Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 9Citation - Scopus: 10Modelling Trip Distribution With Fuzzy and Genetic Fuzzy Systems(Taylor and Francis Ltd., 2013) Kompil, Mert; Çelik, Hüseyin MuratThis paper explores the potential capabilities of fuzzy and genetic fuzzy system approaches in urban trip distribution modelling with some new features. First, a simple fuzzy rule-based system (FRBS) and a novel genetic fuzzy rule-based system [GFRBS: a fuzzy system improved by a knowledge base learning process with genetic algorithms (GAs)] are designed to model intra-city passenger flows for Istanbul. Subsequently, their accuracy, applicability and generalizability characteristics are evaluated against the well-known gravity- and neural network (NN)-based trip distribution models. The overall results show that: traditional doubly constrained gravity models are still simple and efficient; NNs may not show expected performance when they are forced to satisfy trip constraints; simply-designed FRBSs, learning from observations and expertise, are both efficient and interpretable even if the data are large and noisy; and use of GAs in fuzzy rule-based learning considerably increases modelling performance, although it brings additional computation cost.Article Citation - WoS: 28Citation - Scopus: 27Determination of Thiamine Hcl and Pyridoxine Hcl in Pharmaceutical Preparations Using Uv-Visible Spectrophotometry and Genetic Algorithm Based Multivariate Calibration Methods(Pharmaceutical Society of Japan, 2004) Özdemir, Durmuş; Dinç, ErdalSimultaneous determination of binary mixtures pyridoxine hydrochloride and thiamine hydrochloride in a vitamin combination using UV-visible spectrophotometry and classical least squares (CLS) and three newly developed genetic algorithm (GA) based multivariate calibration methods was demonstrated. The three genetic multivariate calibration methods are Genetic Classical Least Squares (GCLS), Genetic Inverse Least Squares (GILS) and Genetic Regression (GR). The sample data set contains the UV-visible spectra of 30 synthetic mixtures (8 to 40 μg/ml) of these vitamins and 10 tablets containing 250 mg from each vitamin. The spectra cover the range from 200 to 330 nm in 0.1 nm intervals. Several calibration models were built with the four methods for the two components. Overall, the standard error of calibration (SEC) and the standard error of prediction (SEP) for the synthetic data were in the range of <0.01 and 0.43 μg/ml for all the four methods. The SEP values for the tablets were in the range of 2.91 and 11.51 mg/tablets. A comparison of genetic algorithm selected wavelengths for each component using GR method was also includedArticle Citation - WoS: 16Citation - Scopus: 19Genetic Multivariate Calibration Methods for Near Infrared (nir) Spectroscopic Determination of Complex Mixtures(TUBITAK, 2004) Özdemir, Durmuş; Öztürk, BetülThe simultaneous determination of ternary mixtures of methylene chloride, ethyl acetate, and methanol using near infrared (NIR) spectroscopy and 4 different genetic algorithms based multivariate calibration methods was demonstrated. The 4 genetic multivariate calibration methods are genetic partial least squares (GPLS), genetic regression (GR), genetic classical least squares (GCLS) and genetic inverse least squares (GILS). The sample data set contains the NIR spectra of 63 ternary mixtures and covers the range from 900 to 2000 nm in 2 nm intervals. Of these 63 spectra, 42 were used as the calibration set, and 21 were reserved for the prediction purposes. Several calibration models were built with the 4 genetic algorithm based methods for each component that makes up the mixtures. Overall, the standard error of calibration (SEC) and the standard error of prediction (SEP) were in the range of 0.22 to 2.5 (% by volume (v/v)) for all the 4 methods. A comparison of genetic algorithm selected wavelengths for each component and for each method was also included.