Search Results - (( parallel optimization method algorithm ) OR ( tree validation learning algorithm ))
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Phylogenetic tree classification system using machine learning algorithm
Published 2015“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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Final Year Project Report / IMRAD -
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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Classification of fault and stray gassing in transformer by using duval pentagon and machine learning algorithms
Published 2022“…The algorithms are able to achieve the accuracy of 82.6% (boosted trees), 81.2% (RUS boosted trees) and 72.5% (subspace KNN), respectively, when validated with actual transformer condition.…”
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Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms
Published 2015“…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes
Published 2007“…Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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Research Report -
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Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design
Published 2024“…This paper presents a comprehensive study on the design optimization of a robotic gripper, focusing on both the gripper modeling and the optimization of its parallel mechanism structure. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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Prediction of Machine Failure by Using Machine Learning Algorithm
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Final Year Project -
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Prediction of life expectancy for Asian population using machine learning ALGORITHMS / Nurul Shahira Pisal, Shuzlina Abdul-Rahman, Mastura Hanafiah and Saidatul Izyanie Kamarudin
Published 2022“…This study presents machine learning algorithms for life expectancy based on the Asian population dataset. …”
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Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation
Published 2023“…The study involved three machine learning algorithms, random forest (RF), extra tree (ET), and support vector machine (SVM). …”
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems
Published 2018“…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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14
Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil
Published 2014“…Examples of EC such as Genetic Algorithm (GA) and PSO (Particle Swarm Optimization) are prevalent due to their efficiency and effectiveness. …”
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15
Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks
Published 2022“…Next, the method is integrated with two optimization algorithms: (1) backpropagation (BP), which optimizes deep learning locally within each local chunk of the CN; (2) particle swarm optimization (PSO), which is used to improve the BP optimization involving all CN chunks. …”
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PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems
Published 2016“…The AGC loop is used to minimize the frequency deviation and control the power exchange in order to maintain them at their scheduled values due to the changes of the step-load disturbance. The optimal parameters of the PID scheme optimized by the proposed MS algorithm are compared with that one’s obtained by GA algorithm, and the proposed method has proven that its performance is more efficient and improved as well. …”
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Design and analysis of high performance matrix filling for DNA sequence alignment accelerator using asic design flow: article / Nurzaima Mahmod
“…The scope of this paper is to optimize the DNA sequences alignment on the matrix rilling module by implementing a parallel method of the Smith-Waterman algorithm. …”
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Design and analysis of high performance matrix filling for DNA sequence alignment accelerator using ASIC design flow / Nurzaima Mahmod
Published 2010“…The scope of this paper is to optimize the DNA sequences alignment on the matrix filling module by implementing a parallel method of the SmithWaterman algorithm. …”
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Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow
Published 2023“…Selected regression models were compared with Random Forest, Gradient Boosting, Decision Tree, and other non-tree algorithms to prove the R2 driven performance superiority of tree-based ensemble models. …”
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