Search Results - (( parallel optimization methods algorithm ) OR ( new optimization method algorithm ))
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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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3
Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…The new algorithms also boast faster contractions. Both new algorithms performed better than DISOPE. …”
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Monograph -
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OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM
Published 2011“…In this thesis, a new optimization GA-based algorithm that emanates from modification of conventional GA to reduce the iterations number and the duration time, namely, semi-parallel operation genetic algorithm (SPOGA) is proposed. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…Therefore, this study explores how to model reconfigurable manufacturing activities in an optimization perspective and how to develop and select appropriate non-conventional optimization techniques for reconfigurable process planning.In this study, a new approach to modeling Manufacturing Process Planning Optimization (MPPO) was developed by extending the concept of manufacturing optimization through a decoupled optimization method. …”
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Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…This paper presents two intelligent algorithms that hybridized between ant colony optimization (ACO) and SVM for tuning SVM parameters and selecting feature subset without having to discretize the continuous values. …”
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Article -
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…In this study, Simulated Kalman Filter (SKF) is applied to image template matching application as the optimization algorithm. SKF is compared with conventional algorithms for image template matching which are performance index value (PIM) and correlation by using DC components of image (TMC) and by using power of images (TMP) methods. …”
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Thesis -
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Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system
Published 2010“…The particle swarm optimization (PSO) method is used to tune the parameters of the controller and weighting functions subject to QFT and/or constraints. …”
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A parallel ensemble learning model for fault detection and diagnosis of industrial machinery
Published 2023“…Deep learning has recently emerged as effective methods for machine FDD applications. However, the gradient descent optimization method that is commonly used in deep learning suffers from several limitations, such as high computational cost and local sub-optimal solutions. …”
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Hybrid metaheuristics for QOS-aware service composition / Hadi Naghavipour
Published 2022“…An absolute majority of base algorithms for this problem were nature-inspired and population-based metaheuristics extended to complementary methods in hybrid solutions. …”
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Thesis -
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Hybrid intelligent methods for parameter identification and load frequency control in power system
Published 2014“…A new method from the improvement of Particle Swarm Optimization (PSO) is developed in order to find the best global optimal value. …”
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An efficient indexing and retrieval of iris biometrics data using hybrid transform and firefly based K-means algorithm title
Published 2019“…It uses a weighted K-means clustering algorithm based on the improved FA to optimize the initial clustering centers of K-means algorithm, known as Weighted K-means clustering-Improved Firefly Algorithm (WKIFA). …”
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A multi-layer perceptron for scheduling cellular manufacturing systems in the presence of unreliable machines and uncertain cost
Published 2016“…In this paper, a new method is proposed for short-term period scheduling of dynamic cellular manufacturing systems in the presence of bottleneck and parallel machines. …”
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Article -
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FPGA Implementation of Multi-User Detection Genetic Algorithm Tool for SDMA-OFDM Systems
Published 2016“…Resource utilization is optimized, and the total number of clock cycles required is found to be 15 initially, in addition to one clock cycle per member of algorithm population. …”
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Numerical methods for nonlinear optimal control problems using haar wavelet operational matrices / Waleeda Swaidan Ali
Published 2015“…To establish a direct method, an efficient new algorithm is proposed to solve nonlinear optimal control problems with a finite time horizon under inequality constraints. …”
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Thesis -
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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A new approach in solving illumination and facial expression problems for face recognition
Published 2009“…In this paper, a novel dual optimal multiband features (DOMF) method is presented to increase the robustness of face recognition system to illumination and facial expression variations.The wavelet packet transform first decomposes image into low-, mid- and high-frequency subbands and the multiband feature fusion technique is incorporated to select the subbands that are invariant to illumination and expression variation separately.These subbands form the optimal feature sets.Parallel radial basis function neural networks are employed to classify these feature sets.The scores generated by the neural networks are combined by an adaptive fusion mechanism where the level of illumination variations of the testing image is estimated and the weights are assigned to the scores accordingly.The experimental results show that DOMF outperforms other algorithms and also achieves promising performance on illumination and facial expression variation conditions.…”
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Conference or Workshop Item -
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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