Search Results - (( sequence optimization method algorithm ) OR ( using classification using algorithmic ))

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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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 major problems in classifying protein sequences into existing families/superfamilies are the following: the selection of a suitable sequence encoding method, the extraction of an optimized subset of features that possesses significant discriminatory information, and the adaptation of an appropriate learning algorithm that classifies protein sequences with higher classification accuracy. …”
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An improved particle swarm optimization algorithm for data classification by Waqas Haider Bangyal, Kashif Nisar, Tariq Rahim Soomro, Ag Asri Ag Ibrahim, Ghulam Ali Mallah, Nafees Ul Hassan, Najeeb Ur Rehman

“…Optimisation-based methods are enormously used in the field of data classification. …”
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Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences by Rajesvary Rajoo R., Salam R.A.

Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

“…To further augment the ARTMAP's pattern classification ability, multiple ARTMAPs were optimized via genetic algorithm and assembled into a classifier ensemble. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

“…The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. …”
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Integrating Pixel-Based Algorithms for Area Measurement in Brain Tumor Classification by Dwi Swasono, Rachmad

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Computational intelligence approach for classification and risk quantification of metabolic syndrome / Habeebah Adamu Kakudi by Habeebah Adamu , Kakudi

“…Genetic Algorithm(GA) is used to optimize the order of sequence of the input sample and the parameters of the Bayesian ARTMAP (BAM). …”
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Evaluation of heuristic-based MicroRNA marker selection techniques for classification of cancer by Razak, Eliza, Yusof, Faridah, Ahmad Raus, Raha

“…In this paper, we employed three marker selection algorithms to select relevant miRNAs that are directly responsible for cancer classification. …”
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Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

“…Application of genetic algorithm method to optimize flow shop sequencing problem as the title of this project is the study about the method used in order to optimize flow shop sequencing problem. …”
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Comparative Analysis Using Bayesian Approach To Neural Network Of Translational Initiation Sites In Alternative Polymorphic Contex by Herman, Nanna Suryana, Husin, Nurul Arneida, Hussin, Burairah

“…The objectives of this paper are to develop useful algorithms and to build a new classification model for the case study.The first approach of neural network includes training on algorithms of Resilient Backpropagation,Scaled Conjugate Gradient Backpropagation and Levenberg-Marquardt.The outputs are used in comparison with Bayesian Neural Network for efficiency comparison.The results showed that Resilient Backpropagation have the consistency in all measurement but performs less in accuracy.In second approach,the Bayesian Classifier_01 outperforms the Resilient Backpropagation by successfully increasing the overall prediction accuracy by 16.0%.The Bayesian Classifier_02 is built to improve the accuracy by adding new features of chemical properties as selected by the Information Gain Ratio method,and increasing the length of the window sequence to 201.The result shows that the built model successfully increases the accuracy by 96.0%.In comparison,the Bayesian model outperforms Tikole and Sankararamakrishnan (2008) by increasing the sensitivity by 10% and specificity by 26%. …”
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Detection of Workers’ Behaviour in the Manufacturing Plant using Deep Learning by Goh, Ching Pang

“…Utilizing machine learning algorithms, our system learns and detects intricate activities from worker behavior sequences, offering a sophisticated analysis of worker efficiency. …”
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A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

“…The first layer is used to detect up to superfamily and family in SCOP hierarchy, by using optimized binary SVM classification rules directly to ROC-Area. …”
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NETASA: neural network based prediction of solvent accessibility by Ahmad, Shandar, Gromiha, M. Michael

“…In the present work, we have implemented a server, NETASA for predicting solvent accessibility of amino acids using our newly optimized neural network algorithm. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD by ABDULLAH, H., LAW BOON HUI, C., ZAKARIA, M. S.

“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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Minimization of machining process sequence based on ant colony algorithm and conventional method by Abdullah, Haslina, Law, Boon Hui C., Zakaria, Mohamad Shukri

“…Thus, in this study, an optimization of the sequence operation in machining was conducted using an Artificial Intelligence method, which is the Ant Colony algorithm. …”
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