Search Results - (( sequence classification model algorithm ) OR ( parallel optimization path algorithm ))

Computational Technique for an Efficient Classification of Protein Sequences With Distance-Based Sequence Encoding Algorithm by Iqbal, M.J., Faye, I., Said, A.M.D., Samir, B.B.

“…The accurate classification of protein sequence would be helpful in determining the structure and function of novel protein sequences. …”
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Tool path generation of contour parallel based on ant colony optimisation by Abdullah, Haslina, Ramli, Rizauddin, Abd Wahab, Dzuraidah, Abu Qudeiri, Jaber

“…An Ant Colony Optimisation (ACO) method is used to optimize the tool path length because of its capability to find the shortest tool path length. …”
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Optimized tree-classification algorithm for classification of protein sequences by Iqbal, M.J., Faye, I., Said, A.M., Belhaouari Samir, B.

“…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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Optimized tree-classification algorithm for classification of protein sequences by Iqbal, M.J., Faye, I., Said, A.M., Belhaouari Samir, B.

“…In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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Minimizing machining airtime motion with an ant colony algorithm by Abdullah, Haslina, Ramli, Rizauddin, Abd Wahab, Dzuraidah, Abu Qudeiri, Jaber

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OPTIMAL DATAPATH DESIGN FOR A CRYPTOGRAPHIC PROCESSOR: THE BLOWFISH ALGORITHM by Zain Ali, Noohul Basheer, Noras, James

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A Multi-tier Model and Filtering Approach to Detect Fake News Using Machine Learning Algorithms by Yu, Chiung Chang, A Hamid, Isredza Rahmi, Abdullah, Zubaile, Kipli, Kuryati, Amnur, Hidra

“…Two sequences of classification models are used in this research paper: LR_DT_RF and LR_NB_AdaBoost. …”
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Protein Sequences Classification Using Modular RBF Neural Networks by Wang, Dianhui, Lee, Nung Kion, Dillon, Tharam S., Hoogenraad, Nicholas J.

“…These algorithms compare an unseen protein sequence with all the identified protein sequences and returned the higher scored protein sequences. …”
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An efficient computational intelligence technique for classification of protein sequences by Iqbal, M.J., Faye, I., Said, A.M., Samir, B.B.

“…This classification would be helpful in the analysis and modeling of unknown protein to determine their structure and function. …”
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A new LoRa based positioning algorithm utilizing sequence based deep learning technique by Suseenthiran, Kavetha

“…Next, RSSI and Signal-to-Noise Ratio (SNR) that is measured is being classified whether it is LoS or NLoS environment based on the sequence-based Bi-LSTM model. Furthermore, an analysis of classification using different sequence length is done. …”
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Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib by Dian Najihah , Abu Talib

“…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga by Mwenge , Mulenga

“…The research shows that a model that addresses dimensionality, feature dominance and sparsity produce outstanding prediction results in colorectal cancer identification using high sequence-based gut microbiome data. …”
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Multitasking deep neural network models for Arabic dialect sentiment analysis by Alali, Muath Mohammad Oqlah

“…Therefore, a model called Multi-Tasking Learning based on Convolutional Hierarchical Attention Neural Network (MTL-CHAN) is proposed, comprising of (i) shared word encoder and word attention networks across classification tasks, (ii) task-specific layers with convolutional neural network-based attention (CNNA) on sentence-level; to handle the Arabic explicit negation words and improve the classification performance by training Arabic classification tasks (binary, ternary, and five) jointly. …”
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Improved GART neural network model for pattern classification and rule extraction with application to power systems by Yap K.S., Lim C.P., Au M.T.

“…Generalized adaptive resonance theory (GART) is a neural network model that is capable of online learning and is effective in tackling pattern classification tasks. …”

Power quality event characterization by Tan C.K., Kumaran V., Siam F.M., Busrah A.M.

Hybrid data regression model based on the generalized adaptive resonance theory neural network by Wong S.Y., Yap K.S., Lim C.P., Lee E.W.M.

Development of Phasor Measurement Unit Based Fault Detection and Faulty Line Classification in Electrical Power System by Muhammad Qasim, Khan

“…This model implements Non-Recursive Phasor Estimation (NRPE) algorithm. …”
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Convolutional neural networks with feature fusion method for automatic modulation classification by Elshebani, Mohamed Salem, Ali, Yahya, Azroug, Nser, Khalifa, Ramdan A. M., Khalifa, Othman Omran, Saeed, Rashid A.

“…However, most existing modulation classification algorithms are neglecting the fact of mixing features between different representations, and the importance of features fusion method. …”
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An accurate algorithm of PMU-based wide area measurements for fault detection using positive-sequence voltage and unwrapped dynamic angles by Muhammad Qasim, Khan, Musse Mohamud, Ahmed, Ahmed Mohamed, Ahmed Haidar

“…The algorithm includes an index for faulty bus classification based on the positive-sequence voltage measurements of the pre-fault and post-fault conditions, where the bus with a maximum differential percentage is identified as a faulted bus. …”
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ANALYSIS OF CLASSIFICATION PROCESS FOR VIDEO SCENE UNDERSTANDING by MOHD RASHDAN, NURUL FARAH

“…Scene understanding is a process observing scenes which humans are used as models to understand them. This project is focused on analyzing the classification process for video scene. …”
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