Search Results - (( data reduction ((a algorithm) OR (_ algorithm)) ) OR ( parallel optimization method algorithm ))
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Algorithm optimization and low cost bit-serial architecture design for integer-pixel and sub-pixel motion estimation in H.264/AVC / Mohammad Reza Hosseiny Fatemi
Published 2012“…To address the computational complexity and memory bandwidth requirement problems of interpolate and search method in the SME of H.264/AVC, we introduce a low complexity algorithm and its hardware architecture for SME with quarter-pixel accuracy that is based on parabolic interpolation free algorithms. …”
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2
Design and analysis of high performance and low power matrix filling for DNA sequence allignment accelerator using ASIC design flow / Nurul Farhana Abd Razak
Published 2010“…The scope of study is by using the matrix filling method which is in parallel implementation of the SmithWaterman algorithm. …”
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Student Project -
3
Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method
Published 2016“…Since the proposed models (like similar models in the literature) are likely to fall into local optimum points, a Branch and Bound based heuristic, a hybrid Simulated Annealing and Genetic algorithm, a hybrid Tabu search and Simulated Annealing, a hybrid Genetic algorithm and Simulated Annealing, a hybrid Ant Colony Optimization and Simulated Annealing and a hybrid Multi-layer Perceptron and Simulated Annealing algorithms are developed. …”
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Performance of various forecasting algorithms to reduce the number of transmitted packets by sensor node in wireless sensor networks
Published 2018“…Moreover, in term of overall performance for reduction in a number of data transmission reduction EDCD1 algorithm shows the highest ratios. …”
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5
Propositional satisfiability algorithm to find minimal reducts for data mining
Published 2002“…Reduct is a rough set approach in data mining that determines the set of important attributes to represent the IS. …”
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Parallelization of noise reduction algorithm for seismic data on a beowulf cluster
Published 2010“…This paper presents the parallelization of a sequential noise reduction algorithm for seismic data processing into a parallel algorithm. …”
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Citation Index Journal -
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An Alternative Algorithm for Soft Set Parameter Selection using Special Order
Published 2015“…This paper proposed a parameter reduction algorithm, known as 3C algorithm, to circumvent the false frequent object in reduction. …”
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Conference or Workshop Item -
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An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma
Published 2017“…Many normal parameter reduction algorithms exist to handle parameter reduction and maintain consistency of decision choices. …”
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9
Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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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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14
Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2023“…The best accuracy result of 99.97% is obtained when the model operates in a hybrid mode based on a combination of PCA, LDA and RF algorithms, and the data reduction parameter equals 40.…”
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Performance evaluation of caching placement algorithms in named data network for video on demand service
Published 2016“…Also, the outcomes led to conclude that the increase in cache capacity leads to make the placement algorithms have a significant increase in the average cache hit ratio, a reduction in server load, and the total reduction in network footprint, which resulted in obtaining a minimized delay time. …”
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Real-time time series error-based data reduction for internet-of-things applications
Published 2018“…This work differs from existing PIP in the sense that, we have devised a real-time data reduction algorithm namely error-based PIP Data Reduction (PIPE), that operates with a single value configuration; error rate, which can be used with various sensor data without any priori analysis required. …”
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Final Year Project / Dissertation / Thesis -
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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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An enhanced soft set data reduction using decision partition order technique
Published 2017“…The results show that the decision partition order technique performs up to 50% in parameter reduction, while some algorithms could not obtain any reduction. …”
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20
Numerical Integration And Data Reduction For Application In Photometry
Published 2003“…In this thesis, an algorithm based on a local interpolation scheme called the Average Angle Method was developed for numerical integration and data reduction of photometric data, and in general, for any data set sharing similar characteristics as the luminous intensity data The new interpolation scheme interpolates discrete data with piecewise cubic polynomials having a CI continuity in the interior. knots. …”
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