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54 results for “Adaptive Models”
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EditorialOpen accessIn the abstractChasing the Fat Demon: Fat Chance, Buddy?David L. Katz, Joachim Storsberg, Christian SchmidtScience is an interesting profession. At times, one could get caught up in his or her own world of thoughts, perception, far away from reality, sometimes referred to as the proverbial ivory tower (Lederberg, 1972). Science for the sake of science is, per se, not without merit, with our fragmented understanding of a given issue providing ample justification for experimentation … …American Journal of Immunology, Vol. 13, Issue 2 · 29 May 2017 · 8,137 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultiple Vehicle Tracking using Adaptive Gaussian Mixture Model and Kalman FilterFandy Setyo UtomoBased on data from the Central Statistics Agency (BPS) of the Republic of Indonesia in catalog Crime Statistics in 2014, the number of crimes of theft of motor vehicles has increased since 2010 until 2013. Recorded in 2013 the number reached 42.508 cases of theft. In this study, we made a prototype application using Adaptive Gaussian Mixture Models algorithms and … …American Journal of Applied Sciences, Vol. 13, Issue 12 · 22 Dec 2016 · 7,379 accessesView PDFCite
Research ArticleOpen accessIn the abstractHydrological Forecasting Using Hybrid Data-Driven ApproachYoungmin Seo, Sungwon KimThis study develops a hybrid model, EEMD-FANN, coupling feed Forward Artificial Neural Network (FANN) and Ensemble Empirical Mode Decomposition (EEMD) for improving the accuracy of daily river stage forecasting. An original river stage data is broken down into a residue and Intrinsic Mode Functions (IMFs) using the EEMD and different FANNs are developed as forecasting models for the decomposed IMFs … …American Journal of Applied Sciences, Vol. 13, Issue 8 · 2 Sep 2016 · 8,140 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Bayesian Adaptive Design for Combination of Three Drugs in Cancer Phase I Clinical TrialsMourad Tighiouart, Quanlin Li, Steven Piantadosi, Andre RogatkoWe describe a Bayesian adaptive design for early phase cancer trials of a combination of three agents. This is an extension of an earlier work by the authors by allowing all three agents to vary during the trial and by assigning different drug combinations to cohorts of three patients. The primary objective is to estimate the Maximum Tolerated Dose (MTD) … …Current Research in Biostatistics, Vol. 6, Issue 1 · 25 Aug 2016 · 8,426 accessesView PDFCite
EditorialOpen accessIn the abstractImpact of Quantitative Pharmacology on Drug DevelopmentAna Ruiz-Garcia, Kourosh ParivarThesuccess of drug development rests over two well defined pillars, a goodunderstanding of the drug’s clinical pharmacology and the appropriate targetpopulation for whom the clinical use is intended. The label for human prescription drugsrequires a good understanding of the pharmacological effects (pharmacodynamicsor PD) and the mechanism of action of the drug as well as detailed informationof the drug’s Pharmacokinetics (PK): … …American Journal of Pharmacology and Toxicology, Vol. 9, Issue 4 · 24 Apr 2015 · 7,164 accessesView PDFCite
Research ArticleOpen accessIn the abstractNelder-Mead Method with Local Selection Using Neighborhood and Memory for Stochastic OptimizationNoocharin Tippayawannakorn, Juta PichitlamkenWe consider the Nelder-Mead (NM) simplex algorithm for optimization of discrete-event stochastic simulation models. We propose new modifications of NM to reduce computational time and to improve quality of the estimated optimal solutions. Our means include utilizing past information of already seen solutions, expanding search space to their neighborhood and using adaptive sample sizes. We compare performance of these extensions … …Journal of Computer Science, Vol. 9, Issue 4 · 10 May 2013 · 6,126 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance of Multiple Linear Regression and Nonlinear Neural Networks and Fuzzy Logic Techniques in Modelling House PricesSiti Amri, Gurudeo Anand TularamHouse price prediction continues to be important for government agencies insurance companies and real estate industry. This study investigates the performance of house sales price models based on linear and non-linear approaches to study the effects of selected variables. Linear stepwise Multiple Regression (MR) and nonlinear models of Neural Network (NN) and Adaptive Neuro-Fuzzy (ANFIS) are developed and compared. The … …Journal of Mathematics and Statistics, Vol. 8, Issue 4 · 18 Dec 2012 · 8,434 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetection of Aberrant Data Points for an effective Effort Estimation using an Enhanced Algorithm with Adaptive FeaturesS. Malathi, S. SridharProblem statement: The spiraling growth of IT industry has witnessed an unprecedented change in the software development paradigm, from algorithmic models to machine learning techniques. At present, there are no standard methods to predict the accuracy of software cost estimation, which is an important goal of the software community. Approach: This study proposes a simple and systematic algorithmic procedure for … …Journal of Computer Science, Vol. 8, Issue 2 · 21 Nov 2011 · 7,095 accessesView PDFCite
Research ArticleOpen accessIn the abstractUsing an Adaptative Fuzzy-Logic System to Optimize the Performances and the Reduction of Chattering Phenomenon in the Control of Induction MotorM. M. Krishan, L. Barazane, A. KhwaldehProblem statement: Neural networks and fuzzy inference systems are becoming well-recognized tools of designing an identifier/controller capable of perceiving the operating environment and imitating a human operator with high performance. Also, by combining these two features, more versatile and robust models, called “neuro-fuzzy” architectures have been developed. The mo Approach: Motivation behind the use of neuro-fuzzy approaches was based on … …American Journal of Applied Sciences, Vol. 7, Issue 1 · 31 Jan 2010 · 7,526 accessesView PDFCite