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62 results for “Ensemble Method”
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Research ArticleOpen accessIn the abstractHydrological Forecasting Using Hybrid Data-Driven ApproachYoungmin Seo, Sungwon KimThis study develops a hybrid model, EEMD-FANN, coupling feed Forward Artificial Neural Network (FANN) and Ensemble Empirical Mode Decomposition (EEMD) for improving the accuracy of daily river stage forecasting. An original river stage data is broken down into a residue and Intrinsic Mode Functions (IMFs) using the EEMD and different FANNs are developed as forecasting models for the decomposed IMFs … …American Journal of Applied Sciences, Vol. 13, Issue 8 · 2 Sep 2016 · 8,136 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnsemble Divide and Conquer Approach to Solve the Rating Scores’ Deviation in Recommendation SystemIsmail Ahmed Al-Qasem Al-Hadi, Nurfadhlina Mohd Sharef, Md Nasir Sulaiman, Norwati MustaphaThe rating matrix of a personalized recommendation system contains a high percentage of unknown rating scores which lowers the quality of the prediction. Besides, during data streaming into memory, some rating scores are misplaced from its appropriate cell in the rating matrix which also decrease the quality of the prediction. The singular value decomposition algorithm predicts the unknown rating scores … …Journal of Computer Science, Vol. 12, Issue 6 · 25 Jun 2016 · 7,701 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhanced Ensemble Prediction Algorithms for Detecting Faulty Modules in Object Oriented Systems Using Quality MetricsM. Punithavalli, C. NeelamegamThe high usage of software system poses high quality demand from users, which results in increased software complexity. To address these complexities, software quality engineering methods should be updated accordingly and enhance their quality assuring methods. Fault prediction, a sub-task of SQE, is designed to solve this issue and provide a strategy to identify faulty parts of a program, so … …Journal of Computer Science, Vol. 8, Issue 12 · 20 Dec 2012 · 6,435 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Evaluation of Adaptive Filter and Neuro-Fuzzy Filter in Artifacts Removal From Electroencephalogram SignalPaulchamy Balaiah, IlavennilaProblem statement: This study presents an effective method for removing mixed artifacts (EOG-Electro-ocular gram, ECG-Electrocardiogram, EMG-Electromyogram) from the EEG-Electroencephalogram records. The noise sources increases the difficulty in analyzing the EEG and obtaining clinical information. EEG signals are multidimensional, non-stationary (i.e., statistical properties are not invariant in time), time domain biological signals, which are not reproducible. It is supposed to contain … …American Journal of Applied Sciences, Vol. 9, Issue 10 · 15 Aug 2012 · 7,087 accessesView PDFCite
Research ArticleOpen accessIn the abstractSurvival and Change of Mahoree Tradition in Cambodian SocietyPittayawat Pantasri, Jarernchai Chonpairot, Boonsom YodmaleeProblem statement: Mahoree, is an important music ensemble in Cambodia since the Angkorean period. Mahoree formerly belonged to the court or noble Cambodian families. Mahoree is very popular and practiced by ordinary people and plays an important role in Cambodian society. Mahoree is a culture of the community and the Cambodian society and can be preserved and promoted by community … …Journal of Social Sciences, Vol. 8, Issue 2 · 13 Mar 2012 · 8,662 accessesView PDFCite
Research ArticleOpen accessIn the abstractBoosting Kernel Discriminative Common Vectors for Face RecognitionC. Lakshmi, M. PonnavaikkoProblem statement: Kernel discriminative common vector (KDCV) was one of the most effective non-linear techniques for feature extraction from high dimensional data including images and text data. Approach: This study presented a new algorithm called Boosting Kernel Discriminative Common Vector (BKDCV) to further improve the overall performance of KDCV by integrating the boosting and KDCV techniques. Results: In BKDCV, the … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,571 accessesView PDFCite
Research ArticleOpen accessIn the abstractBenders' Decomposition Based Heuristics for Large-Scale Dynamic Quadratic Assignment ProblemsSirirat Muenvanichakul, Peerayuth CharnsethikulProblem statement: Dynamic Quadratic Assignment Problem (DQAP) is NP hard problem. Benders decomposition based heuristics method is applied to the equivalent mixed-integer linear programming problem of the original DQAP. Approach: Approximate Benders Decomposition (ABD) generates the ensemble of a subset of feasible layout for Approximate Dynamic Programming (ADP) to determine the sub-optimal optimal solution. A Trust-Region Constraint (TRC) for the … …Journal of Computer Science, Vol. 5, Issue 1 · 31 Jan 2009 · 7,681 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Wide Scale Classification of Class Imbalance Problem and its Solutions: A Systematic Literature ReviewGillala Rekha, Amit Kumar Tyagi, V. Krishna ReddyIn today’s world, most of the data (real world) is present in imbalanced form by nature. This is because of not having efficient algorithms to put this data (i.e., generated data by billion of internet- connected devices (IoTs)) in respective format. Imbalanced data poses a great challenge to (both) data mining and machine learning algorithms. The imbalanced dataset consists of … …Journal of Computer Science, Vol. 15, Issue 7 · 3 Jul 2019 · 9,372 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordMulti-Source Cyber Intrusion Detection Using Ensemble Machine LearningTaskeen Ali Khan, Sara Abbas, Biswaranjan Senapati et al.The increased usage of digital technologies across businesses has led to an increase in cybercrime. It is difficult for existing intrusion detection systems to detect highly skilled hacking attempts; however, machine learning has been suggested as a way around these drawbacks. The purpose of this study is to evaluate how well various machine learning algorithms identify and stop cyberattacks in … …Journal of Computer Science, Vol. 21, Issue 1 · 14 Dec 2024 · 5,696 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordA Weighted Voting Deep Learning Approach for Plant Disease ClassificationAssia Ennouni, Noura Ouled Sihamman, My Abdelouahed Sabri, Abdellah AarabPlant destruction is usually caused by plant diseases. Without early and reliable detection, it can affect the plants and may eventually cause permanent losses, especially for inexperienced farmers. Therefore, intelligence in agriculture is becoming more and more required. Thereafter early diagnosis and classification are crucial and a very challenging research field in the agriculture sector for its treatment. In this … …Journal of Computer Science, Vol. 17, Issue 12 · 16 Dec 2021 · 6,557 accessesView PDFCite