Search Results - (( using value parallel algorithm ) OR ( java application optimization algorithm ))
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Parallel implementation on improved error signal of backpropagation algorithm
Published 2001“…The experiments are implemented using the Sequent Symmetry SE30 parallel machine. …”
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Thesis -
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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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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Parallel execution of diagonally implicit Runge-Kutta methods for solving IVPs.
Published 2009“…In this paper we used DIRK methods which are specifically designed for parallel execution to solve a set of initial value problems. …”
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Parallel block methods for solving higher order ordinary differential equations directly
Published 1999“…A new parallel algorithm for solving systems of ODEs using variable step size and order is also developed. …”
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Thesis -
10
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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Parallel Kalman filter-based multi-human tracking in surveillance video
Published 2014“…A Kalman filter is a recursive algorithm which predict the state variables and further uses the observed data to correct the predicted value. …”
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Ant colony optimization algorithm for load balancing in grid computing
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…After classifying the time set using the canopy with the K-means algorithm and the vector representation weighted by factors, the clustering impact is assessed using purity, precision, recall, and F value. …”
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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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Parallel Block Methods for Solving Ordinary Differential Equations
Published 2004“…The new codes were then used for the parallel implementation in solving large systems of first and higher order ODEs. …”
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Thesis -
17
Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering
Published 2023“…We first extracted the emotion features from speech and calculated the F-Emotion value for each feature. These values were then used to determine the combination of speech emotion features that was optimal for speech emotion recognition. …”
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A parallel-model speech emotion recognition network based on feature clustering
Published 2023“…We first extracted the emotion features from speech and calculated the F-Emotion value for each feature. These values were then used to determine the combination of speech emotion features that was optimal for speech emotion recognition. …”
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