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54 results for “fuzzy rule”
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Research ArticleOpen accessIn the abstractQOS BASED SELECTION AND COMPOSITION OF WEB SERVICES-A FUZZY APPROACHN. Hema Priya, A. M. Shobana Priya, S. ChandramathiWeb Services are emerging technologies which satisfy users’ requests on the Web. Selecting appropriate services to suit the needs is a huge task. There are a huge number of service providers who offer same type of service, with differences in functional and non functional qualities. A few users may need multiple services at the same moment. So composition of services … …Journal of Computer Science, Vol. 10, Issue 5 · 18 Jan 2014 · 6,602 accessesView PDFCite
Research ArticleOpen accessIn the abstractAPPLICATION OF A FUZZY-SIMULATION MODEL OF SCHEDULING ROBOTIC FLEXIBLE ASSEMBLY CELLSKhalid Abd, Kazem Abhary, Romeo MarianThis study describes the application of the developed model to the scheduling of the Robotic Flexible Assembly Cells (RFACs). The present study is a continuation of the paper titled “Development of a Fuzzy-Simulation Model of Scheduling Robotic Flexible Assembly Cells”. This new model for multi-objective scheduling problems in RFACs was based on combining a fuzzy-based mathematical model with simulation software … …Journal of Computer Science, Vol. 9, Issue 12 · 25 Nov 2013 · 6,738 accessesView PDFCite
Research ArticleOpen accessIn the abstractCombined Pattern Mining for D3M Using FuzzyS. S. Dhenakaran, S. MaheswariMany algorithms and models were developed but the findings are not actionable and lack of soft power while solving the complex problems. Domain Driven Data mining is used a major efforts to promote the action ability of the knowledge discovery in the real world smart decision making. Combined mining is one of the common methods for analyzing complex data for … …American Journal of Applied Sciences, Vol. 10, Issue 12 · 1 Nov 2013 · 6,750 accessesView PDFCite
Research ArticleOpen accessIn the abstractDesign and Study of Online Fuzzy Risk Score Analyzer for Diabetes MellitusSunithaKarnam Anantha, Senthil Kumar Natarajan, Subransu Sekar DashThe aim of this study is to determine the risks of various subjects to type 2 Diabetes and its dependence on the different subject records. A Fuzzy based system was designed to find the risk scores for diabetes based on risk score derived from Chennai Urban Rural Epidemiology Study (CURES). The risk score that has been adapted into the system … …American Journal of Applied Sciences, Vol. 10, Issue 9 · 24 Aug 2013 · 6,379 accessesView PDFCite
Research ArticleOpen accessIn the abstractTECHNICAL ANALYSIS OF FUZZY METAGRAPH BASED DECISION SUPPORT SYSTEM FOR CAPITAL MARKETAnbalagan Thirunavukarasu, Uma MaheswariThis study proposes a Fuzzy Metagraph based Decision Support System (DSS) for short term and long term investment in share market. This rule base decision system will help traders to make correct decision at very low risk. Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD) and WILLIAM- %R are some of the Technical Indicators which are used as input … …Journal of Computer Science, Vol. 9, Issue 9 · 6 Aug 2013 · 6,690 accessesView PDFCite
Research ArticleOpen accessIn the abstractMODELING AND SIMULATION OF FUZZY BASED AUTOMATIC INSULIN DELIVERY SYSTEMSunithaKarnam Anantha, Senthil Kumar Natarajan, Subransu Sekar DashThe aim is to design a complete online, automatic, intelligent and independent insulin delivery system. The proposed system calculates the amount of insulin by formulation based upon two linguistic factors i.e. weight and blood glucose levels. These factors have been used to develop a rule based fuzzy system in LabVIEW. The fuzziness brings a better regulation into the regime than … …Journal of Computer Science, Vol. 9, Issue 9 · 6 Aug 2013 · 6,623 accessesView PDFCite
Research ArticleOpen accessIn the abstractA NOVEL APPROACH BASED ON GENETIC FUZZY CLUSTERING AND ADAPTIVE NEURAL NETWORKS FOR SALES FORECASTINGAttariuas Hichama, Bouhorma Mohameda, El Fallahi AbdellahbThis article proposes a new hybrid sales forecasting system based on genetic fuzzy clustering and Back-Propagation (BP) Neural Networks with adaptive learning rate (GFCBPN).The proposed architecture consists of three stages: (1) utilizing Winter’s Exponential Smoothing method and Fuzzy C-Means clustering, all normalized data records will be categorized into k clusters; (2) using an adapted Genetic Fuzzy System (MCGFS), the fuzzy … …Journal of Computer Science, Vol. 9, Issue 8 · 2 Jul 2013 · 6,669 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Development of Expert Mood Identifier System using Fuzzy Logic on Blackberry PlatformOctavia George, Maria Gorethi, Syerra Riswandi, Widodo BudihartoIn our daily life, deciding what caused the bad mood is not easy. This study will design an Expert Mood Identifier System for mobile application. We propose a model that uses 6 variables as the inputs, they are intensity of Sleep (SL), intensity of Eat (ET), hours of using Phone (PH), Spare Time (ST), intensity of Sensitive (SN), intensity of … …Journal of Computer Science, Vol. 9, Issue 6 · 3 Jun 2013 · 7,003 accessesView PDFCite
Research ArticleOpen accessIn the abstractDesign and Development of an Intelligent Control by Using Bee Colony Optimization TechniqueS. Tiacharoen, T. ChatchanayuenyongProblem statement: In the modern industrial manufacturing system, the efficiency of machine control is essential to reduce waste and increase the output. Most of the manufacturing machines employ an induction motor in their driving system. A number of induction motors must be controlled during machine operation. The more accurately these motors are controlled the higher is the quality of the … …American Journal of Applied Sciences, Vol. 9, Issue 9 · 4 Aug 2012 · 6,806 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvolving Fuzzy Neural Network for Phishing Emails DetectionAmmar ALmomani, Tat-Chee Wan, Altyeb Altaher et al.One of the broadly used internet attacks to deceive customers financially in banks and agencies is unknown “zero-day” phishing Emails “zero-day” phishing Emails is a new phishing email that it has not been trained on old dataset, not included in black list. Accordingly, the current paper seeks to Detection and Prediction of unknown “zero-day” phishing Emails by provide a new … …Journal of Computer Science, Vol. 8, Issue 7 · 4 Jun 2012 · 8,005 accessesView PDFCite