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A Step Forward in Studying the Compact Genetic Algorithm [article]

Reza Rastegar, Arash Hariri
2009 arXiv   pre-print
The compact Genetic Algorithm (cGA) is an Estimation of Distribution Algorithm that generates offspring population according to the estimated probabilistic model of the parent population instead of using  ...  This paper introduces a theoretical framework for studying the cGA from the convergence point of view in which, we model the cGA by a Markov process and approximate its behavior using an Ordinary Differential  ...  One of the simplest algorithms of the no dependencies model is the compact Genetic Algorithm (cGA).  ... 
arXiv:0901.0598v1 fatcat:rc7mvb6zyra2pkmiviuaug5gqi

A Step Forward in Studying the Compact Genetic Algorithm

Reza Rastegar, Arash Hariri
2006 Evolutionary Computation  
The compact Genetic Algorithm (cGA) is an Estimation of Distribution Algorithm that generates offspring population according to the estimated probabilistic model of the parent population instead of using  ...  This paper introduces a theoretical framework for studying the cGA from the convergence point of view in which, we model the cGA by a Markov process and approximate its behavior using an Ordinary Differential  ...  The other results can be easily obtained by (4) (Gonzalez et al., 2000) . 2 Analysis of the Compact Genetic Algorithm Under the algorithm specified by (1) , {p(k), k ≥ 0} is a Markov process.  ... 
doi:10.1162/evco.2006.14.3.277 pmid:16903794 fatcat:wloap7457fbo3bo7up7vx7psgy

An implementation of compact genetic algorithm on a quantum computer

Sorrachai Yingchareonthawornchai, Chatchawit Aporntewan, Prabhas Chongstitvatana
2012 2012 Ninth International Conference on Computer Science and Software Engineering (JCSSE)  
The simulation of quantum computing is carried out for solving a problem using the compact genetic algorithm.  ...  This work presents an example of programming a quantum computer. The compact genetic algorithm is used as a target as it is powerful and popular method in evolutionary computation.  ...  In a classical computer, the compact genetic algorithm represents the population as a probability distribution over the set of solutions by using a vector.  ... 
doi:10.1109/jcsse.2012.6261939 fatcat:kgd7ovngbfawrdqk7pxaztuvw4

Accelerating Wright-Fisher Forward Simulations on the Graphics Processing Unit [article]

David S. Lawrie
2016 bioRxiv   pre-print
The single-locus Wright-Fisher forward algorithm is, however, exceedingly parallelizable, with many steps which are so-called embarrassingly parallel, consisting of a vast number of individual computations  ...  Further, as many of the parallel programming techniques used in this simulation can be applied to other computationally intensive algorithms important in population genetics, GO Fish serves as an exciting  ...  In total, log 2 (8) = 3 time steps are required to reduce the example array. C) Compact is a multi-step algorithm that allows one to filter arrays on the GPU [18].  ... 
doi:10.1101/042622 fatcat:y3hno2y5kvembdduliqi6jhm5q

A Novel Handwritten Letter Recognizer Using Enhanced Evolutionary Neural Network [chapter]

Fariborz Mahmoudi, Mohsen Mirzashaeri, Ehsan Shahamatnia, Saed Faridnia
2009 Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering  
The computational results show that the neural network reaches very satisfying results with relatively scarce input data and a promising performance improvement in convergence of the hybrid evolutionary  ...  Evolutionary algorithm is used for the global search of the search space and the back-propagation algorithm is used for the local search.  ...  In this approach a customized genetic algorithm has been utilized in hybrid evolutionary feed-forward neural network which is responsible for searching entire search space while BP algorithms is responsible  ... 
doi:10.1007/978-3-642-02312-5_1 fatcat:iekzharacbgrziiahqpdqv5z2i

An Adaptive Hardware Classifier in FPGA based-on a Cellular Compact Genetic Algorithm and Block-based Neural Network

Yutana Jewajinda
2008 2008 International Symposium on Communications and Information Technologies  
The adaptive hardware is based-on evolvable block-based neural network (BBNN) and a cellular compact genetic algorithm (CCGA). The BBNN consists of a 2-D array of modular neuron.  ...  The implemented hardware demonstrates the completely intrinsic online evolution and adaptation in hardware without software running on microprocessors.  ...  The FPGA implementation of cellular compact genetic algorithm and BBNN layers are presented in Section V. Section VI describes XOR problem as a case study.  ... 
doi:10.1109/iscit.2008.4700275 fatcat:ryocdnofvvfttmi6rqj747epny

Integrating Gene Expression Programming and Geographic Information Systems for Solving a Multi Site Land Use Allocation Problem

Eldrandaly
2009 American Journal of Applied Sciences  
The feasibility of the proposed approach in solving MLUA problems was checked using a fictive case study.  ...  In this study a new approach for solving MLUA problems was proposed by integrating Gene Expression Programming (GEP) and GIS.  ...  , linear chromosomes of fixed length similar to the ones used in genetic algorithms and the ramified structures of different sizes and shapes similar to the parse trees of genetic programming.  ... 
doi:10.3844/ajassp.2009.1021.1027 fatcat:jthnljt6mzabtfx2vdmsncvu2q

Integrating Gene Expression Programming and Geographic Information Systems for Solving a Multi Site Land Use Allocation Problem

Khalid A. Eldrandaly
2009 American Journal of Applied Sciences  
The feasibility of the proposed approach in solving MLUA problems was checked using a fictive case study.  ...  In this study a new approach for solving MLUA problems was proposed by integrating Gene Expression Programming (GEP) and GIS.  ...  , linear chromosomes of fixed length similar to the ones used in genetic algorithms and the ramified structures of different sizes and shapes similar to the parse trees of genetic programming.  ... 
doi:10.3844/ajas.2009.1021.1027 fatcat:52wf7vy4ufccfcahuaxi3cohby

Perceptions of trophectoderm as a sentinel for embryo selection

David F. Albertini
2014 Journal of Assisted Reproduction and Genetics  
These prescient studies set a benchmark in the field for several reasons.  ...  Fast-forward 50 years with the ever-expanding use of time lapse microscopy, we take as commonplace such behaviors in the thousands of human embryos witnessed throughout the world on a daily basis.  ...  These prescient studies set a benchmark in the field for several reasons.  ... 
doi:10.1007/s10815-014-0384-z pmid:25384845 pmcid:PMC4389950 fatcat:x5ejnmng3rdrnpv5mdjjtp6bza

Multi-modulus algorithm based on global artificial fish swarm intelligent optimization of DNA encoding sequences

Y.C. Guo, H. Wang, H.P. Wu, M.Q. Zhang
2015 Genetics and Molecular Research  
speed and smaller MSE in comparison with the CMA, the MMA, and the AFS-DNA-MMA.  ...  Conflicts of interest The authors declare no conflict of interest. ACKNOWLEDGMENTS  ...  If it cannot reach the forward movement condition, it randomly moves a step forward according to Equation 4. Figure 1 . 1 Principle of the multi-modulus algorithm (MMA).  ... 
doi:10.4238/2015.december.21.23 pmid:26782395 fatcat:hxzpo2osbfdkllkntyrdnzek6u

FPGA implementation of a cellular univariate estimation of distribution algorithm and block-based neural network as an evolvable hardware

Yutana Jewajinda, Prabhas Chongstitvatana
2008 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence)  
This paper pr esents a har dwar e implementation of evolvable block-based neur al networ k (BBNN) amd a kind of EDAs called cellular compact genetic algor ithm (CCGA) in FPGA.  ...  In addition, the pr oposed CCGA efficiently solves the scalable issues by scaling up to the size of BBNN. The pr esented appr oach demonstr ates a new kind of evolvable har dwar e.  ...  The FPGA implementation of cellular compact genetic algorithm and BBNN layers are presented in Section V. Section VI describes XOR problem as a case study.  ... 
doi:10.1109/cec.2008.4631253 dblp:conf/cec/JewajindaC08 fatcat:vimctkflvzhrzpnkdzcx7owjuu

Genetic Algorithm-Based Design and Simulation of Manufacturing Flow Shop Scheduling

W. Chen, Y. F. Hao
2018 International Journal of Simulation Modelling  
This paper applies the non-dominated sorting genetic algorithm (NSGA) to the design of non-compact flow shop scheduling plan, and successfully solves the multi-objective optimization problem considering  ...  Specifically, an NSGA-based scheduling strategy was developed after analysing the features of the non-compact flow shop in manufacturing enterprises, and an improved algorithm was created for the multi-objective  ...  ACKNOWLEDGEMENTS The authors acknowledge funding from the National Social Science Foundation of China (Project No. 18CGL003), as well as the contributions from all partners of the mentioned projects.  ... 
doi:10.2507/ijsimm17(4)co17 fatcat:5mxpcwzzv5ardn3hht4s2lugl4

The compact Genetic Algorithm for likelihood estimator of first order moving average model

Rawaa Dawoud Al-Dabbagh, Mohd. Sapiyan Baba, Saad Mekhilef, Azeddien Kinsheel
2012 2012 Second International Conference on Digital Information and Communication Technology and it's Applications (DICTAP)  
In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1).  ...  One such class of these algorithms is compact Genetic Algorithm (cGA), it dramatically reduces the number of bits reqyuired to store the poulation and has a faster convergence speed.  ...  THE COMPACT GENETIC ALGORITHM (cGA) The compact Genetic Algorithm (cGA) is similar to the PBIL (population Based Incremental Learning) but requires fewer steps, fewer parameters and less of a gene sample  ... 
doi:10.1109/dictap.2012.6215410 dblp:conf/dictap/Al-DabbaghBMK12 fatcat:kd4sil2govbvfp5n6nhzdu4ywm

Electric potential source localization reveals a borehole leak during hydraulic fracturing

A. K. Haas, A. Revil, M. Karaoulis, L. Frash, J. Hampton, M. Gutierrez, M. Mooney
2013 Geophysics  
in the electric potential distribution and (2) using a genetic algorithm to refine the position of the source current density on a denser grid.  ...  These self-potential data were inverted in two steps: (1) using a deterministic least-square algorithm with focusing to retrieve the position of the source current density in the block for a given snapshot  ...  ACKNOWLEDGMENTS We thank NSF for funding the SmartGeo Educational Program  ... 
doi:10.1190/geo2012-0388.1 fatcat:3cxz7sbmwvabxn45efc65oip3u

Semi-Active LQG Control of Seismically Excited Nonlinear Buildings using Optimal Takagi-Sugeno Inverse Model of MR Dampers

Mohsen Askari, Jianchun Li, Bijan Samali
2011 Procedia Engineering  
The designed semi-active system is compared with the performances of active control as well as clipped optimal control (COC) systems, which are based on the same nominal controller as is used in this study  ...  The proposed T-S fuzzy inverse model of dampers is derived using subtractive clustering, non-dominated sorting genetic algorithm II (NSGAII) and adaptive neuro-fuzzy inference systems (ANFIS).  ...  Following this idea, an optimal compact T-S inverse model of MR damper has been obtained using Subtractive Clustering and Non-Dominated Sorting Genetic Algorithm II and discussed here.  ... 
doi:10.1016/j.proeng.2011.07.348 fatcat:3njhkmuxjbeg7ddhovla4xlyzy
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