Search Results - (( using function based algorithm ) OR ( sequence classification modeling 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.

“…In this article, we have proposed a distance-based sequence encoding algorithm that captures the sequence's statistical characteristics along with amino acids sequence order information. …”
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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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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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FIS-PNN: a hybrid computational method for protein-protein interactions prediction using the secondary structure information by Sakhinah Abu Bakar, Javid Taheri, Albert Y Zomaya

“…As a result, they must interact with each other. In this study we used our approach, namely FIS-PNN, to predict the interacting proteins in yeast from the information of their secondary structures using hybrid machine learning algorithms. …”
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Computational analysis of biological data: Where are we? by Soreq, Lilach, Mohamed, Wael Mohamed Yousef

“…The current book chapter discusses the advantages of computational modeling in studying biomedical research. Using computational modeling, classification algorithms can be applied to microarray and RNA sequencing data (such as hierarchical clustering - HCL, t-SNE and principal component analysis - PCA), and high-resolution images can be generated based on the analyzed data and patient samples. …”
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A fuzzy approach for early human action detection / Ekta Vats by Ekta, Vats

“…The performance is tested for human action recognition and scene classification. This is a crucial step as it is the first attempt of using fuzzy BK subproduct for classification. …”
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Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling by Mohamed, Raihani

“…When the data are induced with the lower quality model, the performance is also truncated. Furthermore, there is tendency that multi label classifications used instead of traditional single label classification technique. …”
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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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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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Ensemble learning using multi-objective optimisation for arabic handwritten words by Ghadhban, Haitham Qutaiba

“…Multi-Objective Ensemble Oriented (MOEO) formulated to control the classifier topology and provide feedback support for changing the classifiers' topology and weights based on the extension of Non-dominated Sorting Genetic Algorithm (NSGA-II). …”
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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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