Search Results - (( parallel distribution mining algorithm ) OR ( parallel optimization modified algorithm ))
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Parallel multiple tabu search for multiobjective Urban Transit Scheduling Problem
Published 2020“…A set covering model was then adopted to minimize the number of buses and drivers simultaneously. A parallel tabu search algorithm was proposed to solve the problem by modifying the initialization process and incorporating intensification and diversification approaches to guide the search effectively from the different feasible domain in finding optimal solutions with lesser computational effort. …”
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Article -
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Development of optimization Alghorithm for uncertain non-linear dynamical system
Published 2004“…An algorithm that definitely can satisfy the objectives is the Dynamic Integrated Systems Optimization and Parameter Estimation (DISOPE) algorithm. …”
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Monograph -
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Review of the grey wolf optimization algorithm: variants and applications
Published 2023“…The paper begins with a concise introduction to the GWO, providing insight into its natural establishment and conceptual framework for optimization. It then lays out the theoretical foundation and key procedures involved in the GWO, following which it comprehensively examines the most recent iterations of the algorithm and categorizes them into parallel, modified, and hybridized variations. …”
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A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction
Published 2013“…The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. …”
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Conference or Workshop Item -
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Thesis -
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Review of the grey wolf optimization algorithm: variants and applications
Published 2024“…The paper begins with a concise introduction to the GWO, providing insight into its natural establishment and conceptual framework for optimization. It then lays out the theoretical foundation and key procedures involved in the GWO, following which it comprehensively examines the most recent iterations of the algorithm and categorizes them into parallel, modified, and hybridized variations. …”
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Article -
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Development of a real-time clutch transition strategy for a parallel hybrid electric vehicle
Published 2011“…Model predictive control (MPC) has been used for this model and tested with different control horizons and weighting factors to verify the ability of MPC to control the vehicle speeds for the clutch engagement. Some modified MPC algorithms with softened constraints and with output regions have been also studied to improve the robustness and the ability of this controller. …”
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Citation Index Journal -
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OPTIMIZATION OF TWO FISH ENCRYPTION ALGORITHM ON FPGA
Published 2004“…For this project, 2 different optimized designs were implemented. The first design (Design I) was implemented with minimum hardware resources usage, using a single F -Function (modified) and was optimized with reasonable latency, throughput and throughput per gate. …”
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Final Year Project -
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A 'snowflake' geometrical representation for optimised degree six 3-modified chordal ring networks
Published 2016“…This research was aimed at the investigation of a new degree six chordal ring, the optimised degree six 3-modified chordal ring CHR6o3. A tree visualisation was constructed based on its connectivity to enable the generation of formulae for optimal diameter and average optimal path lengths. …”
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Conference or Workshop Item -
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Random sampling method of large-scale graph data classification
Published 2024“…Mining a large number of graphs becomes a challenging task because state-of-the-art methods are not scalable due to the memory limit. …”
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Optimization Of Twofish Encryption Algorithm On FPGA
Published 2005“…For this project, 2 different optimized designs were implemented. The first design (Design I) was implemented with minimum hardware resources usage, using a single F -Function (modified) and was optimized with reasonable latency, throughput and throughput per gate. …”
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Conference or Workshop Item -
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Automatic generic process migration system in linux
Published 2012“…A migration algorithm is designed which attempts to exploit the unique features of the basic migration algorithms to form a generic algorithm. …”
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Thesis -
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Hybrid metaheuristics for QOS-aware service composition / Hadi Naghavipour
Published 2022“…As a result of this mapping study, five major hybridization strategies were identified in which two-third of solutions have been based on modifying algorithm operators or integration with another metaheuristic. …”
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Thesis -
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Dual search maximum power point algorithm based on mathematical analysis under partially-shaded conditions
Published 2016“…In the first group, the conventional techniques are combined with other techniques and the second group is based on the optimization methods. One of the main challenges of MPPT techniques under PSCs is ability of the algorithms to find the GMPP faster with minimal oscillation in power. …”
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Thesis -
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K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata
Published 2018“…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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