University of Tabriz

About: University of Tabriz is a education organization based out in Tabriz, Iran. It is known for research contribution in the topics: Population & Nanocomposite. The organization has 12141 authors who have published 20976 publications receiving 313982 citations.

Symmetric multilevel inverter with reduced components based on non-insulated dc voltage sources

Abstract: Multilevel inverters have an important portion in power processing in power systems. These inverters have some inherent advantages such as ability to operate with high power and voltage, improved output waveform quality and flexibility which make them attractive and more popular. This study proposes a new topology based on the non-insulated dc voltage sources for multilevel inverter with reduced number of switching devices. As a result, it reduces control complexity and gate driver circuits. The proposed topology is a general topology which can be easily extended to a desired number of voltage levels. All of the desired output voltage levels (both odd and even) can be achieved using the proposed topology. The validity of the proposed multilevel inverter is verified with both computer simulation and experimental results from a 15-level laboratory prototype.

1 – Metaheuristic Algorithms in Modeling and Optimization

Abstract: Metaheuristic algorithms have become powerful tools for modeling and optimization This chapter provides an overview of nature-inspired metaheuristic algorithms, especially those developed in the last two decades, and their applications We will briefly introduce algorithms such as genetic algorithms, differential evolution, genetic programming, fuzzy logic, and most importantly, swarm-intelligence-based algorithms such as ant and bee algorithms, particle swarm optimization, cuckoo search, firefly algorithm, bat algorithm, and krill herd algorithm We also briefly describe the main characteristics of these algorithms and outline some recent applications of these algorithms

Application of wavelet-artificial intelligence hybrid models for water quality prediction: a case study in Aji-Chay River, Iran

Abstract: The accuracy of Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), wavelet-ANN and wavelet-ANFIS in predicting monthly water salinity levels of northwest Iran’s Aji-Chay River was assessed. The models were calibrated, validated and tested using different subsets of monthly records (October 1983 to September 2011) of individual solute (Ca2+, Mg2+, Na+, SO4 2− and Cl−) concentrations (input parameters, meq L−1), and electrical conductivity-based salinity levels (output parameter, µS cm−1), collected by the East Azarbaijan regional water authority. Based on the statistical criteria of coefficient of determination (R2), normalized root mean square error (NRMSE), Nash–Sutcliffe efficiency coefficient (NSC) and threshold statistics (TS) the ANFIS model was found to outperform the ANN model. To develop coupled wavelet-AI models, the original observed data series was decomposed into sub-time series using Daubechies, Symlet or Haar mother wavelets of different lengths (order), each implemented at three levels. To predict salinity input parameter series were used as input variables in different wavelet order/level-AI model combinations. Hybrid wavelet-ANFIS (R2 = 0.9967, NRMSE = 2.9 × 10−5 and NSC = 0.9951) and wavelet-ANN (R2 = 0.996, NRMSE = 3.77 × 10−5 and NSC = 0.9946) models implementing the db4 mother wavelet decomposition outperformed the ANFIS (R2 = 0.9954, NRMSE = 3.77 × 10−5 and NSC = 0.9914) and ANN (R2 = 0.9936, NRMSE = 3.99 × 10−5 and NSC = 0.9903) models.

Carbon quantum dots: recent progresses on synthesis, surface modification and applications

Abstract: Generally, carbon nanoparticles with a size of 10 nm (or less) are called carbon quantum dots (CQDs, C-dots or CD), which have created huge excitement due to their advantages in chemical inertness, high water solubility, excellent biocompatibility, resistance to photobleaching and various optical superiority. In this article, we describe the recent advancements in the area of CQDs; concentrating on their synthesis techniques, size control, surface modification approaches, optical properties, luminescent mechanism, and their applications in bioimaging, biosensing, drug delivery and catalysis.