نتایج جستجو برای: moga
تعداد نتایج: 405 فیلتر نتایج به سال:
In current research, artificial neural network (ANN) and Multi objective genetic algorithm (MOGA) have been used for the prediction multi optimization of end milling operation. Cutting speed, feed rate, depth cut, material density hardness considered as input variables. The predicted values optimized results obtained through ANN MOGA are compared with experimental results. A good correlation ha...
Ankur Kumar, Rohit Bhatia and Pooja A Chawla* Author Affiliations Department of Pharmaceutical Chemistry, ISF College Pharmacy, India Received: July 01, 2022 | Published: 06, Corresponding author: Chawla, Chemistry Analysis, Moga-142001, Punjab, DOI: 10.26717/BJSTR.2022.45.007133
The efficient plan of site arrangement during the construction phase has been considered a vital duty to successful project performance due productivity enhancement as well safety in executions. optimization Construction Site Layout Problem (CSLP) is combinatorial complexity that regards numerous objectives and considerable growth scale increasing constraints facilities. rearrangement on may th...
Evolutionary Polynomial Regression (EPR) is a recently developed hybrid regression method that combines the best features of conventional numerical regression techniques with the genetic programming/symbolic regression technique. The original version of EPR works with formulae based on true or pseudo-polynomial expressions using a single-objective genetic algorithm. Therefore, to obtain a set o...
This paper examines the evolutionary approach for aircraft design optimization. Several niching and elitist models are first applied to Multiple-Objective Genetic Algorithms (MOGAs). Numerical results suggest that the combination of the fitness sharing and the best-N selection leads to the best performance. The resulting MOGA is then applied to multidisciplinary design optimization problems of ...
1Anca Ionel, 1Ondine Lucaciu, 1Minodora Moga, 1Dan Buhatel, 1Aranka Ilea, 2Flaviu Tabaran, 2Cornel Catoi, 3Cristian Berce, 3Septimiu Toader, 1Radu S. Campian 1 Department of Oral Reahabilitation, Oral Health and Dental Office Management, Faculty of Dentistry, “Iuliu Haţieganu” University of Medicine and Pharmacy, Cluj-Napoca, Romania; 2 Department of Anatomic Pathology, Necropsy and Forensic Me...
The design of an electrostatic electron optical system with five electrodes and two objective functions is optimized using multiobjective genetic algorithms (MOGAs) optimization. considered are minimum probe size the primary beam in a fixed image plane maximum secondary detection efficiency at in-lens detector plane. time-consuming step calculation potential. There methods to do this. first COM...
In this article a procedure to tune robust Generalized Predictive Controllers (GPC) is presented. To tune the controller parameters a multiobjective optimization problem is formulated so the designer can consider conflicting objectives simultaneously without establishing any prior preference. Moreover model uncertainty, represented by a list of possible models, is considered. The multiobjective...
An attempt has been made in this article to compare the performances of two multiobjective evolutionary algorithms namely ev-MOGA and GODLIKE. The performances of both are evaluated on risk based optimal power scheduling of virtual power plant. The risk based scheduling is proposed as a conflicting bi objective optimization problem with increased number of durations of day. Both the algorithms ...
The NBI-NLPQLP optimization method is tested on several multi-objective optimization problems. Its performance is compared to that of MOGA-II: since NBI-NLPQLP is based on the classical gradientbased NLPQLP, it is fast and accurate, but not as robust, in comparison with the genetic algorithm. Furthermore a discontinuous Pareto frontier can give rise to problems in the NBI’s convergence. In orde...
نمودار تعداد نتایج جستجو در هر سال
با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید