Search Results - (( parallel optimization path algorithm ) OR ( process classification problem algorithm ))
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Tool path generation of contour parallel based on ant colony optimisation
Published 2016“…An Ant Colony Optimisation (ACO) method is used to optimize the tool path length because of its capability to find the shortest tool path length. …”
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Minimizing machining airtime motion with an ant colony algorithm
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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection
Published 2015“…Subsequently, the integration of embedded correlation-based filtering algorithm has further increased the classification accuracy of training process and testing process by 4.93% and 14.73% respectively. …”
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to create parameters, there are many problems arise in the process of fuzzy modeling. The problems are data incomplete and the size of the data is large. …”
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Undergraduates Project Papers -
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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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Diagnosis of eyesight using Improved Clonal Selection Algorithm (ICLONALG) / Nor Khirda Masri
Published 2017“…This study aims to implement the classification algorithm using the Improved Clonal Selection Algorithm (ICLONALG) to classify the eyesight’s problems. …”
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Overview of metaheuristic: classification of population and trajectory
Published 2010“…Some algorithms can be defined if the developer of the system has problem specific knowledge to the solution. …”
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Monograph -
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Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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WCBP: A new water cycle based back propagation algorithm for data classification
Published 2016“…The performance of the proposed Water Cycle based Back-Propagation (WCBP) algorithm is compared with the conventional BPNN, ABC-BP and ABC-LM algorithms on selected benchmark classification problems from UCI Machine Learning Repository. …”
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Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib
Published 2019“…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…One of the most powerful machine learning methods to handle classification problems is the decision tree. There are various decision tree algorithms, but the most commonly used are Iterative Dichotomiser 3 (ID3), CART, and C4.5. …”
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Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems
Published 2015“…The outcome positively demonstrates that the hybrid algorithm is able to improve the classification performance with a smaller number of hidden nodes and is effective in multiclass classifi cation problems.Furthermore, the results indicate that the proposed hybrid method is a potentially useful classifi er for enhancing the classification process ability when compared with the multiobjective genetic algorithm based on the TBP network (MOGATBP) and certain other methods found in the literature.…”
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Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems
Published 2015“…The outcome positively demonstrates that the hybrid algorithm is able to improve the classification performance with a smaller number of hidden nodes and is effective in multiclass classifi cation problems. …”
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
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Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems
Published 2011“…We use two common benchmark classification problems to illustrate the improvement in convergence time.…”
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Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification
Published 2015“…Specifically, some selected benchmark classification problems are used. The simulation results show that the computational efficiency of ERN and BPERN training process is highly enhanced when coupled with the proposed hybrid method.…”
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An enhancement of classification technique based on rough set theory for intrusion detection system application
Published 2019“…In order to improve classification performance problem, feature selection and discretization algorithm are crucial in selecting relevant attributes that could improve classification performance. …”
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New Instances Classification Framework On Quran Ontology Applied To Question Answering System
Published 2019“…As a result, the instances classification framework consists of several essential components: pre-processing, morphology analysis, semantic analysis, feature extraction, instances classification with Radial Basis Function Networks algorithm, and the transformation module. …”
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