Search Results - (( data integration based algorithm ) OR ( data classification problem algorithm ))

Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

“…In addition, GA has the limitation on generalization which causes the problem of overfitting to the training data. Therefore a correlation-based filtering algorithm is embedded into GA feature selection to solve the over-fitting problem and increase the adaptability of the diagnostic scheme to unpredictable input data. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal by Fadzal, Ahmad Nazmi

“…ACO classification accuracy is compared to Genetic Algorithm classifier which also a wrapper method. …”
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Feature and Instances Selection for Nearest Neighbor Classification via Cooperative PSO by Sharifah Sakinah, Syed Ahmad

“…The reduction method contains two techniques, namely features reduction and data reduction which are commonly applied to a classification problem. …”
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Hyper-heuristic framework for sequential semi-supervised classification based on core clustering by Adnan, Ahmed, Muhammed, Abdullah, Abd Ghani, Abdul Azim, Abdullah, Azizol, Huyop @ Ayop, Fahrul Hakim

“…Existing stream data learning models with limited labeling have many limitations, most importantly, algorithms that suffer from a limited capability to adapt to the evolving nature of data, which is called concept drift. …”
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Jogging activity recognition using k-NN algorithm by Afifah Ismail

“…The k-NN algorithm is a simple and easy-to-implement supervised machine learning algorithm that can be used to solve both classification and regression problems. …”
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Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm by Mohamed, M. E, Samir, B. B., Azween, Abdullah

“…A new non classification algorithm was developed based on the danger theory model of human immune system (HIS).The abstract model of system algorithm is inspired from HIS cell mechanism mainly, the Dendritic cell behavior and T-cell mechanisms. …”
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SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

“…Intrusion detection system detects the violation of confidentiality, integrity, and availability of the data. Intrusion detection systems are developed on the bases of two different detection techniques, signature-based technique and anomaly-based technique. …”
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Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

Empowering cloud providers: optimised locust-inspired algorithm for SLA violation mitigation in green cloud computing by Alsaaidah, Yousef A., Muhammed, Abdullah, Ala’anzy, Mohammed Alaa, Othman, Mohamed, Abdullah, Azizol

“…It enhances the locust-inspired algorithm by integrating SLA-awareness and adaptive host classification and is evaluated using real workload traces in the CloudSim toolkit. …”
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Integrated framework with association analysis for gene selection in microarray data classification by Ong, Huey Fang

“…Therefore, gene selection is an indispensable task in microarray data classification to identify smaller sets of relevant genes. …”
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Neuro fuzzy classification and detection technique for bioinformatics problems by Othman, Mohd. Fauzi, Moh, Thomas Shan Yau

“…A set diabetes data based on real diagnosis of patient was used.…”
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Prognostic Health Management of Pumps Using Artificial Intelligence in the Oil and Gas Sector: A Review by Aliyu, R., Mokhtar, A.A., Hussin, H.

“…While the need for selecting appropriate training algorithms is seen to be significant. Interestingly, no specific method or algorithm exists for a given problem instead the solution relies on the type of data and the algorithmâ��s or methodâ��s aptitude for resolving the provided errors. …”
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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.

New Algorithm of Location Model based on Robust Estimators and Smoothing Approach by Hamid, Hashibah

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A De-noising Scheme for Enhancing Power Quality Problem Classification System Based on Wavelet Transform and Rule-Based Method by Keow, Chuah Heng, Nallagownden, Perumal, K. S. , Rama Rao

“…A Power quality Classification system can easily extract features from the second detail signal obtained after Discrete Wavelet Transform and using these features to construct a Rule Based Algorithm for identifying types of disturbances that exist in the captured power signal. …”
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Comparison of diverse ensemble neural network for large data classification by Mumtazimah, Mohamad, Md Yazid, Mohamad Saman

“…Thus, a Distributed Reordering Technique (DRT) is proposed. DRT is an enhanced algorithm based on distributed random for different neural networks. …”
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Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome by Salari, Nader

“…To this end, as the initial stage, the pros and cons of the “single AI-based” were evaluated toward providing a strategy in development of the best classification models for prediction of heart failure based on the Perth data set. …”
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A Fusion-Based Framework For Explainable Suicide Attempt Prediction by Nordin, Noratikah

“…The proposed work aims to analyse an explainable learning algorithms for predicting suicide attempts, propose an ontology model for semantically representing the classification risk of suicide attempts and propose an explanation generation algorithm by combining predictions from explainable machine learning and ontology models. …”
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Anomaly behavior detection using flexible packet filtering and support vector machine algorithms by Abdul Wahid, Mohammed N.

“…Furthermore, Network traffic prediction algorithms based on SVM such as EaSVM have commented about the fundamental difficulties in achieving an accurate declaration that defines anomaly which suppose to solve the problem of the high rate of false positive alarm and finding excellent ways that guarantees to clear up pending issues of the network traffic normality such as the alluvial data noise of the TAaM method. …”
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