نتایج جستجو برای: multi objective genetic algorithm moga

تعداد نتایج: 2159089  

Journal: :journal of biomedical physics and engineering 0
a. nickfarjam tarbiat modares university, medical physics department, tehran, iran. s. m. p. firoozabadi tarbiat modares university, medical physics department, tehran, iran. b. kalaghchi cancer research center, tehran university of medical sciences, tehran, iran.

background: irreversible electroporation (ire) is a novel tumor ablation technique. ire is associated with high electrical fields and is often reported in conjunction with thermal damage caused by joule heating. for good response to surgery it is crucial to produce minimum thermal damage in both tumoral and healthy tissues named non-thermal irreversible electroporation(ntire). non-thermal irrev...

Ashkan Nabavi Pelesaraei, Mohammad Bagher Dehpour Sajjad Shaker Koohi

This paper studies the modeling and optimization of energy use and greenhouse gas emissions of eggplant production using artificial neural network and multi-objective genetic algorithm in Guilan province of Iran. Results showed that the highest share of energy consumption belongs to diesel fuel (49.24%); followed by nitrogen (33.30%). The results indicated that a total energy input of 13910.67 ...

Ashkan Nabavi Pelesaraei, Mohammad Bagher Dehpour Sajjad Shaker Koohi

This paper studies the modeling and optimization of energy use and greenhouse gas emissions of eggplant production using artificial neural network and multi-objective genetic algorithm in Guilan province of Iran. Results showed that the highest share of energy consumption belongs to diesel fuel (49.24%); followed by nitrogen (33.30%). The results indicated that a total energy input of 13910.67 ...

Journal: :JDCTA 2010
Ali Hadian Mahdi Nasiri Behrouz Minaei-Bidgoli

Multi-Objective Genetic Algorithm (MOGA) is a new approach for association rule mining in the market-basket type databases. Finding the frequent itemsets is the most resource-consuming phase in association rule mining, and always does some extra comparisons against the whole database. This paper proposes a new algorithm, Cluster-Based MultiObjective Genetic Algorithm (CBMOGA) which optimizes th...

Journal: :Environmental Modelling and Software 2009
Kourosh Behzadian Zoran Kapelan Dragan A. Savic Abdollah Ardeshir

This paper presents a novel multi-objective genetic algorithm (MOGA) based on the NSGA-II algorithm, which uses metamodels to determine optimal sampling locations for installing pressure loggers in a water distribution system (WDS) when parameter uncertainty is considered. The new algorithm combines the multi-objective genetic algorithm with adaptive neural networks (MOGA–ANN) to locate pressur...

2013
Zhiyong Fan Quansen Sun Feng Ruan Yiguang Gong Zexuan Ji

In allusion to remove Racian noise while lessen the loss of details as low as possible, this paper proposed an filter algorithm which comprehensive utilize Multi-Objective Genetic Algorithm (MOGA) and Shearlet transform based on a Multi-scale Geometric Analysis (MGA) theory. First, it performs a wavelet multi-scale decomposition of image. Then, it builds target function in MOGA by several evalu...

2011
Indra Ganesan

Multi-label spatial classification based on association rules with multi objective genetic algorithms (MOGA) enriched by semi supervised learning is proposed in this paper. It is to deal with multiple class labels problem. In this paper we adapt problem transformation for the multi label classification. We use hybrid evolutionary algorithm for the optimization in the generation of spatial assoc...

Journal: :JASIST 2009
Antonio Gabriel López-Herrera Enrique Herrera-Viedma Francisco Herrera

In this article, our interest is focused on the automatic learning of Boolean queries in information retrieval systems (IRSs) by means of multi-objective evolutionary algorithms considering the classic performance criteria, precision and recall. We present a comparative study of four well-known, general-purpose, multi-objective evolutionary algorithms to learn Boolean queries in IRSs. These evo...

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