Search Results - (( code classification system algorithm ) OR ( parallel classification learning algorithm ))
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The forecasting of poverty using the ensemble learning classification methods
Published 2023“…This research was conducted to forecast poverty using classification methods. Random Forest and Extreme Gradient Boosting (XGBoost) algorithms were applied to forecast poverty since they are supervised learning algorithms that use the ensemble learning approach for classification. …”
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Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms
Published 2015“…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living
Published 2024“…In this view, this research develops an arithmetic optimization algorithm with deep learning based tweets classification (AOADL-TC) approach for sustainable living. …”
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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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Combining deep and handcrafted image features for MRI brain scan classification
Published 2019“…In this paper, a deep learning feature extraction algorithm is proposed to extract the relevant features from MRI brain scans. …”
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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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Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach
Published 2023“…Aerial photography; Aircraft detection; Antennas; Codes (symbols); Discrete cosine transforms; Discrete wavelet transforms; Glossaries; Image classification; Image coding; Image enhancement; Learning algorithms; Learning systems; Object recognition; Remote sensing; Satellite imagery; Satellites; Unmanned aerial vehicles (UAV); Discrete tchebichef transforms; Discriminative features; Finite Ridgelet Transform; Histogram of oriented gradients; Image processing and computer vision; Scale invariant feature transforms; SIFT; Sparse coding; Classification (of information)…”
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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…The incorporation of a single parallel hidden layer feed-forward neural network to the Fast Learning Network (FLN) architecture gave rise to the improved Extreme Learning Machine (ELM). …”
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Maldroid- attribute selection analysis for malware classification
Published 2019“…Hence, the objective of this paper is to find the most effective and efficient attribute selection and classification algorithm in malware detection. Moreover, in order to get the best combination between attribute selection and classification algorithm, eight attributes selection and seven categories machine learning algorithm are applied in this study. …”
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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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Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition
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Object-Oriented Programming semantics representation utilizing agents
Published 2011“…The algorithm requires source codes comparison based on keyword similarity to extract the words that exist in the two related source codes. …”
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The development of virtual product life cycle design tool using artificial intelligence technique
Published 2008“…The generated features from code classification algorithm give the information of machining parameter through the mapping algorithm. …”
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POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD
Published 2012“…The performance of the classification system would be greatly degraded. To overcome this difficulty and to improve the performance of the system, a de-noising scheme is proposed to be used together with the system. …”
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Classification of metamorphic virus using n-grams signatures
Published 2020“…Metamorphic virus has a capability to change, translate, and rewrite its own code once infected the system to bypass detection. …”
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