• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.46 no.1
• /
• pp.15-22
• /
• 2023

An Ant Colony Optimization Algorithm(ACO) is one of the frequently used algorithms to solve the Traveling Salesman Problem(TSP). Since the ACO searches for the optimal value by updating the pheromone, it is difficult to consider the distance between the nodes and other variables other than the amount of the pheromone. In this study, fuzzy logic is added to ACO, which can help in making decision with multiple variables. The improved algorithm improves computation complexity and increases computation time when other variables besides distance and pheromone are added. Therefore, using the algorithm improved by the fuzzy logic, it is possible to solve TSP with many variables accurately and quickly. Existing ACO have been applied only to pheromone as a criterion for decision making, and other variables are excluded. However, when applying the fuzzy logic, it is possible to apply the algorithm to various situations because it is easy to judge which way is safe and fast by not only searching for the road but also adding other variables such as accident risk and road congestion. Adding a variable to an existing algorithm, it takes a long time to calculate each corresponding variable. However, when the improved algorithm is used, the result of calculating the fuzzy logic reduces the computation time to obtain the optimum value.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.4C
• /
• pp.255-264
• /
• 2006

The auxiliary reinforcement method is normally applied to prevent a possible collapse of the tunnel face where the ground condition is not favorable or geologic information is not sufficient. Recently, several engineering approaches have been made to choose the effective reinforcement methods using expert system such as neural network and fuzzy theory field, among others. Even if the expert system has offered many decision aid tools to properly select the reinforcement method, the quantitative assessment items are not easy to estimate and this is why the data mining technique, widely used in the field of social science, medical treatment, banking and agriculture, is introduced in this study. Using decision tree together with PDA, the decision aids for reinforcement method based on field construction data are created to derive the field rules and future study will be concentrated on the application of the proposed methods in a variety of underground development cases.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.34 no.5
• /
• pp.1395-1408
• /
• 2014

In this research, a River Recreation Index Model (RRIM) was developed to provide sufficient information on the water quality of rivers to the public in order to secure safety of publics. River Recreation Index (RRI) is an integrated water quality information for recreation activities in rivers and expressed as the point from 0 to 100. The proposed RRIM consisted of two sub models: Fecal Coliform Model (FCM) and Water Quality Index Model (WQIM). FCM predicted Fecal Coliform Grade (FCG) using a logistic regression and WQIM synthesized water quality parameters of, DO, pH, turbidity and chlorophyll a into Water Quality Index (WQI). FCG and WQI were integrated into RRI by the integrating algorithm. The proposed model was applied to upstream of Gangjeong Weir in Nakdong River, and compared with Real Time Water Quality Index (RTWQI) which is the existing water quality information system for recreation use. The results show that calculated RRI reflected change of integrated water quality parameters well. Especially chlorophyll a showed Pearson correlation coefficient -0.85 with RRI. Also, RRIM produced more conservative index than RTWQI because RRI was calculated considering uncertainty of water quality criteria. Further, RRI showed especially low values when fecal coliform was predicted as low grade.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.34 no.10
• /
• pp.1359-1366
• /
• 2010

Recently, many electronic control techniques for vehicles have been developed and applied. One of the technologies can be X-by-wire such as throttle-by-wire, brake-by-wire, steer-by-wire, and etc, in which most of mechanical parts are replaced into electrical wire and actuators. In this study, the effect of throttle-by-wire and brake-by-wire control systems on vehicle velocity control, especially in a school zone, are taken into consideration. The number of accidents reported in school zones is higher than that in other places. The reason for this is that many vehicle drivers do not obey speed limit regulations. Moreover, some of the students are careless while crossing the streets. Therefore, in this study, we attempt to develop a method using throttle-by-wire and brake-by-wire control systems for automatically reducing the vehicle speed such that it will be within the speed limit. First, an engine model and a transmission system model are developed for a specific vehicle model. Second, speed reduction is carried out such that the reduction follows a pre-designed cubic spline trajectory; the trajectory is determined such that rapid deceleration, which causes discomfort to the driver and passengers, can be prevented, for which a fuzzy-PID control algorithm is applied for the trajectory following control. Finally, simulation results are presented to verify the performance of the proposed speed reduction control system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.34 no.3
• /
• pp.273-282
• /
• 2016

There has been growing social interest recently in the movement rights of people with reduced mobility. However, it simply eliminates the temporary inconvenience of walking of people with reduced mobility because it focuses only on supply of institutional facilities. Therefore, we look forward to improving movement welfare by proposing an optimized path finding algorithm for people with reduced mobility that takes into consideration physical elements affecting their movement, such as slope, steps etc. We selected Walking barrier factor by analyzing previous studies and calculated the relative importance of Walking barrier factors using an Analytic Hierarchy Process(AHP). Next, through the fuzzy system, the Walking disturbance level of link, which integrates the weights of Walking barrier factors and the attributes of each link, is derived. Then, Walking path cost that takes into consideration the ‘length’ factors is calculated and an optimized path for people with reduced mobility is searched using Dijkstra’s Algorithm. Nineteen different paths were searched and we confirmed that the derived paths are meaningful in terms of improving the mobility of people with reduced mobility by conducting a field test. We look forward to improving movement welfare by providing a navigation service using the path finding algorithm proposed in this study.

• Journal of Intelligence and Information Systems
• /
• v.12 no.3
• /
• pp.15-32
• /
• 2006

The increasing complexity of the socio-economic environments makes it less and less possible for single decision-maker to consider all relevant aspects of problem. Therefore, many organizations employ groups in decision making. In this paper, we present a multiperson decision making method using fuzzy logic with linguistic quantifier when each of group members specifies imprecise judgments possibly both on performance evaluations of alternatives with respect to the multiple criteria and on the criteria. Inexact or vague preferences have appeared in the decision making literatures with a view to relaxing the burdens of preference specifications imposed to the decision-makers and thus taking into account the vagueness of human judgments. Allowing for the types of imprecise judgments in the model, however, makes more difficult a clear selection of alternative(s) that a group wants to make. So, further interactions with the decision-makers may proceed to the extent to compensate for the initial comforts of preference specifications. These interactions may not however guarantee the selection of the best alternative to implement. To circumvent this deadlock situation, we present a procedure for obtaining a satisfying solution by the use of linguistic quantifier guided aggregation which implies fuzzy majority. This is an approach to combine a prescriptive decision method via a mathematical programming and a well-established approximate solution method to aggregate multiple objects.

• Journal of Navigation and Port Research
• /
• v.36 no.10
• /
• pp.905-910
• /
• 2012

In early 1990s, the Sea & Air Transport Cargoes (SATC) was increased annually with more than 50% rate due to the rising trade between Korea and China. However, after that, the increasing rate of the SATC was slowdown from the late 1990s, furthermore, recently it became sluggish and declined. This phenomenon is totally different compared to the skyrocketing trade volumes between two countries. In this respect, to forecast the SATC, draw out the factors for activation, and calculate the weight of priority of these factors are urgently needed. To achieve the research objectives, the ARIMA and Fuzzy-AHP were used as research methodology. The estimated volume of SATC using the data from year 2007 to 2012 on the ARIMA model, will be reached approximately 33,000 tons in year 2015. In the mean time, For drawing out and weighing the activation factors for SATC, the Fuzzy-AHP was adopted. As a result, 'Sea & Air transportation-related information system policies' is the most important factor among the principle criteria, and 'the construction of consolidation logistics center' is the most important factor among the 12 sub-principle criteria.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.12
• /
• pp.17-26
• /
• 1998

Ultrasonic sensors are widely used in various applications due to advantages of low cost, simplicity in construction, mechanical robustness, and little environmental restriction in usage. But for the application of object recognition, ultrasonic sensors exhibit several shortcomings of poor directionality which results in low spatial resolution of objects, and specularity which gives frequent erroneous range readings. The time-of-flight(TOF) method generally used for distance measurement can not distinguish small object patterns of plane, corner or edge. To resolve the problem, an increased number of the sensors in the forms of a linear array or 2-dimensional array of the sensors has been used. Also better resolution has been obtained by shifting the array in several steps using mechanical actuators. Also simple patterns are classified based on analyzing signal reflections. In this paper we propose a method of a sensor array system with improved capability in pattern distinction using electronic circuits accompanying the sensor array, and intelligent algorithm based on neuro-fuzzy processing of data fusion. The circuit changes transmitter output voltages of array elements in several steps. A set of different return signals from neighborhood sensors is manipulated to provide enhanced pattern recognition in the aspects of inclination angle, size and shift as well as distance of objects. The results show improved resolution of the measurements for smaller targets.

• Information Systems Review
• /
• v.12 no.2
• /
• pp.189-203
• /
• 2010

Is presenting guidance of information performance measurement as government PRM version 2.0 these common reference models in public sector. Government PRM is consisted of assessment classification system and standard line of sight and performance management standard form. Through this, is sorting performance element and define cause-and effect. Government PRM is supplying measurement categories at assessment classification system, but relative importance for application standard by measurement categories is not presenting. In this study, importance for government PRM's measurement categories been applying by commonness Test of information performance measurement of public sector wishes to deduce estimation and priority. Research model used Fuzzy QFD, and designed so that can reflect well PRM's development purpose. I applied Fuzzy AHP and FPP method that graft together fuzzy theory to minimize uncertainty and ambiguity in that expert opinion. Is drawn to element that "Standard model offer for information department and management" is the most important in government PRM's development purpose. "Quality of service" is showing the highest priority in customer results in measurement category. Importance for government PRM's measurement categories can offer common valuation basis in government and public institution. Hereafter if examine closely quantitative cause-and effect for structure model of measurement classification system when study government PRM more objective and efficient reference model become.

• Journal of Korea Water Resources Association
• /
• v.38 no.7 s.156
• /
• pp.565-574
• /
• 2005

It is used water quality data that was measured at Pyeongchanggang real time monitoring stations in Namhan river. These characteristics were analyzed with the water qualify of rainy and nonrainy periods. TOC (Total Organic Carbon) data of rainy periods has correlation with discharge and shows high values of mean, maximum, and standard deviation. DO (Dissolved Oxygen) value of rainy periods is lower than those of nonrainy periods. Input data of the water quality forecasting models that they were constructed by neural network and neuro-fuzzy was chosen as the reasonable data, and water qualify forecasting models were applied. LMNN, MDNN, and ANFIS models have achieved the highest overall accuracy of TOC data. LMNN (Levenberg-Marquardt Neural Network) and MDNN (MoDular Neural Network) model which are applied for DO forecasting shows better results than ANFIS (Adaptive Neuro-Fuzzy Inference System). MDNN model shows the lowest estimation error when using daily time, which is qualitative data trained with quantitative data. The observation of discharge and water quality are effective at same point as well as same time for real time management. But there are some of real time water quality monitoring stations far from the T/M water stage. Pyeongchanggang station is one of them. So discharge on Pyeongchanggang station was calculated by developed runoff neural network model, and the water quality forecasting model is linked to the runoff forecasting model. That linked model shows the improvement of waterquality forecasting.