Search Results - (( parallel optimization sensor algorithm ) OR ( data distributed learning algorithm ))

Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

“…Stereo vision sensor consists of two stereo cameras, mounted parallel in stationary position. …”
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Single-objective and multi-objective optimization algorithms based on sperm fertilization procedure / Hisham Ahmad Theeb Shehadeh by Hisham Ahmad, Theeb Shehadeh

“…The obtained results are compared with the results of four algorithms. These algorithms are Genetic Algorithms (GA), Parallel Genetic Algorithm (PGA), Particle Swarm Optimization (PSO) and Accelerated Particle Swarm Optimization (APSO). …”
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Performance monitoring algorithm for optimizing electrical power generated by using photovoltaic system by Pradeep, M.V.K., Balbir, S.M.S., Norani, M.M.

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Mapping the distribution of oil palm using Landsat 8 data by comparing machine learning and non-machine learning algorithms by Shaharum, Nur Shafira Nisa, Mohd Shafri, Helmi Zulhaidi, Wan Ab. Karim Ghani, Wan Azlina, Samsatli, Sheila, Yusuf, Badronnisa

“…Hence, the mapping of oil palm distributions via machine learning algorithm was better than that via non-machine learning algorithm.…”
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Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data by Amri, A’inur A’fifah, Ismail, Amelia Ritahani, Zarir, Abdullah Ahmad

“…The experiment shows that although the algorithm is stable and suitable for multiple domains, the imbalanced data distribution still manages to affect the outcome of the conventional machine learning algorithms.…”
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Classification of diabetic patients with imbalanced class distribution by using a Cost-Sensitive forest algorithm / Ummi Asyiqin Che Muhammad and Muhammad Hasbullah Mohd Razali by Che Muhammad, Ummi Asyiqin, Mohd Razali, Muhammad Hasbullah

“…Although many machine learning algorithms have been developed by researchers, the class imbalanced distribution still makes it challenging for classifiers to properly learn and differentiate between the minority and majority classes. …”
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Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

“…An alternative method is proposed, utilizing machine learning algorithms. Therefore, this thesis explores the comparative analysis for BOTDA data processing using the six most suited machine learning algorithms. …”

Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J., Hasan, M.H.

“…However, the problem of learning or inferencing the posterior distribution of the algorithm is trivial. …”
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Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J., Hasan, M.H.

“…However, the problem of learning or inferencing the posterior distribution of the algorithm is trivial. …”
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Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing by Goh, Kwang Yi

“…To overcome this limitation, the Q-Learning algorithm was proposed by several researchers to minimise randomness. …”
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Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data by Terence Chia Yi Kai, Agus Saptoro, Zulfan Adi Putra, King Hann Lim, Wan Sieng Yeo, Jaka Sunarso

“…Deep learning algorithms were widely used among all the data-driven algorithms. …”
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Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning by Masuyama, Naoki, Loo, Chu Kiong, Ishibuchi, Hisao, Kubota, Naoyuki, Nojima, Yusuke, Liu, Yiping

“…Moreover, generated topological networks cannot represent the distribution of data. In contrast, the proposed algorithm realizes a stable computation and reduces the number of parameters compared to existing algorithms. …”
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Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique by Mohd Mawardi, Saari, Mohd Herwan, Sulaiman, Kiwa, Toshihiko

“…In this work, the core size estimation technique of magnetic nanoparticles (MNPs) using the static magnetization curve obtained from a high-Tc SQUID magnetometer and a metaheuristic inversion technique based on the Particle Swarm Optimizer (PSO) algorithm is presented. The high-Tc SQUID magnetometer is constructed from a high-Tc SQUID sensor coupled by a flux transformer to sense the modulated magnetization signal from a sample. …”
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Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System by R.Badlishah, Ahmad, Nawir, M., Amir, A, Yaakob, N, Mat Safar, A, Mohd Warip, M.N, Zunaidi, I

“…Therefore, this paper aims to develop an effective and efficient network anomaly detection system by using distributed online averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome these issues. …”
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Distributed Online Averaged One Dependence Estimator (DOAODE) Algorithm for Multi-class Classification of Network Anomaly Detection System by Badlishah, Ahmad, Nawir, M., Amir, A, Yaakob, N, Mat Safar, A, Mohd Warip, M.N, Zunaidi, I

“…Therefore, this paper aims to develop an effective and efficient network anomaly detection system by using distributed online averaged one dependence estimator (DOAODE) classification algorithm for multi-class network data to overcome these issues. …”
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A Divide-and-Distribute Approach to Single-Cycle Learning HGN Network for Pattern Recognition by Muhamad Amin , Anang Hudaya, Khan, Asad I.

“…Distributed Hierarchical Graph Neuron (DHGN) is a single-cycle learning distributed pattern recognition algorithm, which reduces the computational complexity of existing pattern recognition algorithms by distributing the recognition process into smaller clusters. …”
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Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour by Pebrianti, Dwi, Ariawan, Angga, Bayuaji, Luhur, Mahdiana, Deni, ,, Rusdah

“…Meanwhile, k-NN algorithm is used to classify the experimental data. …”
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Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set by Yap, Chau Tean

“…Weka, a data mining tool, provides the facility to classify the data set with different machine learning algorithms. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Dheyab, Saad Ahmed, Mohammed Abdulameer, Shaymaa, Mostafa, Salama A

“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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