Institution
Graduate University of Advanced Technology
Education•Kerman, Iran•
About: Graduate University of Advanced Technology is a education organization based out in Kerman, Iran. It is known for research contribution in the topics: Carbon paste electrode & Electrochemical gas sensor. The organization has 890 authors who have published 2169 publications receiving 31027 citations.
Topics: Carbon paste electrode, Electrochemical gas sensor, Cyclic voltammetry, Electrode, Differential pulse voltammetry
Papers
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TL;DR: The network reconfiguration and capacitor placement simultaneously are employed simultaneously to reduce energy losses and improve the system reliability subjected to satisfy operational and power quality constraints using a fuzzy approach.
61 citations
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TL;DR: A new distributed energy efficient multi-level route-aware clustering algorithm for WSNs called MLRC is proposed, which applies a route conscious manner in which nodes could gain desired information about possible routes to the destination and construct an optimal routing tree with the least transmission cost.
60 citations
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TL;DR: The MD simulation comparison of two bilayers showed that the ST60/Ergo vesicles have better properties for gene delivery, and in vitro results confirmed the in silico results and revealed that Ergo-niosomes have smaller size, better polydispersity, and slower release of plasmid than Chol- niosome.
60 citations
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TL;DR: The proposed point forecast model (GMDHMFOA) has an acceptable error and better performance than the other ones commonly used in predicting energy consumption and provides suitable solutions for energy management of the microgrid.
60 citations
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01 Dec 2015TL;DR: Combining static and dynamic ensemble strategies as well as utilizing NSGA-II are the main contributions of this research, confirming that the proposed methods outperform the other ensemble approaches over 14 datasets in terms of classification accuracy.
Abstract: Proposing a new hybrid approach for ensemble learning systems that exploits the abilities of static ensemble selection (SES) and dynamic ensemble selection (DES) strategies.Presenting an SES approach based on NSGAII multi-objective genetic algorithm.Improving one of the DES approaches by utilizing the SES proposed method.Justifying the performance of the proposed methods by UCI repository and LKC datasets. Ensemble learning is a system that improves the performance and robustness of the classification problems. How to combine the outputs of base classifiers is one of the fundamental challenges in ensemble learning systems. In this paper, an optimized Static Ensemble Selection (SES) approach is first proposed on the basis of NSGA-II multi-objective genetic algorithm (called SES-NSGAII), which selects the best classifiers along with their combiner, by simultaneous optimization of error and diversity objectives. In the second phase, the Dynamic Ensemble Selection-Performance (DES-P) is improved by utilizing the first proposed method. The second proposed method is a hybrid methodology that exploits the abilities of both SES and DES approaches and is named Improved DES-P (IDES-P). Accordingly, combining static and dynamic ensemble strategies as well as utilizing NSGA-II are the main contributions of this research. Findings of the present study confirm that the proposed methods outperform the other ensemble approaches over 14 datasets in terms of classification accuracy. Furthermore, the experimental results are described from the view point of Pareto front with the aim of illustrating the relationship between diversity and the over-fitting problem.
60 citations
Authors
Showing all 906 results
Name | H-index | Papers | Citations |
---|---|---|---|
Michael Wink | 83 | 938 | 32658 |
Hassan Karimi-Maleh | 63 | 245 | 12503 |
Hadi Beitollahi | 56 | 272 | 8023 |
Sayed Khatiboleslam Sadrnezhaad | 38 | 215 | 4959 |
Akbar Maleki | 36 | 78 | 3542 |
Alireza Goudarzi | 34 | 117 | 4065 |
Alireza Askarzadeh | 32 | 68 | 4369 |
Somayeh Tajik | 31 | 109 | 2602 |
Mohammad Najafzadeh | 30 | 60 | 1882 |
Daryoush Afzali | 29 | 111 | 2363 |
Mehdi Yoosefian | 27 | 66 | 1673 |
Masoud Torkzadeh-Mahani | 26 | 94 | 1687 |
Reza Mohammadinejad | 26 | 85 | 2454 |
Farshid Keynia | 24 | 68 | 2402 |
Mohammad Yaghoobi | 24 | 83 | 1847 |