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1
Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
Published 2011“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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Recognizing complex human activities using hybrid feature selections based on an accelerometer sensor
Published 2017“…Wearable sensor technology is evolving in parallel with the demand for human activity monitoring applications. …”
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3
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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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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5
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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10
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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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
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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An efficient computation technique for cryptosystems based on Lucas functions
Published 2008“…In this paper, we are presenting a new and efficient computations algorithm for LUC Cryptosystems. We have found that the binary sequence used in a new algorithm is shorter than a special sequence used in an existing algorithm. …”
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