• 한국사회정책
• /
• v.25 no.4
• /
• pp.301-321
• /
• 2018

The purpose of this paper is to analyze whether any combination of the quantitative and qualitative aspects of the public pension system is a causal factor for the elderly poverty reduction rate. For this, fuzzy-set qualitative comparison analysis was conducted with the poverty reduction rate as the outcome condition variable, the public pension expenditure ratio, the redistributive index, the first floor public pension weight, the second floor public pension weight and the second floor forced private pension weight did. As a result of the analysis, the combination of high public pension expenditure ratio, low two - tier public pension share and high two - tier compulsory private pension share has become a cause of high poverty reduction rate of the elderly. And more various forms of association were found as the cause of low poverty reduction rate of the elderly. This paper suggests policy proposals based on the above findings.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.5
• /
• pp.151-155
• /
• 2019

Recently heart attack is 80% of the sudden death of elderly. The causes of a heart attack are complex and sudden, and it is difficult to predict the onset even if prevention or medical examination is performed. Therefore, early diagnosis and proper treatment are the most important. In this paper, we show the accuracy of normal and abnormal classification with neural network using weighted fuzzy function for accurate and rapid diagnosis of myocardial infarction. The data used in the experiment was data from the UCI Machine Learning Repository, which consists of 14 features and 303 sample data. The algorithm for feature selection uses the average of weight method. Two features were selected and removed. Heart attack was classified into normal and abnormal(1-normal, 2-abnormal) using the average of weight method. The test result for the diagnosis of heart attack using a weighted fuzzy neural network showed 87.66% accuracy.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.3
• /
• pp.255-260
• /
• 2004

Existing flapping MAV which is driven by motors or the other materials, has various defects. For the settlement of the issue, flapping MAV wing actuator is developed by using ADE(Acrylic Dielectric Elastomer). In comparison with existing materials which drive flapping wing, ADE has advantages of light weight as well as sufficient force. In order that correct lift farce occurs at this actuator, it must require to control to approach given reference. So it is controlled to approach given displacement by using fuzzy algorithm and is verified through simulation.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2002.04a
• /
• pp.463-468
• /
• 2002

In this paper, we proposed a recurrent time delayed neural network controller which compensate a output of neural network controller. Even if learn by neural network controller, it can occur an bad results from disturbance or load variations. So in order to adjust above case, we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of learning a inverse model neural network of plant, so a expected dynamic characteristics of plant can be got. As the results of simulation through the second order plant, we confirmed that the proposed recurrent time delayed neural network controller get a good response compare with a time delayed neural network controller.

• Industrial Engineering and Management Systems
• /
• v.6 no.2
• /
• pp.106-118
• /
• 2007

This paper present a new optimization model to generate aggregate production planning by considering electric cost. The new Time Of Switching (TOS) electric type is introduced by switching over Time Of Day (TOD) and Time Of Use (TOU) electric types to minimize the electric cost. The fuzzy demand and Dynamic inventory tracking with multiple plant capacity are modeled to cover the uncertain demand of customer. The constraint for minimum hour limitation of plant running per one start up event is introduced to minimize plants idle time. Furthermore; the Optimal Weight Moving Average Factor for customer demand forecasting is introduced by monthly factors to reduce forecasting error. Application is illustrated for multiple cement mill plants. The mathematical model was formulated in spreadsheet format. Then the spreadsheet-solver technique was used as a tool to solve the model. A simulation running on part of the system in a test for six months shows the optimal solution could save 60% of the actual cost.

• Journal of the Korean Society of Industry Convergence
• /
• v.21 no.3
• /
• pp.125-131
• /
• 2018

In this paper, we propose a homogeneous multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments with moving obstacles using multi-ultrasonic sensor. Instead of using "sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data, "command fusion" method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as real experiments with mobile robot, AmigoBot. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.2 no.1
• /
• pp.150-158
• /
• 1999

A driving system of a dynamic FOG compass with a stabilized platform is described. A stepping motor adopted as a driving motor is required to maintain a stable operation with constant speed and low oscillation for the proper operation of the FOG compass itself. The previous stabilization scheme operated on frequency-modulated supply is modified to include fuzzy control algorithm. The proposed scheme has advantages, particularly in the size, weight and flexibility of the driving system.

• Proceedings of the KIEE Conference
• /
• 2006.07d
• /
• pp.1834-1835
• /
• 2006

A robust adaptive position control algorithm is proposed for servomotor drive system with uncertainties and load disturbance. The proposed controller is comprised of a nominal controller and a robust control. The nominal controller is designed in the condition without all the external load disturbance, nonlinear friction and unpredicted uncertainties. The robust controller containing lumped uncertainty approximator using fuzzy-neural network(FNN) is designed to dispel the effect of uncertainties and load disturbance. The interconnection weight of the FNN can be online tuned in the sense of the Lyapunov stability theorem thus asymptotic stability of the proposed control system can be guaranteed. Finally, simulation results verify that the proposed control algorithm can achieve favorable tracking performance for the induction servomotor drive system.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.35C no.7
• /
• pp.101-108
• /
• 1998

In this paper, after we got to realized FDNN (fuzzy decision neural network) applied the quantization triangularity fuzzy function to DBNN(decision based neural network) of a hierarchical structure for image process, we could esign hardware of the realized FDNN. Also it is normalized the standard image and the input image as the same size. We are applied DWW algorithm which selected the closest value with finding similarity of an interval image by this distance to FDNN. So we could calulated in terms of distance to weight of pixel which composed two image and eliminated the nise of image, minimized the lost of information, obtained the optimal information. It is designed hardware of high speed weighted FDNN using COMPASS tool. Aslo, the total circuit is realized as gates of 61,000 and could show to superiority of FDNN using the simulation.

• Proceedings of the KIEE Conference
• /
• 2006.04a
• /
• pp.198-200
• /
• 2006

In this paper, three types of power control strategies for controlling a Fuel Cell Hybrid Electric Vehicle(FCHEV) are studied in view of fuel economy. The FCHEV has become one of alternatives for future vehicles since it does emit water only without any exhaust gas while it has a high well-to-wheel efficiency together with an energy saving due to regenerative braking. However, it has also several disadvantages such as the complexity of vehicle system, the increased weight and the extra battery cost. Among various power control strategies, a static power control strategy, a power assist control strategy and a fuzzy logic-based power control strategy are simulated and compared to show the effectiveness of each method.