Search Results - (( using function search algorithm ) OR ( using vector problem algorithm ))
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1
Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems
Published 2012“…The proposed algorithm, which is called Vector Evaluated Gravitational Search Algorithm (VEGSA), uses a number of populations of particles. …”
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Performance Evaluation of Vector Evaluated Gravitational Search Algorithms Based on ZDT Test Functions
Published 2014“…This paper presents a performance evaluation of Vector Evaluated Gravitational Search Algorithm (VEGSA), namely VEGSA-I and VEGSA-II algorithms, for multi-objective optimization problems. …”
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3
Performance evaluation of vector evaluated gravitational search algorithm II
Published 2014“…This paper presents a performance evaluation of a novel Vector Evaluated Gravitational Search Algorithm II (VEGSAII) for multi-objective optimization problems. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters
Published 2013“…Ant Colony Optimization originally deals with discrete optimization problems. Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous in nature, the values wil have to be discretized.The discretization process will result in loss of some information and, hence, affects the classification accuracy and seeks time.This paper presents an algorithm to optimize Support Vector Machine parameters using Incremental continuous Ant Colony Optimization without the need to discretize continuous values.Eight datasets from UCI were used to evaluate the performance of the proposed algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.Experimental results of the proposed algorithm also show promising performance in terms of classification accuracy and size of features subset.…”
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Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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7
Crossover and mutation operators of real coded genetic algorithms for global optimization problems
Published 2016“…This study is primarily aimed at investigating two issues in genetic algorithm (GA) and one issue in conformational search (CS) problems. …”
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8
Named entity recognition using a new fuzzy support vector machine.
Published 2008“…Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…The data vectors are assigned to the closest cluster and correspondingly to the set, which contains this cluster and an algorithm based on a derivative-free method is applied to the solution of this problem. …”
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10
Quasi-Newton type method via weak secant equations for unconstrained optimization
Published 2021“…Numerical experiments are carried out using standard test problems and show that the proposed methods are superior to some existing conjugate gradient methods, in terms of iterations and function evaluations required to reach the optimal solutions. …”
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11
An enhanced minimum variance distortionless response beamformer techniques to reduce interference in array antenna system
Published 2017“…Metaheuristic optimization algorithms are used widely to solve many engineering problems. …”
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12
Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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13
Hierarchical fuzzy logic ranking function for Malay translated hadith information retrieval system / Shaiful Bakhtiar Rodzman
Published 2022“…The ranking function is a predictive algorithm that is used to establish a simple ordering of documents according to their relevance. …”
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14
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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15
Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian
Published 2009“…The application of orthogonal decomposition method using Householder transformation (refer to section 3.3) is used to solve the least-squares problem in power system state estimation. …”
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16
Protein Conformantional Search Using Bees Algorithm
Published 2008“…To this end, an energy function is used to calculate its energy and a conformational search algorithm is used to search the conformational search space to find the lowest free energy corformation.…”
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Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…The newly proposed algorithm was tested using a set of standard benchmark functions with different searching space and global optima placement. …”
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Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions
Published 2013“…The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. …”
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Enhancing the cuckoo search with levy flight through population estimation
Published 2016“…The algorithm is tested on five benchmark functions such as Ackley function, Griewank function, Rastrigin function, Rosenbrock function and Schwefel function. …”
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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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