(안동,합천,밀양)을 대상으로 연간 유출모의를 실시 하였으며, 현재 물관리 실무에서 장기유출모형으로 활용중인 SSARR모형과의 성능을 비교하였다. 수문곡선 비교 결과, SSARR 모형이 상대적으로 재현성 높은 결과를 보여주었지만, 본 연구에서 개발한 모형은 관측 가용한 자료만으로도 비교적 신뢰성 있는 장기유출모의가 가능하다는 점에서 향후 실무에서 유용하게 활용할 수 있을 것으로 사료된다.

• 한국경영과학회지
• /
• 제23권2호
• /
• pp.187-200
• /
• 1998

This paper presents an original approach for solving short-term power scheduling in extended power system with two fuels in a unit and a limited fuel using Lagrangian relaxations. The underlying model incorporates the full set of costs and constraints including setup, production, ramping, and operational status, and takes the form of a mixed integer nonlinear control problem. Moreover, the mathematical model developed includes two fuels in a unit and a limited fuel, regulation reserve requirements of prespecified group of units. Lagrangian relaxation is used to disaggregate the model by generator into separate subproblems which are then solved with a nested dynamic program including empirical knowledges. The strength of the methodology lies partially in its ability to construct good feasible solutions from information provided by the dual. Thus, the need for branch-and-bound is eliminated. In addition, the inclusion of two fuels in a unit and a limited fuel provides new insight into the limitations of current techniques. Computational experience with the proposed algorithm indicates that Problems containing up to 23 units including 8 unit used two fuels and 24 time periods can be readily solved in reasonable times. Duality gaps of less than 4％ were achieved.

• 아태비즈니스연구
• /
• 제2권1호
• /
• pp.1-22
• /
• 2011

Chamber of commerce and industry plays important role for development of business community and creating vibrant competition. Present paper compares chambers operations in Bangladesh, especially, Sylhet Chamber of Commerce and Industry(SCCI) by reviewing global models of chambers practices. The study identifies important gaps between international standards and Bangladesh practices. Mostly practiced chambers model in the world are: Continental Model, Anglo-Saxon Model and Mixed model or Asian model. Like other Asian countries, chambers in Bangladesh including SCCI, have been following Mixed Model. The empirical study found that SCCI is performing different developmental functions like accumulating members, collecting revenue, fulfilling corporate social responsibility and providing business development services to its members and business community. The notable constraining factors of SCCI operations are: short term orientation in assembling members, limited functional activities, lack of creative endeavors in diversifying services, linkage between SCCI and academic institutions, poor research involvement etc. The necessary suggestions for improvement of chambers performance include adoption of creative measures in various operations, providing training to the members, assisting entrepreneurs in obtaining industrial finance and extending support in the establishment of specialized industrial zone for attaining long term developmental objectives.

• 전기학회논문지
• /
• 제59권6호
• /
• pp.1041-1045
• /
• 2010

Short-term electric load forecasting of power systems is essential for the power system stability and the efficient power system operation. An accurate load forecasting scheme improves the power system security and saves some economic losses in power system operations. Due to scarcity of the historical same type of holiday load data, most big electric load forecasting errors occur on load forecasting for the holidays. The fuzzy linear regression model has showed good accuracy for the load forecasting of the holidays. However, it is not good enough to forecast the load of the election day. The concept of the load variation rate for the load forecasting of the election day is introduced. The proposed algorithm shows its good accuracy in that the average percentage error for the short-term 24 hourly loads forecasting of the election days is 2.27%. The accuracy of the proposed 24 hourly loads forecasting of the election days is compared with the fuzzy linear regression method. The proposed method gives much better forecasting accuracy with overall average error of 2.27%, which improved about average error of 2% as compared to the fuzzy linear regression method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권6호
• /
• pp.2612-2633
• /
• 2020

Due to the explosive growth of multimedia speech data, how to protect the privacy of speech data and how to efficiently retrieve speech data have become a hot spot for researchers in recent years. In this paper, we proposed an encrypted speech retrieval scheme based on long short-term memory (LSTM) neural network and deep hashing. This scheme not only achieves efficient retrieval of massive speech in cloud environment, but also effectively avoids the risk of sensitive information leakage. Firstly, a novel speech encryption algorithm based on 4D quadratic autonomous hyperchaotic system is proposed to realize the privacy and security of speech data in the cloud. Secondly, the integrated LSTM network model and deep hashing algorithm are used to extract high-level features of speech data. It is used to solve the high dimensional and temporality problems of speech data, and increase the retrieval efficiency and retrieval accuracy of the proposed scheme. Finally, the normalized Hamming distance algorithm is used to achieve matching. Compared with the existing algorithms, the proposed scheme has good discrimination and robustness and it has high recall, precision and retrieval efficiency under various content preserving operations. Meanwhile, the proposed speech encryption algorithm has high key space and can effectively resist exhaustive attacks.

• 한국의류산업학회지
• /
• 제10권6호
• /
• pp.873-881
• /
• 2008

The purpose of this study is to examine the effects of sales person's perception of ethical management on job performance in department stores. Sales person's perception of ethical management consists of such things as fairness, looking for short-term profits and observing the rules. Job performance consists of such things as sales person's organizational commitment, Sales person's service delivery level, rational operations, and participational attitude. For these purposes, the author developed several hypotheses. The data was collected from 435 sales person's in department stores. The results of this study are as follows: First, fairness, looking for short-term profits, and observing the rules had a significantly positive effect on sales person's organizational commitment. Second, fairness and observing the rules had significantly positive effect on sales person's service delivery level. Third, fairness had a significantly positive effect on rational operation. Fifth, looking for short-term profits and observing the rules had significantly positive effect on participational attitude. At the end of this paper, limitations, further research directions, and implications are suggested.

• International Journal of Computer Science & Network Security
• /
• 제21권2호
• /
• pp.77-87
• /
• 2021

In this study, a novel improved second order Radial Basis Function Neural Network based method with excellent scheduling capabilities is used for the dynamic prediction of short and long-term energy required applications. The effectiveness and the reliability of the algorithm are evaluated using training operations with New England-ISO database. The dynamic prediction algorithm is implemented in Matlab and the computation of mean absolute error and mean absolute percent error, and training time for the forecasted load, are determined. The results show the impact of temperature and other input parameters on the accuracy of solar Photovoltaic load forecasting. The mean absolute percent error is found to be between 1% to 3% and the training time is evaluated from 3s to 10s. The results are also compared with the previous studies, which show that this new method predicts short and long-term load better than sigmoidal neural network and bagged regression trees. The forecasted energy is found to be the nearest to the correct values as given by England ISO database, which shows that the method can be used reliably for short and long-term load forecasting of any electrical system.

• 한국경영과학회:학술대회논문집
• /
• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
• /
• pp.798-805
• /
• 2005

Estimating the effects of price increase on a company's sales is important task faced by managers. If consumer has prior information on price increase or expect it, there would be stockpiling and subsequent drops in sales. In addition, consumer can suppress demand in the short run. Above factors make the sales dynamic and unstable. We develop a time series model to evaluate the sales patterns with stockpiling and short term suppression of demand and also propose a forecasting procedure. For estimation, we use panel data and extend the model to Bayesian hierarchical structure. By borrowing strength across cross-sectional units, this estimation scheme gives more robust and reasonable result than one from the individual estimation. Furthermore, the proposed scheme yields improved predictive power in the forecasting of hold-out sample periods.

• 한국경영과학회지
• /
• 제31권2호
• /
• pp.157-167
• /
• 2006

Estimating the effects of price increase on a company's sales is important task faced by managers. If consumer has prior information on price increase or expects it, there would be stockpiling and subsequent drops in sales. In addition, consumer can suppress demand in the short run. These factors make the sales dynamic and unstable. In this paper we develop a time series model to evaluate the sales patterns with stockpiling and short-term suppression of demand and also propose a forecasting procedure. For estimation, we use panel data and extend the model to Bayesian hierarchical structure. By borrowing strength across cross-sectional units, this estimation scheme gives more robust and reasonable result than one from the individual estimation. Furthermore, the proposed scheme yields improved predictive power in the forecasting of hold-out sample periods.

• 품질경영학회지
• /
• 제25권1호
• /
• pp.1-16
• /
• 1997

In this paper, we illustrate how to design screening inspections for minimizing a total quality costs in a multi-stage manufacturing systems. The total quality cost model consists of inspection costs, internal failure costs, external failure costs, and Taguchi's loss function. Although, the use of automatic test equipment such as machnie vision and CMM has greatly increased inspection speed and accuracy, screeing(100% inspection) could be considered only as a short-term method to remove nonconforming items from a population, not for a long-term quality improvement. However, screeing should be used for certain situations such as before costly operations and after unsatisfied operations. This paper ends with an example that demonstrates the usefulness of the model.