• Journal of the Korean Institute of Navigation
• /
• v.23 no.1
• /
• pp.75-84
• /
• 1999

Although many studies on modelling of port competitive situation have been conducted, both theoretical frame and methodology are still very weak. In this study, therefore, a new algorithm called ESD (Extensional System Dynamics) for the evaluation of port competition was presented, and applied to simulate port systems in northeast asia. The detailed objectives of this paper are to develop Unit fort Model by using SD(System Dynamics) method; to develop Competitive Port Model by ESD method; to perform sensitivity analysis by altering parameters, and to propose port development strategies. For these the algorithm for the evaluation of part's competition was developed in two steps. Firstly, SD method was adopted to develop the Unit Port models, and secondly HFP(Hierarchical Fuzzy Process) method was introduced to expand previous SD method. The proposed models were then developed and applied to the five ports - Pusan, Kobe, Yokohama, Kaoshiung, Keelung - with real data on each ports, and several findings were derived. Firstly, the extraction of factors for Unit Port was accomplished by consultation of experts such as research worker, professor, research fellows related to harbor, and expert group, and finally, five factor groups - location, facility, service, cargo volumes, and port charge - were obtained. Secondly, system's structure consisting of feedback loop was found easily by location of representative and detailed factors on keyword network of STGB map. Using these keyword network, feedback loop was found. Thirdly, for the target year of 2003, the simulation for Pusan port revealed that liner's number would be increased from 829 ships to 1,450 ships and container cargo volumes increased from 4.56 million TEU to 7.74 million TEU. It also revealed that because of increased liners and container cargo volumes, length of berth should be expanded from 2,162m to 4,729m. This berth expansion was resulted in the decrease of congested ship's number from 97 to 11. It was also found that port's charge had a fluctuation. Results of simulation for Kobe, Yokohama, Kaoshiung, Keelung in northeast asia were also acquired. Finally, the inter port competition models developed by ESB method were used to simulate container cargo volumes for Pusan port. The results revealed that under competitive situation container cargo volume was smaller than non-competitive situation, which means Pusan port is lack of competitive power to other ports. Developed models in this study were then applied to estimate change of container cargo volumes in competitive relation by altering several parameters. And, the results were found to be very helpful for port mangers who are in charge of planning of port development.

• Journal of the Korea Institute of Building Construction
• /
• v.13 no.6
• /
• pp.530-540
• /
• 2013

The business environment that affects the management performance can be characterized by each Strategic Business Unit (SBU) since construction companies win overseas contracts due to the fairly good construction situations while experience a decline in the local housing market. Environmental changes can alter the strategic importance of the SBU when measuring the management performance. However, large construction companies apply BSC (Balanced Score Card) for collective calculation to determine the management performance, making it difficult to reflect the strategic importance of SBU. This method may create a distorted image of management performance that fails to take environmental changes into consideration, and as such it needs to be improved. Yet, there are no studies on the weight of each SBU considering environmental changes. Thus, the current study intends to analyze the weight of SBU for company-wide measurement of the performance of large construction companies. In addition, a model for analysis of SBU importance is proposed to respond to the constantly changing environmental situations and to modify the weight. For analysis of SBU weight, a questionnaire was conducted with 23 experts and hands-on workers, and the questionnaire result was quantitatively analyzed by applying the FD-AHP method. It is expected that the result will enable a model to be proposed to calculate the weight per division in a manner that reflects environmental changes and minimizes strategic distortion when measuring the management performance of large construction companies.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.9 no.1
• /
• pp.51-56
• /
• 2003

The prevention of marine accidents has been a major topic in marine society for long time and various safety policies and Countermeasures have been developed and applied to prevent those accidents. In spite of these efforts, however significant marine accidents have taken place intermittently. Ship is being operated under a highly dynamic environments and many factors are related with ship's collision and those factors are interacting. So, the analysis on ship's collision rouses are very important to prepare countermeasures which will ensure the safe navigation. This study analysed the ship's collision data over the past 10 years(1991-2000), which is compiled by Korea Marine Accidents Inquiry Agency. The analysis confirmed that ‘ship's collision’ is occurred most frequently and the cause is closely related with human factor. The main purpose if this study is to propose risk control countermeasures of ship's collision. For this, the structure of human factor is analysed by the questionnaire methodology. Marine experts were surveyed based on major elements that were extracted from the human factor affecting to ship's collision FSM has been widely adopted in modeling a dynamic system which is composed of human factors. Then, the structure analysis on the rouses of ship's collision using FSM are performed. This structure model could be used in understanding and verifying the procedure of real ship's collision. Furthermore it could be used as the model to prevent ship's collision and to reduce marine accidents.

• Journal of Korea Water Resources Association
• /
• v.51 no.11
• /
• pp.977-987
• /
• 2018

The purpose of the water distribution system is gradually changing to increase the flexibility for responding to various abnormal situations. In addition, it is essential to improve resilience through preparing emergency plans against water supply failure. The most efficient way is emergency interconnections which supply water from interconnected adjacent blocks. To operate successful interconnections, it is essential to evaluate the supply performance in spatial and temporal aspects. The spatial and temporal aspects are dominated by its interconnected pipes and interconnected reservoirs respectively. In this study, an emergency interconnection scenario where problem occurred in reservoir 1 at 0:00hr in A city, Korea. An Advanced-Pressure Driven Analysis model was used to simulate the volume and inflow volume of the interconnected reservoirs. Based on the hydraulic analysis results, a multi-dimensional evaluation of the supply performance was conducted by applying possible water supply range indicator (PWSRI) and possible water supply temporal indicator (PWSTI) which are based on fuzzy membership functions. As a result, it was possible to evaluate the supply performance on the sides of consumers in spatio-temporal aspects and to review whether established plans mitigate the damage as intended. It is expected to be used for decision making on structural and non-structural emergency plan to improve the performance of an emergency interconnection.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2011.05a
• /
• pp.18-18
• /
• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.7
• /
• pp.1694-1704
• /
• 2015

In this paper, a robust trajectory tracking control method of a wheeled mobile robot is newly proposed combining the PDC and the ISMC. The PDC is a relatively simple and easy control method for nonlinear system compared to the other non-linear control methods. And the ISMC can have robust and stable control characteristics against model uncertainties and disturbances from the initial time by placing the states on the sliding plane with desired nominal dynamics. Therefore, the proposed PDC+ISMC trajectory tracking control method shows robust trajectory tracking performance in spite of external disturbance. The tracking performance of the proposed method is verified through simulations. Even though the disturbance increases, the proposed method keeps the performance of the PDC method when there is no disturbance. However, the PDC trajectory tracking control method has increasing tracking error unlike the proposed method when the disturbance increases.

• Journal of Korea Water Resources Association
• /
• v.43 no.8
• /
• pp.721-731
• /
• 2010

The rainfall-runoff relationship is very difficult to predict because it is complicate factor affected by many temporal and spatial parameters of the basin. In recent, models which is based on artificial intelligent such as neural network, genetic algorithm fuzzy etc., are frequently used to predict discharge while stochastic or deterministic or empirical models are used in the past. However, the discharge data which are generally used for prediction as training and validation set are often estimated from rating curve which has potential error in its estimation that makes a problem in reliability. Therefore, in this study, water stage is predicted from antecedent rainfall and water stage data for short term using three models of neural network which trained by error back propagation algorithm and optimized by genetic algorithm and training error back propagation after it is optimized by genetic algorithm respectively. As the result, the model optimized by Genetic Algorithm gives the best forecasting ability which is not much decreased as the forecasting time increase. Moreover, the models using stage data only as the input data give better results than the models using precipitation data with stage data.

• Information Systems Review
• /
• v.21 no.1
• /
• pp.135-152
• /
• 2019

Recently there are many development and support policies for start-up companies because of successful venture companies related to ICT services. However, as these policies have focused on the support for the initial stage of start-up, many start-up companies have difficulties to continuously grow up. The main reason for these difficulties is that they recognize start-up tasks as independent activities. However, many experts or related articles say that start-up tasks are composed of related processes from the initial stage to the stable stage of start-up firms. In this study, we models the start-up processes based on the survey collected by the start-up companies, and analyze the start-up process of ICT service companies with process mining techniques. Through process mining analysis, we can draw a sequential flow of tasks for start-ups and the characteristics of them. The analysis of start-up businessman, idea derivation, creating business model, business diversification processes are resulted as important processes, but marketing activity and managing investment funds are not. This result means that marketing activity and managing investment funds are activities that need ongoing attention. Moreover, we can find temporal and complementary tasks which could not be captured by independent individual-level activity analysis. Our process analysis results are expected to be used in simulation-based web-intelligent system to support start-up business, and more cumulated start-up business cases will be helpful to give more detailed individual-level personalization service. And our proposed process model and analyzing results can be used to solve many difficulties for start-up companies.

• Journal of Intelligence and Information Systems
• /
• v.17 no.3
• /
• pp.187-201
• /
• 2011

KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.

• Journal of Internet Computing and Services
• /
• v.17 no.1
• /
• pp.23-33
• /
• 2016

The current smart lighting is shaped to offer the lighting environment suitable for current context, after identifying user's action and location through a sensor. The sensor-based context awareness technology just considers a single user, and the studies to interpret many users' various context occurrences and conflicts lack. In existing studies, a fuzzy theory and algorithm including ReBa have been used as the methodology to solve context conflict. The fuzzy theory and algorithm including ReBa just avoid an opportunity of context conflict that may occur by providing services by each area, after the spaces where users are located are classified into many areas. Therefore, they actually cannot be regarded as customized service type that can offer personal preference-based context conflict. This paper proposes a priority-based LED lighting control system interpreting multiple context conflicts, which decides services, based on the granted priority according to context type, when service conflict is faced with, due to simultaneous occurrence of various contexts to many users. This study classifies the residential environment into such five areas as living room, 'bed room, study room, kitchen and bath room, and the contexts that may occur within each area are defined as 20 contexts such as exercising, doing makeup, reading, dining and entering, targeting several users. The proposed system defines various contexts of users using an ontology-based model and gives service of user oriented lighting environment through rule based on standard and context reasoning engine. To solve the issue of various context conflicts among users in the same space and at the same time point, the context in which user concentration is required is set in the highest priority. Also, visual comfort is offered as the best alternative priority in the case of the same priority. In this manner, they are utilized as the criteria for service selection upon conflict occurrence.