Search Results - (( simulation optimization mining algorithm ) OR ( binary classification tree algorithm ))

Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

“…In this regard, this thesis proposes five FS methods for efficient EMG signals classification. The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization by Too, Jing Wei, Tee, Wei Hown, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

“…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
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Study Of EMG Feature Selection For Hand Motions Classification by Abdullah, Abdul Rahim, Mohd Saad, Norhashimah, Too, Jing Wei

“…Thus, this paper employs two recent feature selection methods namely competitive binary gray wolf optimizer (CBGWO) and modified binary tree growth algorithm (MBTGA) to evaluate the most informative EMG feature subset for efficient classification. …”
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Formulation of invariants for discrete orthogonal moments and image classification / Pee Chih Yang by Pee, Chih Yang

“…Discrete Tchebichef moments are selected as the implementation platform of the proposed algorithms.To evaluate the performance of invariant algorithms, empirical studies have been carried out on large set of binary images which consist of numbers, English letters, symbols, Chinese characters and objects like animals, trees and company logos under noiseless and noisy conditions. …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…Traditional machine learning algorithms, such as Decision Trees, Naive Bayes, Random Forest, Random Trees, Multi-Layer Perceptron, and Support Vector Machines, have been extensively applied to address these threats. …”
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Automatic Multi-Objective Clustering Algorithm Using Hybrid Particle Swarm Optimization With Simulated Annealing. by Abubaker, Ahmad Asad

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Optimal QoS aware multiple paths web service composition using heuristic algorithms and data mining techniques by Qtaish, Osama Kayed Taher

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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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Enhanced Adaptive Neuro-Fuzzy Inference System Classification Method for Intrusion Detection by Jia, Liu

“…Therefore, this binary tree cannot analyse complex features of mixed attributes and restricts the CART tree's deep-level feature recognition ability. …”
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Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data by Oyebayo, Olaniran Ridwan

“…These problems were extensively studied within the scope of classification (binary and multi-class) and regression (linear and survival). …”
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A Comparative Performance Analysis of Malware Detection Algorithms Based on Various Texture Features and Classifiers by Ahmed I.T., Hammad B.T., Jamil N.

An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Hui, Bian, Chiew, Kang Leng

“…This study investigates the performance of various conventional machine learning algorithms, including decision trees, naive Bayes, naive Bayes trees, random forest, random trees, MLP, and SVM, in detecting network intrusions using binary and multi-classification approaches. …”
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Pixel-based feature for android malware family classification using machine learning algorithms by Mohd Zamri, Osman, Rahiwan Nazar, Romli, Ahmad Firdaus, Zainal Abidin, Mohd Faaizie, Darmawan

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Prediction of cause of death from forensic autopsy reports using text classification techniques: A comparative study by Mujtaba, Ghulam, Shuib, Liyana, Raj, Ram Gopal, Rajandram, Retnagowri, Shaikh, Khairunisa

“…Finally, in text classification algorithms, support vector machine classifier outperforms random forest, Naive Bayes, k-nearest neighbor, decision tree, and ensemble-voted classifier. …”
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Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

“…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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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

“…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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Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method by Abbaszadeh M., Soltani-Mohammadi S., Ahmed A.N.

Behavior Recognition In Video Surveillance System For Indoor Public Areas Using Artificial Immune System by Abad, Azad

“…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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Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm by Mohd Kasihmuddin, Mohd Shareduwan, Abdul Halim, Nur Shahira, Mohd Jamaludin, Siti Zulaikha, Mansor, Mohd. Asyraf, Alway, Alyaa, Zamri, Nur Ezlin, Azhar, Siti Aishah, Marsani, Muhammad Fadhil

“…The simulation suggested that the proposed model outperformed the existing model in doing logic mining for the online shoppers dataset.…”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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