Search Results - (( peer extraction method algorithm ) OR ( pattern optimization method algorithm ))

Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

“…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling by Rayner Alfred, Loo Yew Jie, Joe Henry Obit, Yuto Lim, Haviluddin Haviluddin, Azreen Azman

“…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
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Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin by Shamsudin, Farah Syadiyah

“…Therefore, the aim for this project is to develop a new approach in the fingerprint verification system by applying Clonal Selection Algorithm (CSA) that is known to be good in pattern matching and optimization of problems. …”
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Data mining using genetic algorithm in finance data / A. Noor Latiffah and A. B. Nordin by Latiffah, A. Noor, Nordin, A. B.

“…This project, wilt extract some useful financial knowledge from the Syariah Index data of Kuala Lumpur Syariah Index (KLSI). The methods that wilt be applied are conventional statistical methods Markowitz Optimization as well as evolutionary programming (EP) utilizing genetic algorithms. …”
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Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

“…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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Clustering of rainfall data using k-means algorithm by Mohd Sham, Mohamad, Yuhani, Yusof, Ku Muhammad Na’im, Ku Khalif, Mohd Khairul Bazli, Mohd Aziz

“…K-Means algorithm is used to obtain optimal rainfall clusters. …”
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Development of a scaled conjugate gradient algorithm for significant RF neural signal processing by Mohd Norden, Muhammad Farid Akmal, Mohd Isa, Roshakimah, Mohd Isa, Mohd Roshalizi, S. Abdul Kadir, Ros Shilawani, Md Azli, Muhammad Hariz, Muhammad Akram, Amir Syarif

“…Artificial Neural Networks (ANN) are computational models inspired by the human brain, capable of recognizing patterns and making predictions. Scale Conjugate Gradient (SCG) algorithm is an efficient training method for ANN that accelerates the learning process and improves output accuracy. …”
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An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…However, these algorithms often fall short in consistently detecting and classifying network intrusions, particularly when distinctions between classes are subtle or when facing evolving attack patterns. …”
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Image watermarking optimization algorithms in transform domains and feature regions by Tao, Hai

“…A series of training patterns are constructed by employing between two images.Moreover,the work takes accomplishing maximum robustness and transparency into consideration.HPSO method is used to estimate the multiple parameters involved in the model. …”
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Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti by Abd Mukti, Shahrul Nizan

“…Three (3) chequerboards were used in camera calibration to find an optimal camera parameter. 50mm size of chequerboard pattern yielded the lowest pre-projection error while there’s no guaranteed in having better projection by increased the focal length of the camera. …”
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

“…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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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

“…Apart from that, having low values in four of the performance criteria: RMSE, MAE, NSE, and RSR, have further strengthened the credibility of the results. As for the optimization process, the reservoir operation rule was derived using a meta-heuristic algorithm at the monthly interval. …”
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Investigating optimal smartphone placement for identifying stairs movement using machine learning by Muhammad Ruhul Amin, Shourov, Husman, Muhammad Afif, Toha, Siti Fauziah, Jasni, Farahiyah

“…Accurate identification of human activities is crucial in conveying essential gait information to users for the recognition of human movement activities. However, gait patterns can vary significantly between individuals, making it challenging to develop a generalized algorithm for identifying incline surface human activity. …”
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

“…The proposed segmentation is evaluated on real-world clinical data using publicly accessible benchmark clinical liver datasets containing one of the highest numbers of tumors and pathological livers utilized for liver tumor and vasculature segmentation. The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment by Sojodishijani, Omid

“…In the case of real datasets, the proposed method yields 12.16% average misclassification error while the average misclassification error for five different methods GAM, TSY, NWKNN, DWM and FISH is 19.54%. …”
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P300 detection of brain signals using a combination of wavelet transform techniques by Motlagh, Farid Esmaeili

“…Meanwhile the new approaches in channels selection methods help the algorithms for convenient online usage.…”
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Feature extraction and classification stage on facial expression : A review by Shidiq, Muchamad Bachram, Ernawan, Ferda, Khubrani, Mousa Mohammed, Nugroho, Fajar Agung

“…This review will compare two kinds of extract features methods and one classification method. The first technique of extracting features is the optimization technique using the K-Mean algorithm, which helps to increase recognition accuracy. …”
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A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams by Immad , Shams

“…In terms of controller-based, in this work, a new global maximum power point tracking (GMPPT) algorithm based on a modified butterfly optimization algorithm (MBOA) has been proposed. …”
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Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

“…On the other hand, when we use computers to reduce uncertainty, the computer itself can become an expert in a specific field through a variety of methods. One such method is machine learning, which involves computer algorithm to capture hidden knowledge from data. …”
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