• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.10
• /
• pp.1423-1427
• /
• 2014

Quantity of the solar power generation is heavily influenced by weather. In other words, due to difference in insolation, different quantity may be generated. However, it does not mean all areas with identical insolation produces same quantity because of various environmental aspects. Additionally, geographic factors such as altitude, height of plant may have an impact on the quantity. Hence, through this research, we designed a system to predict efficiency of the solar power generation system by applying insolation, weather factor such as duration of sunshine, cloudiness parameter and location. By applying insolation, weather data that are collected from various places, we established a system that fits with our nation. Apart from, we produced a geographic model equation through utilizing generated data installed nationwide. To design a prediction model that integrates two factors, we apply fuzzy algorithm, and validate the performance of system by establishing simulation system.

• Journal of applied mathematics & informatics
• /
• v.26 no.5_6
• /
• pp.1169-1183
• /
• 2008

In this paper, a method to find the weighted possibilistic variance and moments about the mean value of fuzzy numbers via applying a difuzzification using minimizer of the weighted distance between two fuzzy numbers is introduced. In this way, we obtain the nearest weighted point with respect to a fuzzy number, this main result is a new and interesting alternative justification to define of weighted mean of a fuzzy number. Considering this point and the weighted distance quantity, we introduce the weighted possibilistic mean (WPM) value and the weighted possibilistic variance(WPV) of fuzzy numbers. This paper shows that WPM is the nearest weighted point to fuzzy number and the WPV of fuzzy number is preserved more properties of variance in probability theory so that it can simply introduce the possibilistic moments about the mean of fuzzy numbers without problem. The moments of fuzzy numbers play an important role to estimate of parameters, skewness, kurtosis in many of fuzzy times series models.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1694-1699
• /
• 2003

A windshield wiper system plays a key part in assuring the driver's safety during the rainfall. However, because the quantity of rain and snow vary irregularly according to time and the velocity of the automobile, a driver changes wiper speed and interval from time to time to secure enough visual field in the traditional windshield wiper system. Because a manual operation of windshield wiper distracts driver's sensitivity and causes inadvertent driving, this is becoming a direct cause of traffic accidents. Therefore, this paper presents the basic architecture of a vision-based smart windshield wiper system and a rain sensing algorithm that regulates speed and interval of the windshield wiper automatically according to the quantity of rain or snow. This paper also introduces a fuzzy wiper control algorithm based on human's expertise, and evaluates the performance of the suggested algorithm in an experimental simulator.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.8 no.2
• /
• pp.134-141
• /
• 1998

Sometimes we need to acquire symbolic quantity of information instead of physical quantity for the output of any system. For instance we can not control traffic signal accurately through only the number of vehicles. At that case we can produce better output using symbolic quantity of road length and width and vehicle type. But it is very difficult to aggregate symbolic information from the unrelated and mutually conflicted input after calculating linear and related expression. Moreover that will take much time to produce symbolic output by the physical quantity only. In this paper we implemented the ultimate traffic control information by using fuzzy sensor algorithm and compared our results with the conventional traffic controller after studying the necessity of symbolic information in the traffic control.

• Structural Engineering and Mechanics
• /
• v.25 no.2
• /
• pp.147-160
• /
• 2007

In this paper, a dynamic analysis based on the fuzzy set theory is presented as a possible complementary tool to the classical stochastic methods for dynamic analyses. Material parameters of a structure are influenced by uncertainties and therefore they are considered to be fuzzy quantities with given distributions, that means fuzzy numbers with given membership functions. The fuzzy dynamic analysis is conducted with help of fuzzy arithmetic defined on the so-called ${\alpha}$-cuts. The results of the analysis are also obtained in the form of fuzzy numbers, which compared to the stochastic methods is less computationaly expensive while at the same time they still provide information about the distribution of a quantity. This method is demonstrated on an analysis of a two-dimensional frame subjected to possible seismic load, where the uncertain eigenmodes and eigenfrequencies are used in the modal analysis.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2006.05a
• /
• pp.187-192
• /
• 2006

In the absence of a clear command and control structure, a key challenge in supply chain management is the coordination and alignment of the supply chain members who pursue divergent and often conflicting goals. The newsvendor model is typically used as a framework to quantify the cost of misalignment and to assess the impact of coordination initiatives. This paper considers a fuzzy approach for the newsvendor problem which includes a single manufacturer and a single retailer. We use several fuzzy parameters in the model such as the demand, the wholesale price, and the market sales price. We apply a coordination policy, referred to as buyback, to solve the fuzzy newsvendor problem. Based on the buyback policy, the optimal order quantity of the retailer can be computed, and the possible profits of the members in the supply chain can be calculated with minimum sharing of private information. Focusing on the fuzzy model with buyback policy for the newsvendor problem, we illustrate exemplary fuzzy models. We also illustrate an integration model, which extends a single-manufacturer-single-retailer model to the single-manufacturer-multiple-retailer setting. In the extended model, we consider three coordination policies including quantity discount, profit sharing, and buyback, as well as non-coordination case.

• Journal of Mechanical Science and Technology
• /
• v.17 no.4
• /
• pp.492-500
• /
• 2003

By means of the transformation from the problem of fuzzy reliability to the problem of general reliability, a model for analyzing fuzzy reliability is introduced in this paper Because of the complexity of the Problem of the fuzzy reliability, generally speaking, the analytical equations for calculating fuzzy reliability indexes of machine part cannot be obtained in most cases. Therefore, in this paper, an approach is given wherein progressions are employed to calculate them, or a simulation approach is used to estimate them by expressing general reliability indexes as progressions. By utilizing the approach put forwards in the paper, the calculating quantity for analyzing the fuzzy reliability will be reduced : even substantially reduced sometimes. Some examples are taken to explain the feasibility of the model and a simulation approach.

• The Journal of Society for e-Business Studies
• /
• v.6 no.3
• /
• pp.197-207
• /
• 2001

The industrial structure comes to be complicated and for the production of the enterprise the rational and scientific forecast is necessary. The demand forecast has been widely used to linear regression, and up to now the linear regression was sharp the relationskp between then dependent variable and the independent variables. But, The real society demands accurate demand forecast from uncertain environment and subjective concept. This paper proposes the demand quantity forecast method to using of the fuzzy linear regression in uncertain and vague environment. Also, the optimum decision making of the demand quantity forecast uses integral calculus of the Sugeno to reflecting with the expert's (inventory manager) opinion.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.6 no.4
• /
• pp.89-95
• /
• 1997

Welding technique is widely applied to general industry such as pressure vessel for chemical plant, pipe system, heavy industry, and automobile. There are some points which must be considered when robot system is used in welding automation process for productivity improvement. Welding quality is governed by heat input, and this quantity can be different according to shape, property, and thick of material . For desired heat input , weld input parameters such as welding voltage, current, and welding velocity must be determined with those consideration. Until now these parameters have been determined mainly by experience of operator. In this study, the size of welding zone was predicted by fuzzy rules were constructed from the relation between welding variables and weld pool size. Inverse model method which welding control input for welder is determined with optimum voltage and current by fuzzy controller is validatied by computer simulation.

• Proceedings of the KIEE Conference
• /
• 2003.07e
• /
• pp.38-41
• /
• 2003

An Autonomous Mobile Robot(AMR) performs duty by sensing a recognized situation and controlling suitably. The existing algorithm has some advantages that it is possible to express the obstacle exactly and the robot is sensitive to the change of environment. However, this algorithm needs to control repeatedly according to the modelling and working environment that requires a great quantity of calculations. In this paper, We supplement shortcoming and designed direction algorithm of AMR using fuzzy controller. Fuzzy controller does not derive special quality spinning expression for system, and uses rules by value expressed by language. It is used extensively to non-linear, plant which mathematical modelling is difficult etc... Fuzzy control algorithm of AMR that is used by this research applies obstacle position, distance of obstacle, Progress direction of robot, speed of robot, Perception area of sensor, etc... by fuzzy control and decide steering angle of robot.