Search Results - (( using function based algorithm ) OR ( sequence optimization window algorithm ))
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1
Ensemble learning using multi-objective optimisation for arabic handwritten words
Published 2021“…In this thesis, new type of feature for handwriting using Segments Interpolation (SI) to find the best fitting line in each of the windows with a model for finding the best operating point window size for SI features. …”
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2
Examining the round trip time and packet length effect on window size by using the Cuckoo search algorithm
Published 2016“…This signifies that the training was successful based on the fitted values of the window size. Thus the proposed model trained with the CS algorithm provides a high convergence rate to the true global minimum and a better optimal solution. …”
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3
Comparative Analysis Using Bayesian Approach To Neural Network Of Translational Initiation Sites In Alternative Polymorphic Contex
Published 2012“…The objectives of this paper are to develop useful algorithms and to build a new classification model for the case study.The first approach of neural network includes training on algorithms of Resilient Backpropagation,Scaled Conjugate Gradient Backpropagation and Levenberg-Marquardt.The outputs are used in comparison with Bayesian Neural Network for efficiency comparison.The results showed that Resilient Backpropagation have the consistency in all measurement but performs less in accuracy.In second approach,the Bayesian Classifier_01 outperforms the Resilient Backpropagation by successfully increasing the overall prediction accuracy by 16.0%.The Bayesian Classifier_02 is built to improve the accuracy by adding new features of chemical properties as selected by the Information Gain Ratio method,and increasing the length of the window sequence to 201.The result shows that the built model successfully increases the accuracy by 96.0%.In comparison,the Bayesian model outperforms Tikole and Sankararamakrishnan (2008) by increasing the sensitivity by 10% and specificity by 26%. …”
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4
Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…The BOGS-BAT algorithm is based on three techniques. The first technique is to move or switch solution from single function to functions that contain more than one objective functions. …”
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5
A block cipher based on genetic algorithm
Published 2016“…In many algorithms which are based on the genetic algorithm approach, diffusion properties using crossover and mutation function are being generated to produce a secure data transmission. …”
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6
FaaSBid: an auction-based model for Function as a Service in edge-fog environments using unallocated resources
Published 2026“…To initialise function placement, Fitness-Based Swap (FBSW) algorithm is proposed which places functions based on pre-defined information such as function size, function maximum execution time, and storage cost. …”
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7
Computation of cryptosystem based on Lucas functions using addition chain
Published 2010“…Cryptosystem based on Lucas Functions is known as LUC Cryptosystem. …”
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8
An improved fast scanning algorithm based on distance measure and threshold function in region image segmentation
Published 2016“…Hence, this study proposes an Improved Fast Scanning algorithm that is based on Sorensen distance measure and adaptive threshold function. …”
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9
Enhancing speed performance of the cryptographic algorithm based on the lucas sequence
Published 2003“…Utilizing the properties of Lucas functions introduced a public key system based on Lucas functions instead of exponentiation, which offer a good alternative to the most publicly used exponential public key system RSA. …”
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10
Image encryption algorithm based on chaotic mapping
Published 2003“…HVT function is based on a two-dimensional chaotic map that utilized Baker’s map algorithm. …”
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11
An efficient computation technique for cryptosystems based on Lucas functions
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12
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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13
Biological-based semi-supervised clustering algorithm to improve gene function prediction
Published 2011“…However, commonclustering algorithms do not provide a comprehensive approach that look into the three categories of annotations; biologicalprocess, molecular function, and cellular component, and were not tested with different functional annotation database formats.Furthermore, the traditional clustering algorithms use random initialization which causes inconsistent cluster generation and areunable to determine the number of clusters involved. …”
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14
Enhancing Harmony Search Parameters Based On Step And Linear Function For Bus Driver Scheduling And Rostering Problems
Published 2018“…Therefore,it is of great interest that we find adjustments for these parameters in this research.There are two contributions to this research.The first one is having HMCR parameter using step function and the linear increase function while the second is applying the fret spacing concept on guitars that is associated with mathematical formulae is also applied in the BW parameter.There are three proposed models on the alteration of HMCR parameters based on the use of the fundamental step function;namely,the constant interval of step function, and its dynamic increase and decrease interval functions.The experimental results revealed that our proposed approach is superior to other state of the art harmony searches either in specific or generic cases. …”
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15
A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System
Published 2020“…Then, the histogram distance function for each location is computed using a pseudo-probability combination of novel histogram distance functions on a clustered histogram. …”
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16
Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy
Published 2014“…This algorithm is used to obtain the best solution or best fitness value from the initial random threshold values, and to evaluate the quality of a solution, correlation function is used. …”
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17
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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18
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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19
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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20
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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