195,477 research outputs found

    Quality Function Deployment and Fuzzy TOPSIS Methods in Decision Support System for Internet Service Provider Selection

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    Internet Service Provider (ISP) is a company or business organization that provides access to intenet and services related for individual consumer or companies. There are many ISP in Indonesia recently, and they have almost the same product to offered. This problem makes internet service provider selection become a major issue. Decision support system can be used to recommend the best ISP company based on need. The aim of this research is to used Quality Function Deployment with Fuzzy TOPSIS sequentially to select the best ISP company as needed, and implemented in decision support system for internet service provider selection. Quality Function Deployment and Fuzzy TOPSIS methods used to evaluate, and then recommend the ISP company by ranked. Quality Function Deployment method used to find out customers requirements about internet network, the weighting of the criteria and the assessment of each ISP company. Fuzzy TOPSIS used to rank ISP company. These two methods produce consistent ratings when sensitivity analysis is performed for fuzzy and crisp value. These two methods make decision support system result can be trusted

    Fuzzy Reinforcement Learning using Neural Network: An Application to Medical Diagnosis and Business Intelligence

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    The information available to the system is incomplete in many applications particularly in Decision Support Systems The fuzzy logic deals incomplete information with belief rather than likelihood probability Sometimes the decision has to be taken with fuzzy information In this paper fuzzy machine learning is studied for decision support systems The fuzzy Decision set is defined with two-fold fuzzy set The fuzzy inference is studied with fuzzy neural network for fuzzy Decision sets Business application is given as applicatio

    Fuzzy Reinforcement Learning using Neural Network: An Application to Medical Diagnosis and Business Intelligence

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    The information available to the system is incomplete in many applications, particularly in Decision Support Systems. The fuzzy logic deals incomplete information with belief rather than likelihood (probability). Sometimes the decision has to be taken with fuzzy information. In this paper, fuzzy machine learning is studied for decision support systems. The fuzzy Decision set is defined with two-fold fuzzy set. The fuzzy inference is studied with fuzzy neural network for fuzzy Decision sets. Business application is given as application

    Fuzzy Logic in Clinical Practice Decision Support Systems

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    Computerized clinical guidelines can provide significant benefits to health outcomes and costs, however, their effective implementation presents significant problems. Vagueness and ambiguity inherent in natural (textual) clinical guidelines is not readily amenable to formulating automated alerts or advice. Fuzzy logic allows us to formalize the treatment of vagueness in a decision support architecture. This paper discusses sources of fuzziness in clinical practice guidelines. We consider how fuzzy logic can be applied and give a set of heuristics for the clinical guideline knowledge engineer for addressing uncertainty in practice guidelines. We describe the specific applicability of fuzzy logic to the decision support behavior of Care Plan On-Line, an intranet-based chronic care planning system for General Practitioners

    Sistem Penunjang Keputusan Pemilihan Sekolah Luar Biasa Dengan Metode Fuzzy Multiple Criteria Decision Making

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    Decision support system has many methods that can be used by decision makers. one of the methods is fuzzy multiple criteria decision making (FMCDM) this method will help decision makers to make the final decision with regard to multiple criteria decision alternatives. This final task will be to apply the decision support system with fuzzy multiple criteria decision making to determine the selection of special schools

    Fuzzy Decision-Support System for Safeguarding Tangible and Intangible Cultural Heritage

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    In the current world economic situation, the maintenance of built heritage has been limited due to a lack of funds and accurate tools for proper management and implementation of these actions. However, in specific local areas, the maintenance and conservation of historical and cultural heritage have become an investment opportunity. In this sense, in this study, a new tool is proposed, for the estimation of the functional service life of heritage buildings in a local region (city of Seville, South Spain). This tool is developed in Art-Risk research project and consists of a free software to evaluate decisions in regional policies, planning and management of tangible and intangible cultural heritage, considering physical, environmental, economic and social resources. This tool provides a ranking of priority of intervention among case studies belonging to a particular urban context. This information is particularly relevant for the stakeholders responsible for the management of maintenance plans in built heritage

    Cloud Based Intelligent Decision Support System for Disaster Management Using Fuzzy Logic

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    Field of cloud computing is an emerging field in computer science. Computational intelligence and Decision support systems (DSS) have to gain concern as a computing solution to planned and unplanned problems of organizations in order to progress decision-making tasks in a better way. In today era, Disaster management is a big problem. To overcome this problem, a real time computation is required. Cloud computing is a tool to offer promising support to decision support system in a real time environment. In this paper, a fuzzy based decision support system is proposed to meet all the requirements using fuzzy logic inference system

    SISTEM PENDUKUNG KEPUTUSAN DALAM BENTUK SIMULASI KEBIJAKAN PERENCANAAN BAHAN BAKU DAN PRODUKSI BAGI IKM FURNITURE DI SOLO RAYA

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    ASBTRACT The level of intense competition at the moment, demanding every industry to make a decision how much number of production and production capacity of the company that is able to meet consumer demand. Therefore we need a system that can assist managers in taking decisions that are called decision support systems. Decision support systems are interactive computerbased systems that help decision-makers utilize data and models to solve a problem that is not structured. This decision support system is created by using the programming language PHP and the MySQL database. Prior to the decision-making process is carried out forecasting demand for the next period by using Trend Projection method. Whereas decision making is done by using Fuzzy logic.One of the fuzzy method that can be used in solving these problems is the Fuzzy Tsukamoto Inference System methodthat apply an average weighted to calculate the number of the production Board and purchase logs by considering the number of requests and the supplies of raw materials in the form of logs or boards. As a result of this final project is the making of a decision support system in the form of simulation planning policy of raw materials and production for IKM Furniture in Solo that can assist managers in determining policy planning the amount of board production and the amount of raw material purchase log for the next period. Key words: Forecasting, decision support Systems, Php, MySQL, Trend Projection, Fuzzy logic, Fuzzy Tsukamoto, furniture, raw materials and production Plannin
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