Search Results - (( evolution optimization steam algorithm ) OR ( binary classification rules algorithm ))
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1
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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2
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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3
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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4
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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5
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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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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7
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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8
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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10
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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11
Decision-Level Fusion Scheme For Nasopharyngeal Carcinoma Identification Using Machine Learning Techniques
Published 2020“…We have implemented the fusion of the three image texture-based schemes (local binary patterns, the first-order statistics histogram properties, and histogram of gray scale) at the decision level and tested the performance of this scheme using the same experimental setup in the previous section for simple scorelevel fusion, but for comparison, We used the classifiers methods which are support vector machines (SVM), k-nearest neighbors’ algorithm, and artificial neural network (ANN). …”
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A study on component-based technology for development of complex bioinformatics software
Published 2004“…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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