Search Results - (( sequence optimization _ algorithm ) OR ( using classification based 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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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

“…Particle Swarm Optimization (PSO) is a metaheuristic algorithm based on swarm intelligence, widely used to solve global optimisation problems throughout the real world. …”
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An optimal mesh algorithm for remote protein homology detection by M. Abdullah, Firdaus, M. Othman, Razib, Kasim, Shahreen, Hashim, Rathiah, Hassan, Rohayanti, Asmuni, Hishammuddin, Taliba, Jumail

“…This paper also shows that the use of the refinement algorithm increases the performance of the multiple alignments programs by at least 4%.…”
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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.

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Evaluation and optimization of frequent association rule based classification by Izwan Nizal Mohd Shaharanee, Jastini Jamil

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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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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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Angle Based Protein Tertiary Structure Prediction Using Bees Optimization Algorithm by Al-Qattan, Zakaria Noor Aldeen Mahmood

“…In this project, angles based control with Bees Optimization search algorithm were adopted to search with guidance the protein conformational space in order to find the optimum solution. …”
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Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

“…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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Integrating Pixel-Based Algorithms for Area Measurement in Brain Tumor Classification by Dwi Swasono, Rachmad

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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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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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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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Assembly sequence optimization using the bees algorithm by Kamaruddin, Shafie, Azmi, Nabilah, Sukindar, Nor Aiman

“…As a result, the Bees Algorithm outperforms other algorithms in dealing with the multi-modal optimization problem of assembly sequence optimization.…”
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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 second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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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. Several new features in the neural network architecture and training method have been introduced, and the network learns faster to provide accuracy values, which are comparable or better than other methods of ASA prediction. …”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems by Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Bin Ag. Ibrahim, Muhammad Reazul Haque, Joel J. P. C. Rodrigues, Danda B. Rawat

“…These algorithms can influence the convergence to find an efficient optimal solution. …”
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