Search Results - (( data classification problems algorithm ) OR ( simulation optimization parallel algorithm ))
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1
A parallel prevention algorithm for black hole attacks in MANET
Published 2015“…In this paper, we propose a parallel algorithm for MANETs that optimizes both routing discovery and security in an Ad Hoc On Demand Distance Vector (AODV). …”
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2
Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…To achieve an optimum waiting and response time this thesis has proposed a new approach utilizing the aforementioned modelling, optimizing and partitioning algorithms. This approach has simulated on Alea v.4, which is a dedicated simulator for simulating exascale parallel scheduling. …”
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3
Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…The simulation results prove that proposed algorithms outperform from state of the art algorithms for variety of workflows. …”
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4
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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5
FPGA implementation of metaheuristic optimization algorithm
Published 2023“…The selected metaheuristic was the Simulated Kalman Filter (SKF) which proposed an algorithm that was low in complexity and used a small number of steps. …”
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6
Fpga Implementation Of Metaheuristic Optimization Algorithm
Published 2022“…The selected metaheuristic was the Simulated Kalman Filter (SKF) which proposed an algorithm that was low in complexity and used a small number of steps. …”
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Undergraduates Project Papers -
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Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…This project focused on three main objectives: to investigate dengue data and Clonal Selection Algorithm for classification of Dengue, to design and develops Clonal Selection Classification System (CSCS) and to evaluate Clonal Selection Classification System symptoms. …”
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8
Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…As the total objective values in most of problems could not be improved by simulated algorithm, it proved the well performing of proposed intelligence based genetic algorithm in reaching the near optimal solutions.…”
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9
PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems
Published 2016“…Integral Square Error (ISE) is considered as an objective function for both algorithms to determine its performance index value for the same parallel-connected power system. …”
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10
Parallel CFD Simulations of Multiphase Systems: Jet into a Cylindrical Bath and Rotary Drum on a Rectangular Bath.
Published 2001“…In short, this research is intended to establish a strategic procedure to optimize a parallel version of a CFD package, FLUENT. …”
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11
WCDMA teletraffic performance improvement via power resource optimization using distributed parallel genetic algorithm
Published 2023“…The algorithm works by finding the minimum transmitter power with the help of Distributed Parallel Genetic Algorithm (DPGA) employed on an offload microcontroller system to form optimal beam coverage to reduce power usage of adaptive antenna at WCDMA base station. …”
Conference paper -
12
Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…Based on the results of these simulations, we compared the number of iterations needed by each algorithm to arrive at the optimal solution and the CPU time taken for each algorithm to execute the search. …”
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Monograph -
13
Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…The study verified that the FID3-DBD algorithm could classify the continuous data, and the BFID3-DBD algorithm overcame the overfitting issue, reduced high variance, and increased test data classification accuracy.…”
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14
An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning focusing on predicting class labels for datasets with continuous features. …”
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15
An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…This paper addresses the classification problem in machine learning, focusing on predicting class labels for datasets with continuous features. …”
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16
A derivative-free optimization method for solving classification problem
Published 2010“…Problem statement: The aim of data classification is to establish rules for the classification of some observations assuming that we have a database, which includes of at least two classes. …”
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17
Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Next the problem of data classification is studied as a problem of global, non-smooth and non-convex optimization; this approach consists of describing clusters for the given training sets. …”
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18
Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Decision tree is an important method in data mining to solve the classification problems. …”
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19
Simulated annealing algorithm for scheduling divisible load in large scale data grids.
Published 2009“…Many Scheduling approaches have been studied but there is no optimal solution. This paper proposes a novel Simulated Annealing (SA) algorithm for scheduling divisible load in large scale data grids. …”
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20
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…The result has shown that the proposed integration system could be applied to increase the performance of the classification. However, further study is needed in the feature extraction and clustering algorithms part as the performance of the pattern classification is still depending on the data input.…”
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