نتایج جستجو برای: Genetic algorithm

تعداد نتایج: 1224125  

Alireza rezaee,

In this paper, echo cancellation is done using genetic algorithm (GA). The genetic algorithm is implemented by two kinds of crossovers; heuristic and microbial. A new procedure is proposed to estimate the coefficients of adaptive filters used in echo cancellation with combination of the GA with Least-Mean-Square (LMS) method. The results are compared for various values of LMS step size and diff...

Journal: :Jurnal Sisfokom (Sistem Informasi dan Komputer) 2020
Muhammad EzarAl Rivan, BhagaskaraBhagaskara,

Journal: :Transactions of the Society of Instrument and Control Engineers 1999
KotaroHIRASAWA, YasutakaISHIKAWA, JingluHU, JunichiMURATA,

Journal: :Russian Technological Journal 2020
M. A.Anfyorov,

Journal: :International Journal of Future Generation Communication and Networking 2015
YanhuaChen,

Journal: :International Journal of Computer Applications 2014
JyotiSharma, RaviShankar Singhal,

Ahmad Reza Tahanian, Maryam Khaleghi,

This paper describes a Genetic Algorithms approach to amanpower-scheduling problem arising at a Petrochemical Company. AlthoughGenetic Algorithms have been successfully used for similar problemsin the past, they always had to overcome the limitations of theclassical Genetic Algorithms paradigm in handling the conflict betweenobjectives and constraints. The approach taken here is to use an indir...

K. N. Nandurkar, , K. V. Chandratre, ,

In today’s economy, manufacturing plants must be able to operate efficiently and respond quickly to changes in the product mix and demand.[1] Layout design has a significant impact on manufacturing efficiency. Initially, it was treated as a static decision but due to improvements in technology, it is possible to rearrange the manufacturing facilities in different scenarios. The Plant layout...

Journal: :Int. Arab J. Inf. Technol. 2015
Mohammad Javidi, Roghiyeh Hosseinpour Fard,

Today the Genetic Algorithm (GA) is used to solve a large variety of complex nonlinear optimization problems. However, permute convergence which is one of the most important disadvantages in GA is known to increase the number of iterations for reaching a global optimum. This paper, presents a new GA based on chaotic systems to overcome this shortcoming,. We employ logistic map and tent map as t...

Journal: :Computer 1994
J.L.Ribeiro Filho, P.C.Treleaven, C.Alippi,

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