• Journal of Korea Water Resources Association
• /
• v.52 no.10
• /
• pp.729-742
• /
• 2019

Natural disasters such as floods has been increased in many parts of the world, also Korea is no exception. The biggest part of natural damage in South Korea was caused by the flooding during the rainy season in every summer. The existing flood vulnerability analysis cannot explain the reality because of the repeated changes in topography. Therefore, it is necessary to calculate a new flood vulnerability index in accordance with the changed terrain and socio-economic environment. The priority of the investment for the flood prevention and mitigation has to be determined using the new flood vulnerability index. Total 25 urban districts in Seoul were selected as the study area. Flood vulnerability factors were developed using Pressure-State-Response (PSR) structures. The Pressure Index (PI) includes nine factors such as population density and number of vehicles, and so on. Four factors such as damage of public facilities, etc. for the Status Index (SI) were selected. Finally, seven factors for Response Index (RI) were selected such as the number of evacuation facilities and financial independence, etc. The weights of factors were calculated using AHP method and Fuzzy AHP to implement the uncertainties in the decision making process. As a result, PI and RI were changed, but the ranks in PI and RI were not be changed significantly. However, SI were changed significanlty in terms of the weight method. Flood vulnerability index using Fuzzy AHP shows less vulnerability index in Southern part of Han river. This would be the reason that cost of flood mitigation, number of government workers and Financial self-reliance are high.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.975-976
• /
• 1993

This talk presents the overview of the author's research and development activities on fuzzy inference hardware. We involved it with two distinct approaches. The first approach is to use application specific integrated circuits (ASIC) technology. The fuzzy inference method is directly implemented in silicon. The second approach, which is in its preliminary stage, is to use more conventional microprocessor architecture. Here, we use a quantitative technique used by designer of reduced instruction set computer (RISC) to modify an architecture of a microprocessor. In the ASIC approach, we implemented the most widely used fuzzy inference mechanism directly on silicon. The mechanism is beaded on a max-min compositional rule of inference, and Mandami's method of fuzzy implication. The two VLSI fuzzy inference chips are designed, fabricated, and fully tested. Both used a full-custom CMOS technology. The second and more claborate chip was designed at the University of North Carolina(U C) in cooperation with MCNC. Both VLSI chips had muliple datapaths for rule digital fuzzy inference chips had multiple datapaths for rule evaluation, and they executed multiple fuzzy if-then rules in parallel. The AT & T chip is the first digital fuzzy inference chip in the world. It ran with a 20 MHz clock cycle and achieved an approximately 80.000 Fuzzy Logical inferences Per Second (FLIPS). It stored and executed 16 fuzzy if-then rules. Since it was designed as a proof of concept prototype chip, it had minimal amount of peripheral logic for system integration. UNC/MCNC chip consists of 688,131 transistors of which 476,160 are used for RAM memory. It ran with a 10 MHz clock cycle. The chip has a 3-staged pipeline and initiates a computation of new inference every 64 cycle. This chip achieved an approximately 160,000 FLIPS. The new architecture have the following important improvements from the AT & T chip: Programmable rule set memory (RAM). On-chip fuzzification operation by a table lookup method. On-chip defuzzification operation by a centroid method. Reconfigurable architecture for processing two rule formats. RAM/datapath redundancy for higher yield It can store and execute 51 if-then rule of the following format: IF A and B and C and D Then Do E, and Then Do F. With this format, the chip takes four inputs and produces two outputs. By software reconfiguration, it can store and execute 102 if-then rules of the following simpler format using the same datapath: IF A and B Then Do E. With this format the chip takes two inputs and produces one outputs. We have built two VME-bus board systems based on this chip for Oak Ridge National Laboratory (ORNL). The board is now installed in a robot at ORNL. Researchers uses this board for experiment in autonomous robot navigation. The Fuzzy Logic system board places the Fuzzy chip into a VMEbus environment. High level C language functions hide the operational details of the board from the applications programme . The programmer treats rule memories and fuzzification function memories as local structures passed as parameters to the C functions. ASIC fuzzy inference hardware is extremely fast, but they are limited in generality. Many aspects of the design are limited or fixed. We have proposed to designing a are limited or fixed. We have proposed to designing a fuzzy information processor as an application specific processor using a quantitative approach. The quantitative approach was developed by RISC designers. In effect, we are interested in evaluating the effectiveness of a specialized RISC processor for fuzzy information processing. As the first step, we measured the possible speed-up of a fuzzy inference program based on if-then rules by an introduction of specialized instructions, i.e., min and max instructions. The minimum and maximum operations are heavily used in fuzzy logic applications as fuzzy intersection and union. We performed measurements using a MIPS R3000 as a base micropro essor. The initial result is encouraging. We can achieve as high as a 2.5 increase in inference speed if the R3000 had min and max instructions. Also, they are useful for speeding up other fuzzy operations such as bounded product and bounded sum. The embedded processor's main task is to control some device or process. It usually runs a single or a embedded processer to create an embedded processor for fuzzy control is very effective. Table I shows the measured speed of the inference by a MIPS R3000 microprocessor, a fictitious MIPS R3000 microprocessor with min and max instructions, and a UNC/MCNC ASIC fuzzy inference chip. The software that used on microprocessors is a simulator of the ASIC chip. The first row is the computation time in seconds of 6000 inferences using 51 rules where each fuzzy set is represented by an array of 64 elements. The second row is the time required to perform a single inference. The last row is the fuzzy logical inferences per second (FLIPS) measured for ach device. There is a large gap in run time between the ASIC and software approaches even if we resort to a specialized fuzzy microprocessor. As for design time and cost, these two approaches represent two extremes. An ASIC approach is extremely expensive. It is, therefore, an important research topic to design a specialized computing architecture for fuzzy applications that falls between these two extremes both in run time and design time/cost. TABLEI INFERENCE TIME BY 51 RULES {{{{Time }}{{MIPS R3000 }}{{ASIC }}{{Regular }}{{With min/mix }}{{6000 inference 1 inference FLIPS }}{{125s 20.8ms 48 }}{{49s 8.2ms 122 }}{{0.0038s 6.4㎲ 156,250 }} }}

• 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 Environmental Science International
• /
• v.15 no.2
• /
• pp.141-155
• /
• 2006

This study is aimed at the development of a runoff forecasting model to solve the uncertainties occurring in the process of rainfall-runoff modeling and improve the modeling accuracy of the stream runoff forecasting, The study area is the downstream of Naeseung-chun. Therefore, time-dependent data was obtained from the Wolpo water level gauging station. 11 and 2 out of total 13 flood events were selected for the training and testing set of model. The model performance was improved as the measuring time interval$(T_m)$ was smaller than the sampling time interval$(T_s)$. The Neuro-Fuzzy(NF) and TANK models can give more accurate runoff forecasts up to 4 hours ahead than the Feed Forward Multilayer Neural Network(FFNN) model in standard above the Determination coefficient$(R^2)$ 0.7.

• Proceedings of the KIEE Conference
• /
• 1991.07a
• /
• pp.795-798
• /
• 1991

The hybrid positon/force control is required when two or more robots perform a coorperative task in a uncertain environment, or when single robot does a task with a constant force to the environment. In this paper, a new control algorithm which control simultaneously the position and the force are proposed, however, especially the conventional position controller employed in the present robot control is used. Moreover, in order to improve the output response characteristics of the system, the PI gains which were computed from the PI gain tunning techniques, are varied based on the results of the Fuzzy algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.10
• /
• pp.1865-1874
• /
• 2011

This paper proposes a novel maximum power point tracking(MPPT) using a new fuzzy control(NFC) algorithm for robust in insolation variation. Maximum power point(MPP) of solar cell has to achieve for improving output efficiency because it is changed with insolation and temperature. Conventional MPPT controller such as constant voltage(CV), perturbation and observation(PO) and incremental conductance(IC) are researched. But these controller have the problem that is failure to MPP with environment changing. The proposed NFC controller is based the fuzzy control algorithm and able to robust control with environment changing. Also the proposed controller of PV system is modeled by PSIM and the response characteristics according to the parameter variation is compared and analyzed. The validity of this controller is proved through response results.

• 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.

• Proceedings of the Korea Contents Association Conference
• /
• 2004.05a
• /
• pp.401-405
• /
• 2004

The paper describes a technique for building a reuse environment obtained by polling user feedback about selected reuse components in order to enhance the system effectiveness. In order to do, we use fuzzification function adapting fuzzy technique. This is made by user profile. Function modification attained by result of continuous choice of components. This method is aimed to enhance system rather than optimization about single query

• Industrial Engineering and Management Systems
• /
• v.11 no.3
• /
• pp.241-254
• /
• 2012

To gain competitive advantage in a fast changing environment, the higher education institution (HEI) must continuously adjust the strategies to that environment. One important strategy is how to determine appropriate practical actions based on what students really need and want. Despite the abundance of research on service quality management, there is no universal consensus on how best to determine appropriate practical actions in HEIs. The aim of this paper is to develop an integrated model to be used to accurately acquire the most critical service attributes and determine appropriate actions that promote student satisfaction. Drawing on relevant literature, an integrated model is proposed which is based on students' perspective by integrating the fuzzy SERVQUAL, refined Kano, and Blue Ocean model. Subsequently, an empirical case study in the higher education sector is described that illustrates the value of the model in determining the most critical attributes and how to improve them.

• Journal of Navigation and Port Research
• /
• v.45 no.5
• /
• pp.252-258
• /
• 2021

Given the cyclicality, seasonality, and capital-intensiveness, the development of the shipping industry has long been contingent on corporate financing activities. As such, there have been a growing number of cities in East Asia pursuing a global maritime financial center in order to support their domestic shipping industry. However, it is widely accepted that financial services relevant to shipping in East Asia are quite under-developed compared to those of other leading maritime financial centers in Europe and North America. In this regard, this paper aimed to construct an evaluation index of maritime financial centers in terms of financial ecological environment for the purpose of highlighting the current status of development and suggesting future directions. Furthermore, this paper examined the development of shipping finance in Qingdao as a numerical example using the fuzzy comprehensive evaluation and compared results with those of Shanghai.