Search Results - (( text classification problem algorithm ) OR ( simulation optimization using algorithm ))
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…In the first proposed algorithm, SA is used to optimize the rule's discovery activity by an ant. …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification
Published 2016“…Thus, this study investigates the use of Bat algorithm along with back-propagation neural network (BPNN) algorithm in-order to gain optimal weights to solve the local minima problem and also to enhance the convergence rate. …”
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WCBP: A new water cycle based back propagation algorithm for data classification
Published 2016“…Water Cycle algorithm is a modern nature inspired meta-heuristic algorithm to provide derivative-free solution to optimize complex problems. …”
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An improved bat algorithm with artificial neural networks for classification problems
Published 2016“…Metaheuristic search algorithms have been used for quite a while to optimally solve complex searching problems with ease. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Simulated Kalman filter (SKF) algorithm is one of the algorithms under this classification. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Second, an Optimized time sliding window packet marker (OTSWTCM) algorithm. …”
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A new ant based rule extraction algorithm for web classification
Published 2011“…Using Classifier-based attribute subset selection will reduce more attributes, but sacrifice the performance of the classifier.A hybrid ant colony optimization with simulated annealing algorithm to discover rules from data is proposed.The simulated annealing technique will minimize the problem of low quality discovered rule by an ant in a colony.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The rule set is arranged in decreasing order of generation.Thirteen data sets which consist of discrete and continuous data were used to evaluate the performance of the proposed algorithm in terms of accuracy, number of rules and number of terms in the rules.Experimental results obtained from the proposed algorithm are comparable to the results of the Ant-Miner algorithm in terms of rule accuracy but are better in terms of rule simplicity.…”
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New modified controlled bat algorithm for numerical optimization problem
Published 2022“…Bat algorithm (BA) is an eminent meta-heuristic algorithm that has been widely used to solve diverse kinds of optimization problems. …”
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Case study : an effect of noise in character recognition system using neural network
Published 2003“…The aim of this project is to develop a network that is able to recognize various inputs through a series of simulation using Neural Network simulator called MATLAB. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…The second test evaluates IFS in a controlled study using simulated datasets. Moreover, the third test used ten natural domain datasets obtained from UCI Repository, in about fifteen different experiments, using three to four different Machine Learning Algorithms for performance evaluation. …”
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Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar
Published 2015“…The objectives of this project are to use FCM as the clustering algorithm to establish TLPs. …”
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Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
Published 2018“…These weights are in turn used to develop new impurity functions for selecting optimal splits for each tree in a forest. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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