• 제목/요약/키워드: Decision Making Algorithm

검색결과 516건 처리시간 0.028초

하수처리시설에서 인 고도처리를 위한 일체형 침전부상공정(SeDAF)의 응집제 주입농도 자동제어기법 검토 (Automatic control of coagulant dosage on the sedimentation and dissolved air flotation(SeDAF) process for enhanced phosphorus removal in sewage treatment facilities)

  • 장여주;정진홍;김원재
    • 상하수도학회지
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    • 제34권6호
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    • pp.411-423
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    • 2020
  • To remove phosphorus from the effluent of public wastewater treatment facilities, hundreds of enhanced phosphorus treatment processes have been introduced nationwide. However, these processes have a few problems including excessive maintenance cost and sludge production caused by inappropriate coagulant injection. Therefore, the optimal decision of coagulant dosage and automatic control of coagulant injection are essential. To overcome the drawbacks of conventional phosphorus removal processes, the integrated sedimentation and dissolved air flotation(SeDAF) process has been developed and a demonstration plant(capacity: 100 ㎥/d) has also been installed. In this study, various jar-tests(sedimentation and / or sedimentation·flotation) and multiple regression analyses have been performed. Particularly, we have highlighted the decision-making algorithms of optimal coagulant dosage to improve the applicability of the SeDAF process. As a result, the sedimentation jar-test could be a simple and reliable method for the decision of appropriate coagulant dosage in field condition of the SeDAF process. And, we have found that the SeDAF process can save 30 - 40% of coagulant dosage compared with conventional sedimentation processes to achieve total phosphorus (T-P) concentration below 0.2 mg/L of treated water, and it can also reduce same portion of sludge production.

Matrix-Based Intelligent Inference Algorithm Based On the Extended AND-OR Graph

  • Lee, Kun-Chang;Cho, Hyung-Rae
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 1999년도 추계학술대회-지능형 정보기술과 미래조직 Information Technology and Future Organization
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    • pp.121-130
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    • 1999
  • The objective of this paper is to apply Extended AND-OR Graph (EAOG)-related techniques to extract knowledge from a specific problem-domain and perform analysis in complicated decision making area. Expert systems use expertise about a specific domain as their primary source of solving problems belonging to that domain. However, such expertise is complicated as well as uncertain, because most knowledge is expressed in causal relationships between concepts or variables. Therefore, if expert systems can be used effectively to provide more intelligent support for decision making in complicated specific problems, it should be equipped with real-time inference mechanism. We develop two kinds of EAOG-driven inference mechanisms(1) EAOG-based forward chaining and (2) EAOG-based backward chaining. and The EAOG method processes the following three characteristics. 1. Real-time inference : The EAOG inference mechanism is suitable for the real-time inference because its computational mechanism is based on matrix computation. 2. Matrix operation : All the subjective knowledge is delineated in a matrix form, so that inference process can proceed based on the matrix operation which is computationally efficient. 3. Bi-directional inference : Traditional inference method of expert systems is based on either forward chaining or backward chaining which is mutually exclusive in terms of logical process and computational efficiency. However, the proposed EAOG inference mechanism is generically bi-directional without loss of both speed and efficiency.

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An Improved Dempster-Shafer Algorithm Using a Partial Conflict Measurement

  • Odgerel, Bayanmunkh;Lee, Chang-Hoon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제16권4호
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    • pp.308-317
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    • 2016
  • Multiple evidences based decision making is an important functionality for computers and robots. To combine multiple evidences, mathematical theory of evidence has been developed, and it involves the most vital part called Dempster's rule of combination. The rule is used for combining multiple evidences. However, the combined result gives a counterintuitive conclusion when highly conflicting evidences exist. In particular, when we obtain two different sources of evidence for a single hypothesis, only one of the sources may contain evidence. In this paper, we introduce a modified combination rule based on the partial conflict measurement by using an absolute difference between two evidences' basic probability numbers. The basic probability number is described in details in Section 2 "Mathematical Theory of Evidence". As a result, the proposed combination rule outperforms Dempster's rule of combination. More precisely, the modified combination rule provides a reasonable conclusion when combining highly conflicting evidences and shows similar results with Dempster's rule of combination in the case of the both sources of evidence are not conflicting. In addition, when obtained evidences contain multiple hypotheses, our proposed combination rule shows more logically acceptable results in compared with the results of Dempster's rule.

항적 데이터 학습을 통한 추천 항로 구성에 관한 연구 (Composing Recommended Route through Machine Learning of Navigational Data)

  • 김주성;정중식;이성용;이은석
    • 한국항해항만학회:학술대회논문집
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    • 한국항해항만학회 2016년도 춘계학술대회
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    • pp.285-286
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    • 2016
  • 해상교통관제센터에 의해 실시간으로 수집되는 선박의 항해 데이터를 바탕으로 선박 항적 패턴 인식을 수행하고 이를 바탕으로 항적 모델을 추출하여 사전에 선위를 예측하는 기법을 제안한다. 항적 데이터의 처리와 가공, 항적 모델링을 위하여 Support Vector Regression 알고리즘이 사용되었으며, 적정 파라미터 선정을 위하여 k-fold cross validation과 grid search가 사용되었다. 제안된 항적 데이터 모델링 기법을 통하여 사전에 선박의 선위를 예측하여 해상교통과제사의 의사결정을 지원하고자 한다.

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Organizational Memory Formulation by Inference Diagram

  • Lee, Kun-Chang;Nho, Jae-Bum
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 1999년도 추계학술대회 및 정기총회 : 정보통신기술의 활용과 21세기 전자상거래
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    • pp.42-46
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    • 1999
  • Knowledge management(KM) is emerging as a robust management mechanism with which an organization can remain highly intelligent and competitive in a turbulent market. Organization memory(or knowledge) is at the heart of KM success. How to create organizational memory has been debated among researchers. In literature, a wide variety of methods for creating organizational memory have been proposed only to prove that its applicability is limited to decision-making problems which require shallow or non-causal knowledge type. However, organizational memory with a sense of causal knowledge is highly required in solving complicated decision-making problems in which complex dynamics exist between various factors and influence each other with cause and effect relationship among them. In this respect, we propose a new approach to creating a causal-typed organizational memory (CATOM), which has a form of causal knowledge and is represented in a matrix form, by using an inference diagram. An algorithm for CATOM creation is suggested and applied to an illustrative example. Results show that our proposed KM approach can effectively equip an organization with semi-automated CATOM creation and inference process which is deemed useful in a highly competitive business environment.

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J48 and ADTree for forecast of leaving of hospitals

  • Halim, Faisal;Muttaqin, Rizal
    • 한국인공지능학회지
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    • 제4권1호
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    • pp.11-13
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    • 2016
  • These days, medical technology has been developed rapidly to meet desire of living healthy life. Average lifespan was extended to let people see a doctor because of many reasons. This study has shown rate of leaving of hospitals to investigate the rate of not only department of surgery but also department of internal medicine. Linear model, tree, classification rule, association and algorithm of data mining were used. This study investigated by using J48 and AD tree of decision-making tree In this study, J48 and AD tree of decision-making tree of data mining were used to investigate based on result of both data. Both algorithms were found to have similar performance. Both algorithms were not equivalent to require detailed experiment. Collect more experimental data in the future to apply from various points of view. Development of medical technology gives dream, hope and pleasure. The ones who suffer from incurable diseases need developed medical technology. Environment being similar to the reality shall be made to experiment exactly to investigate data carefully and to let the ones of various ages visit hospital and to increase survival rate.

Middleware for Ubiquitous Healthcare Information System

  • Sain, Mangal;Lee, Hoon-Jae;Chung, Wan-Young
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2008년도 추계종합학술대회 B
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    • pp.257-260
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    • 2008
  • We build middleware architecture with J2EE and LiveGraph to process different ubiquitous healthcare application's data and process that data into useful information, which can play a most important role in decision making in ubiquitous Healthcare System. Application developers mostly rely on third party middleware, tools and libraries (i.e., webservers, distributed middleware such as CORBA, etc.) to respond the emerging trends of their target domain. With this middleware we tried to enhance the efficiency of application by decrease their memory uses, data processing and decision making on another web module which is independent of each application. For middleware system, we proposed an algorithm by which we can find some important conclusion about different health status likewise ECG, Accelerometer. etc., which can be used in various data processing and determine the current health status. In this paper we also analyze some different low level and high level middleware technology which were used to build different kind middleware likewise CAMUS, MiLAN and try to find the best solution in the form of middleware for Ubiquitous Healthcare Information System.

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개념설계단계에서 요구품질을 고려한 설계사양 중요도 결정방법 (A Priority Setting Method of the Design Specifications with regards to Functional Requirements at the stage of Concept Design)

  • 박지형;이중호;염기원
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2006년도 춘계학술대회 논문집
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    • pp.119-120
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    • 2006
  • Prioritizing the design specifications among many alternatives is necessary at the stage of concept design. Design specifications have trade-offs between cost and performance, and the relationships among them, in the standpoint of various functional requirements, are complex. AHP(Analytic Hierarchy Process) method is one of the most popular ways of solving the priority setting problem. However, it is impossible to monitor the interim findings in the middle of the process, it is hard to predict the difference when changing pairwise comparison conditions, and the operation done by one person makes it hard to share the process simultaneously. This paper shows a new method of priority setting in this kind of decision making problem. This method is designed to support the realtime priority setting among many design specifications with regards to many functional requirements. A new algorithm and visualization methods are introduced, and the usability is verified in an exemplary concept design stage.

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DNA Based Cloud Storage Security Framework Using Fuzzy Decision Making Technique

  • Majumdar, Abhishek;Biswas, Arpita;Baishnab, Krishna Lal;Sood, Sandeep K.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권7호
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    • pp.3794-3820
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    • 2019
  • In recent years, a cloud environment with the ability to detect illegal behaviours along with a secured data storage capability is much needed. This study presents a cloud storage framework, wherein a 128-bit encryption key has been generated by combining deoxyribonucleic acid (DNA) cryptography and the Hill Cipher algorithm to make the framework unbreakable and ensure a better and secured distributed cloud storage environment. Moreover, the study proposes a DNA-based encryption technique, followed by a 256-bit secure socket layer (SSL) to secure data storage. The 256-bit SSL provides secured connections during data transmission. The data herein are classified based on different qualitative security parameters obtained using a specialized fuzzy-based classification technique. The model also has an additional advantage of being able to decide on selecting suitable storage servers from an existing pool of storage servers. A fuzzy-based technique for order of preference by similarity to ideal solution (TOPSIS) multi-criteria decision-making (MCDM) model has been employed for this, which can decide on the set of suitable storage servers on which the data must be stored and results in a reduction in execution time by keeping up the level of security to an improved grade.

GIS기반 최적공간선정을 위한 시스템론적 접근 (System Theory Approach for Decision Making of GIS-based Optimum Allocation)

  • 오상영
    • 한국콘텐츠학회논문지
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    • 제6권12호
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    • pp.121-127
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    • 2006
  • 정보기술 발전과 함께 GIS(geographical information system) 기술이 빠르게 발전하면서 GIS를 이용한 공간분석(spatial analysis)에 관한 수요가 증대되고 있다. 특히 GIS의 일반기술에 관한 연구보다 GIS를 이용한 공간분석연구가 많아지면서 이를 다양하게 응용하여 활용하고 있다. 그러나 대부분의 GIS연구는 밀도기반 군집화 방식인 DBSCAN 또는 개개의 데이터에 가중치를 부여하여 군집화한 DBSCAN-W 등 공간적 현상을 다루고 있으며 시간차원의 합리적 의사결정의 중요성은 간과되고 있다. 본 연구에서는 이와 같이 GIS를 기반으로 한 최적 공간선정을 위해 시간차원의 도입을 위해 시스템 다이내믹스(system dynamics) 이론을 접목하여 접근할 수 있는 방법을 제공하고자 한다.

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