Search Results - (( using function _ algorithm ) OR ( sequence optimization window algorithm ))
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1
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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2
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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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 second technique is to solve bi-objective functions by using the BOBAT algorithm. The third technique is an integration of BOGSA with BOBAT to produce a BOGSBAT algorithm. …”
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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“…Next, the Dynamic Demand Replacement Algorithm (DDRA) algorithm is used to place in-demand functions near the edge nodes periodically, while the proposed task scheduling algorithm - Maximum Revenue Bid (MRB) is used to give priority to tasks to maximise revenue near the edge. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network
Published 2024journal::journal article -
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Transform of Artificial Immune System algorithm optimization based on mathematical test function
Published 2023Conference Paper -
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An efficient method for determining all the extreme points of function with one variable
Published 2014“…The algorithm is the combination of the filled function's algorithm and Inner Iteration algorithm, called IRH's algorithm, in which Inner Iteration algorithm works at the domain which is usually ignored by filled function's algorithm.…”
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11
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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12
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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13
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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14
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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15
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Design and implementation of MD5 hash function algorithm using verilog HDL
Published 2022“…Among hash algorithms, MD5 is the most used hash function algorithm. …”
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Computing the autopilot control algorithm using predictive functional control for unstable model
Published 2009“…This paper discusses the computing development of a control algorithm using Predictive Functional Control (PFC) for model-based that having one or more unstable poles. …”
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Determining the preprocessing clustering algorithm in radial basis function neural network
Published 2008“…Radial Basis Function Networks have been widely used to approximate and classify data. …”
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Design and Implementation of MDS Hash Function Algorithm Using Verilog HDL
Published 2020“…Among hash algorithms, MD5 is the most used hash function algorithm. …”
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A video-rate color image segmentation using adaptive and statistical membership function
Published 2010“…In this algorithm, statistical information of regions is used to create fuzzy membership functions in color model components. …”
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