Search Results - (( data using optimization algorithm ) OR ( binary classification rules algorithm ))
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1
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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2
An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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3
Logic mining method via hybrid discrete hopfield neural network
Published 2025“…Despite the success, the limitations of existing logic mining methods are often overlooked, hindering the search for optimal solutions in binary classification tasks. …”
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4
Genetic algorithm fuzzy logic for medical knowledge-based pattern classification
Published 2018“…This research proposed an algorithm named Genetic Algorithm Fuzzy Logic (GAFL) with Pittsburg approach for rules learning and induction in genetic fuzzy system knowledge discovery. …”
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Text Extraction Algorithm for Web Text Classification
Published 2010“…This study provides a text extraction algorithm for web text classification. The extraction algorithm consists of three phases namely web page extraction, rule formulation, and algorithm validation. …”
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6
Genetic algorithm fuzzy logic for medical knowledge-based pattern classification
Published 2023“…This research proposed an algorithm named Genetic Algorithm Fuzzy Logic (GAFL) with Pittsburg approach for rules learning and induction in genetic fuzzy system knowledge discovery. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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8
A study on component-based technology for development of complex bioinformatics software
Published 2004“…Othman present a comprehensive method based on two-layer multiclass classifiers. The first layer is used to detect up to superfamily and family in SCOP hierarchy, by using optimized binary SVM classification rules directly to ROC-Area. …”
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Overview of biomedical relations extraction using hybrid rule-based approaches.
Published 2013“…However, each of them was implemented in three major types of techniques separately i.e.co-occurrence,kernel based and rule based methods. There are many variants of these algorithms have been developed but the combination of it has not been verified yet. …”
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10
Behavior Recognition In Video Surveillance System For Indoor Public Areas Using Artificial Immune System
Published 2008“…Also, the robust algorithm with hands of artificial immune system rules like binary hamming shape-space and advance detector structure with fast decision making to detect three abnormal behaviors such as entering the forbidden area, standing more than threshold and running was implemented The result obtained showed the improvement in the duration for each phase when compared with previous methods in image segmentation like mixture of Gaussian and behavior recognition like and/Or tree or neural networks.…”
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11
Named entity recognition using a new fuzzy support vector machine.
Published 2008“…The design of our method is a kind of One-Against-All multi classification technique to solve the traditional binary classifier in SVM.…”
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Enhanced Adaptive Neuro-Fuzzy Inference System Classification Method for Intrusion Detection
Published 2024“…Additionally, standard deviation and proposed adaptive K-means algorithms have been employed to minimize the generated rules by ANFIS from the proposed hybrid models. …”
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13
Clustering chemical data set using particle swarm optimization based algorithm
Published 2008“…We found that PSO algorithm reveals better performance than Ward’s algorithm on continuous data format; however for binary data format, Ward’s algorithm outperforms arrogantly.…”
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14
VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). GA is a widely used optimization algorithm based on the concept of survival of the fittest. …”
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15
Human health status IoT device using data optimization algorithm / Albin Lemuel Kushan ... [et al.]
Published 2021“…This project aims to produce a device that can be used to identify the current health status of a person using sensor and a data optimization algorithm. …”
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16
A near-optimal centroids initialization in K-means algorithm using bees algorithm
Published 2009“…This creates problem for novice users especially to those who have no or little knowledge on the data.Trial-error attempt might be one of the possible preference to deal with this issue.In this paper, an optimization algorithm inspired from the bees foraging activities is used to locate near-optimal centroid of a given data set.Result shows that propose approached prove it robustness and competence in finding a near optimal centroid on both synthetic and real data sets.…”
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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18
Ant colony optimization for rule induction with simulated annealing for terms selection
Published 2012“…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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Development of decentralized data fusion algorithm with optimized kalman filter.
Published 2016“…The model collaborates data fusion technology with algorithm engineering domain, accordingly data fusion algorithm is optimized using sophisticated technique such as functional programming to reduce the processing delay and memory usage. …”
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20
Data fitting by G1 rational cubic Be´zier curves using harmony search
Published 2015“…HS is suitable for multivariate non-linear optimization problem. It is mainly achieved by data fitting using rational cubic Be´ zier curves with G1 continuity for every joint of segments of the whole data sets. …”
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