Search Results - (( evolution optimization parallel algorithm ) OR ( label classification based algorithm ))
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The advantage of the cluster labelling algorithm compared to co-spectral plot and maximum-likelihood classifier was the algorithm provided a rapid production of high accuracy classification map.…”
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Multi-label learning based on positive label correlations using predictive apriori
Published 2019“…Multi-label Learning (MLL) is a general task in data mining that consists of three main tasks: classification, label ranking, and multi-label ranking. …”
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Multi label ranking based on positive pairwise correlations among labels
Published 2020“…The first objective is to propose a new multi-label ranking algorithm based on the positive pairwise correlations among labels, while the second objective aims to propose new simple PTMs that are based on labels correlations, and not based on labels frequency as in conventional PTMs. …”
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Nearest neighbour group-based classification
Published 2010“…In this paper, we extend three variants of the nearest neighbour algorithm to develop a number of non-parametric group-based classification techniques. …”
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Optimization of extractive Automatic Text Summarization using Decomposition-based Multi-objective Differential Evolution and parallelization
Published 2024“…The central challenge in Automatic Text Summarization (ATS) is efficiently generating machine-generated text summaries through optimization algorithms, a critical component for systems dealing with textual information processing. …”
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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…Classification is a process of grouping or placing data into appropriate categories or classes based on specificattributes or features to predict labels or classes of new data based on patternsobserved from previously trained data. …”
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Knowledge base processing method based on text classification algorithm
Published 2023“…The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…To evaluate the PMT’s performance and adaptability, the PMT was applied to four contemporary metaheuristic algorithms, Differential Evolution, Particle Swarm Optimization, Simulated Annealing, and Whale Optimization Algorithm, to solve 15 well-known benchmark functions as well as 2 real world problems based on the welded beam design and pressure vessel design. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Samples in the same cluster have the same label. The aim of data classification is to set up rules for the classification of some observations that the classes of data are supposed to be known. …”
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Hyper-heuristic framework for sequential semi-supervised classification based on core clustering
Published 2020“…This article presents a prominent framework that integrates each of the NN, a meta-heuristic based on evolutionary genetic algorithm (GA) and a core online-offline clustering (Core). …”
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PMT: opposition-based learning technique for enhancing meta-heuristic performance
Published 2019“…To evaluate the PMT's performance and adaptability, the PMT has been applied to four contemporary meta-heuristic algorithms, differential evolution (DE), particle swarm optimization (PSO), simulated annealing (SA), and whale optimization algorithm (WOA), to solve 15 well-known benchmark functions. …”
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OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM
Published 2011“…In this thesis, a new optimization GA-based algorithm that emanates from modification of conventional GA to reduce the iterations number and the duration time, namely, semi-parallel operation genetic algorithm (SPOGA) is proposed. …”
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Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling
Published 2018“…Furthermore, there is tendency that multi label classifications used instead of traditional single label classification technique. …”
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Semantic shot classification in soccer videos via playfield ratio and object size considerations.
Published 2013“…This paper presents a semantic shot classification algorithm for soccer videos. Generally, each shot within a match video is assigned either a far or close up-view class label. …”
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Application Of Genetic Algorithms For Robust Parameter Optimization
Published 2010“…Genetic algorithms (GA) are fairly recent in this respect but afford a novel method of parameter optimization. …”
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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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An enhanced feature selection technique for classification of group based holy Quran verses
Published 2018“…The proposed FS technique is a combination of filter-based information gain (IG) and wrapper-based CFS algorithms. …”
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