• Title/Summary/Keyword: multiple fuzzy systems

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Knowledge-Based Unmanned Automation and Control Systems for the Wastewater Treatment Processes (하.폐수 처리장의 원격 모니터링 및 지식 기반 무인 자동화 시스템)

  • Bae, Hyeon;Jung, Jae-Ryong;Seo, Hyun-Yong;Kim, Sung-Shin;Kim, Chang-Won
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.12a
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    • pp.56-59
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    • 2001
  • In this paper, unmaned fully automation systems are applied for the CSTR(Continuously Stirred Tank Reactor) and, SBR (Sequencing Batch Reactor) wastewater treatment pilot plant. This plant is constructed in the country side which is little far from a main city. So networks and wireless modules are employed for the data transmission. The SBR plant has a local control and monitoring system which is contained communication parts which consist of one ADSL (Asymmetric Digital Subscriber Line) network and one CDMA (Code Division Multiple Access) module. Remote control and monitoring systems are constructed at a laboratory in a metropolis.

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A Muti-Resolution Approach to Restaurant Named Entity Recognition in Korean Web

  • Kang, Bo-Yeong;Kim, Dae-Won
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.4
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    • pp.277-284
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    • 2012
  • Named entity recognition (NER) technique can play a crucial role in extracting information from the web. While NER systems with relatively high performances have been developed based on careful manipulation of terms with a statistical model, term mismatches often degrade the performance of such systems because the strings of all the candidate entities are not known a priori. Despite the importance of lexical-level term mismatches for NER systems, however, most NER approaches developed to date utilize only the term string itself and simple term-level features, and do not exploit the semantic features of terms which can handle the variations of terms effectively. As a solution to this problem, here we propose to match the semantic concepts of term units in restaurant named entities (NEs), where these units are automatically generated from multiple resolutions of a semantic tree. As a test experiment, we applied our restaurant NER scheme to 49,153 nouns in Korean restaurant web pages. Our scheme achieved an average accuracy of 87.89% when applied to test data, which was considerably better than the 78.70% accuracy obtained using the baseline system.

Knowledge-Based Unmanned Automation and Control Systems for the Wastewater Treatment Processes (하.폐수 처리장의 원격 모니터링 및 지식 기반 무인 자동화 시스템)

  • Bae, Hyeon;Jung, Jae-Ryong;Seo, Hyun-Yong;Kim, Sung-Shin;Kim, Chang-Won
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.9
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    • pp.844-848
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    • 2001
  • This paper introduces unmaned fully automation systems, which are applied for the CSTR(Continuously Stirred Tank Reactor) and SBR (Sequencing Batch Reactor) wastewater treatment system. The pilot plant is constructed in the country side which is little far from a main city. So networks and wireless modules are employed for the data transmission. The SBR plant has a local control and the remote monitoring system which is contained communication parts which consist of ADSL (Asymmetric Digital Subscriber Line) network and CDMA (Code Division Multiple Access) Wireless module. Remote control and monitoring systems are constructed at laboratory in a metropolis.

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Temporal Search Algorithm for Multiple-Pedestrian Tracking

  • Yu, Hye-Yeon;Kim, Young-Nam;Kim, Moon-Hyun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.5
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    • pp.2310-2325
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    • 2016
  • In this paper, we provide a trajectory-generation algorithm that can identify pedestrians in real time. Typically, the contours for the extraction of pedestrians from the foreground of images are not clear due to factors including brightness and shade; furthermore, pedestrians move in different directions and interact with each other. These issues mean that the identification of pedestrians and the generation of trajectories are somewhat difficult. We propose a new method for trajectory generation regarding multiple pedestrians. The first stage of the method distinguishes between those pedestrian-blob situations that need to be merged and those that require splitting, followed by the use of trained decision trees to separate the pedestrians. The second stage generates the trajectories of each pedestrian by using the point-correspondence method; however, we introduce a new point-correspondence algorithm for which the A* search method has been modified. By using fuzzy membership functions, a heuristic evaluation of the correspondence between the blobs was also conducted. The proposed method was implemented and tested with the PETS 2009 dataset to show an effective multiple-pedestrian-tracking capability in a pedestrian-interaction environment.

Developing a comprehensive model of the optimal exploitation of dam reservoir by combining a fuzzy-logic based decision-making approach and the young's bilateral bargaining model

  • M.J. Shirangi;H. Babazadeh;E. Shirangi;A. Saremi
    • Membrane and Water Treatment
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    • v.14 no.2
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    • pp.65-76
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    • 2023
  • Given the limited water resources and the presence of multiple decision makers with different and usually conflicting objectives in the exploitation of water resources systems, especially dam's reservoirs; therefore, the decision to determine the optimal allocation of reservoir water among decision-makers and stakeholders is a difficult task. In this study, by combining a fuzzy VIKOR technique or fuzzy multi-criteria decision making (FMCDM) and the Young's bilateral bargaining model, a new method was developed to determine the optimal quantitative and qualitative water allocation of dam's reservoir water with the aim of increasing the utility of decision makers and stakeholders and reducing the conflicts among them. In this study, by identifying the stakeholders involved in the exploitation of the dam reservoir and determining their utility, the optimal points on trade-off curve with quantitative and qualitative objectives presented by Mojarabi et al. (2019) were ranked based on the quantitative and qualitative criteria, and economic, social and environmental factors using the fuzzy VIKOR technique. In the proposed method, the weights of the criteria were determined by each decision maker using the entropy method. The results of a fuzzy decision-making method demonstrated that the Young's bilateral bargaining model was developed to determine the point agreed between the decisions makers on the trade-off curve. In the proposed method, (a) the opinions of decision makers and stakeholders were considered according to different criteria in the exploitation of the dam reservoir, (b) because the decision makers considered the different factors in addition to quantitative and qualitative criteria, they were willing to participate in bargaining and reconsider their ideals, (c) due to the use of a fuzzy-logic based decision-making approach and considering different criteria, the utility of all decision makers was close to each other and the scope of bargaining became smaller, leading to an increase in the possibility of reaching an agreement in a shorter time period using game theory and (d) all qualitative judgments without considering explicitness of the decision makers were applied to the model using the fuzzy logic. The results of using the proposed method for the optimal exploitation of Iran's 15-Khordad dam reservoir over a 30-year period (1968-1997) showed the possibility of the agreement on the water allocation of the monthly total dissolved solids (TDS)=1,490 mg/L considering the different factors based on the opinions of decision makers and reducing conflicts among them.

Strategy of Object Search for Distributed Autonomous Robotic Systems

  • Kim Ho-Duck;Yoon Han-Ul;Sim Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.3
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    • pp.264-269
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    • 2006
  • This paper presents the strategy for searching a hidden object in an unknown area for using by multiple distributed autonomous robotic systems (DARS). To search the target in Markovian space, DARS should recognize th ε ir surrounding at where they are located and generate some rules to act upon by themselves. First of all, DARS obtain 6-distances from itself to environment by infrared sensor which are hexagonally allocated around itself. Second, it calculates 6-areas with those distances then take an action, i.e., turn and move toward where the widest space will be guaranteed. After the action is taken, the value of Q will be updated by relative formula at the state. We set up an experimental environment with five small mobile robots, obstacles, and a target object, and tried to research for a target object while navigating in a un known hallway where some obstacles were placed. In the end of this paper, we present the results of three algorithms - a random search, an area-based action making process to determine the next action of the robot and hexagon-based Q-learning to enhance the area-based action making process.

Performance Improvement of Freight Logistics Hub Selection in Thailand by Coordinated Simulation and AHP

  • Wanitwattanakosol, Jirapat;Holimchayachotikul, Pongsak;Nimsrikul, Phatchari;Sopadang, Apichat
    • Industrial Engineering and Management Systems
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    • v.9 no.2
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    • pp.88-96
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    • 2010
  • This paper presents a two-phase quantitative framework to aid the decision making process for effective selection of an efficient freight logistics hub from 8 alternatives in Thailand on the North-South economic corridor. Phase 1 employs both multiple regression and Pearson Feature selection to find the important criteria, as defined by logistics hub score, and to reduce number of criteria by eliminating the less important criteria. The result of Pearson Feature selection indicated that only 5 of 15 criteria affected the logistics hub score. Moreover, Genetic Algorithm (GA) was constructed from original 15 criteria data set to find the relationship between logistics criteria and freight logistics hub score. As a result, the statistical tools are provided the same 5 important criteria, affecting logistics hub score from GA, and data mining tool. Phase 2 performs the fuzzy stochastic AHP analysis with the five important criteria. This approach could help to gain insight into how the imprecision in judgment ratios may affect their alternatives toward the best solution and how the best alternative may be identified with certain confidence. The main objective of the paper is to find the best alternative for selecting freight logistics hub under proper criteria. The experimental results show that by using this approach, Chiang Mai province is the best place with the confidence interval 95%.

Design and Implementation of an Intelligent Medical Expert System for TMA(Tissue Mineral Analysis) (TMA 분석을 위한 지능적 의학 전문가 시스템의 설계 및 구현)

  • 조영임;한근식
    • Journal of KIISE:Software and Applications
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    • v.31 no.2
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    • pp.137-152
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    • 2004
  • Assesment of 30 nutritional minerals and 8 toxic elements in hair are very important not only for determining adequacy, deficiencies and unbalance, but also for assessing their relative relationships in the body. A test has been developed that serves this purpose exceedingly well. This test is known as tissue mineral analysis(TMA). TMA is very popular method in hair mineral analysis for health care professionals in over 46 countries' medical center. However, there are some problems. First, they do not have database which is suitable for korean to do analyze. Second, as the TMA results from TEI-USA is composed of english documents and graphic files prohibited to open, its usability is very low. Third, some of them has low level database which is related to TMA, so hairs are sent to TEI-USA for analyzing and medical services. it bring about an severe outflow of dollars. Finally, TMA results are based on the database of american health and mineral standards, it is possibly mislead korean mineral standards. The purposes of this research is to develope the first Intelligent Medical Expert System(IMES) of TMA, in Korea, which makes clear the problems mentioned earlier IMES can analyze the tissue mineral data with multiple stage decision tree classifier. It is also constructed with multiple fuzzy rule base and hence analyze the complex data from Korean database by fuzzy inference methods. Pilot test of this systems are increased of business efficiency and business satisfaction 86% and 92% respectively.

Fault Detection and Diagnosis System for a Three-Phase Inverter Using a DWT-Based Artificial Neural Network

  • Rohan, Ali;Kim, Sung Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.4
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    • pp.238-245
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    • 2016
  • Inverters are considered the basic building blocks of industrial electrical drive systems that are widely used for various applications; however, the failure of electronic switches mainly affects the constancy of these inverters. For safe and reliable operation of an electrical drive system, faults in power electronic switches must be detected by an efficient system that is capable of identifying the type of faults. In this paper, an open switch fault identification technique for a three-phase inverter is presented. Single, double, and triple switching faults can be diagnosed using this method. The detection mechanism is based on stator current analysis. Discrete wavelet transform (DWT) using Daubechies is performed on the Clarke transformed (-) stator current and features are extracted from the wavelets. An artificial neural network is then used for the detection and identification of faults. To prove the feasibility of this method, a Simulink model of the DWT-based feature extraction scheme using a neural network for the proposed fault detection system in a three-phase inverter with an induction motor is briefly discussed with simulation results. The simulation results show that the designed system can detect faults quite efficiently, with the ability to differentiate between single and multiple switching faults.

Position Estimation of Mobile Robots using Multiple Active Sensors with Network

  • Jin, Tae-Seok
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.11 no.4
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    • pp.280-285
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    • 2011
  • Recently, with the development of service robots and the concept of ubiquitous, the position estimation of mobile objects has received great interest. Some of the localization schemes are introduced, which provide the relative location of the moving objects subjected to accumulated errors. To implement a real time localization system, a new absolute position estimation method for a mobile robot in indoor environment is proposed. Design and implementation of the localization system comes from the usage of active beacon systems (based upon RFID technology). The active beacon system is composed of an RFID receiver and an ultra-sonic transmitter. The RFID receiver gets the synchronization signal from the mobile robot and the ultra-sonic transmitter sends out the traveling signal to be used for measuring the distance. Position of a mobile robot in a three dimensional space can be calculated basically from the distance information from three beacons and the absolute position information of the beacons themselves. In some case, the mobile robot can acquire the ultrasonic signals from only one or two beacons, due to the obstacles located along the moving path. In this paper, a position estimation scheme using fewer than three sensors is developed. Also, the extended Kalman filter algorithm is applied for the improvement of position estimation accuracy of the mobile robot.