Search Results - (( time distribution _ algorithm ) OR ( parameter estimation bat algorithm ))
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Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm
Published 2023“…Decision making; Disaster prevention; Floods; Routing algorithms; Water resources; Absolute deviations; Bat algorithms; Comparative analysis; Computational time; Flood routing; Muskingum models; Particle swarm optimization algorithm; Swarm algorithms; Particle swarm optimization (PSO); accuracy assessment; algorithm; comparative study; decision making; flood; flood forecasting; flood routing; numerical method; optimization; parameter estimation; water resource; United Kingdom; United States…”
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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
Published 2018“…The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…The firefly algorithm remains a feasible alternative for shallow architectural network models, while metaheuristic algorithms such as the Particle swarm algorithm and Bat algorithm are better options for deeper architectural network models. …”
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Improving pipelined time stepping algorithm for distributed memory multicomputers
Published 2010“…We present a modified pipelined time stepping algorithm based on delayed pipelining and reduced communication strategies to improve overall execution time on a distributed memory environment using MPI. …”
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Self-Schedule and Self-Distributive MAC Scheduling Algorithms for Next-Generation Sensor Networks
Published 2015“…It has been demonstrated that, with regard to communication overhead, energy consumption and execution time through simulation proposed that algorithms outperform existing distributed randomized scheduling algorithm (DRAND). …”
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Optimal location and size estimation of distributed generators by employing grouping particle swarm optimization and grouping genetic algorithm
Published 2017“…This work is aimed to decrease the total real and reactive power losses while enhancing the voltage profile of the distribution network with less computation time by proposing two new artificial intelligence algorithms, i.e. grouping particle swarm optimization algorithm and grouping genetic algorithm. …”
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Time Synchronization Using Distributed Observer Algorithm With Sliding Mode Control For Wireless Sensor Network
Published 2015“…The algorithm is known as Time Synchronization using Distributed Observer algorithm with Sliding mode control element (TSDOS).The main purpose of proposing TSDOS is to estimate a common global clock time by which all nodes within the WSN can use it for communication purpose. …”
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Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification
Published 2018“…There are still room for improvement in the time taken for the algorithm to complete the topic distribution. …”
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Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification
Published 2018“…There are still room for improvement in the time taken for the algorithm to complete the topic distribution. …”
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Efficient signaling schedule for centralized and distributed scheduling algorithms for wimax multi-hop relay networks
Published 2012“…On the other hand, the proposed distributed scheduling algorithm (MR-DSA) was evaluated by comparing its performance against performances of Greedy and the factor-graph-based low-complexity distributed scheduling algorithm (FGDS) algorithms in terms of delay, throughput, and overhead. …”
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Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour
Published 2022“…This result shows that the proposed method improves the accuracy by 13.3% on single Naive Bayes algorithms and 4% on a single k-NN algorithm. The results obtained show that in the manual process, the average time per job is 1.42 minutes, while by using the proposed method, the average processing time is around 0.03 seconds per job. …”
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Proceeding Paper -
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Reliability Analysis and Prediction of Time to Failure Distribution of an Automobile Crankshaft
Published 2015“…The developed stochastic algorithm has the capability to measure the parametric distribution function and validate the predict the reliability rate, mean time to failure and hazard rate. …”
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Batch mode heuristic approaches for efficient task scheduling in grid computing system
Published 2016“…In ELB algorithm, the tasks are distributed among resources based on their execution time range. …”
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Distributive and self-sustainable scheduling algorithm for wireless sensor networks
Published 2013“…Simulation results show that DSSA is more performance optimal than the distributed randomized scheduling algorithm DRAND in terms of energy consumption, message overhead and execution time. …”
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Distributive and self-sustainable scheduling algorithm for wireless sensor networks
Published 2013“…Simulation results show that DSSA is more performance optimal than the distributed randomized scheduling algorithm DRAND in terms of energy consumption, message overhead and execution time. …”
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Distributive and self-sustainable scheduling algorithm for wireless sensor networks
Published 2013“…Simulation results show that DSSA is more performance optimal than the distributed randomized scheduling algorithm DRAND in terms of energy consumption, message overhead and execution time. …”
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Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop
Published 2016“…This result help to expand the view of new idea in modelling the tele-traffic algorithm based on bandwidth management and time processing improvement. …”
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