Search Results - (( time estimation bat algorithm ) OR ( property distribution from 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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Solving the minimum dominating set problem of partitioned graphs using a hybrid bat algorithm
Published 2020“…This problem belongs to the NP-complete complexity class that cannot be solved exactly in a polynomial time. Hence, we deployed a stochastic method to estimate good solutions for the MDS in a reasonable time. …”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…Motion estimation in video compression process is computationally intensive for video encoder that involve a large percentage of processing time. …”
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Assessing Bat Roosts Using the LiDAR System at Wind Cave Nature Reserve in Sarawak, Malaysian Borneo
Published 2017“…Conventionally, bat roost counts and roost size estimation are potentially a disruptive, repetitive method and are time consuming. …”
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Acoustic emission partial discharge localization in oil based on artificial bee colony
Published 2025“…After 500 iterations, the optimal solution was the estimated PD location produced by ABC. Comparisons with the genetic algorithm (GA), particle swarm optimization (PSO) and bat algorithm (BA) revealed that the distance error, maximum deviation and computation time for AE PD localization based on ABC are the lowest. …”
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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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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…By implementing optimization algorithm in image template matching, it is expected that the computation time can be reduced. …”
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Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data
Published 2023“…The finding reveals that the Weibull distribution is well-suited to describing the investment behaviour of the MPS based on the estimates via the SA algorithm. …”
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Parameter-driven count time series models / Nawwal Ahmad Bukhari
Published 2018“…A key property of our model is that the distributions of the observed count data are independent, conditional on the latent process, although the observations are correlated marginally. …”
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Poisson Transmuted Exponential Distribution For Count Data With Skewed, Dispersed And Excess Zero
Published 2024“…Nine New Mixed Poisson Distributions And Their Respective Zero-Inflated Forms Are Proposed From These Mixing Distributions. …”
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Comparison between clustering algorithm for rainfall analysis in Kelantan / Wan Nurshazelin Wan Shahidan and Siti Nurasikin Abdullah
Published 2017“…So, in this study clustering algorithm on rainfall distribution dataset is done using WEKA 3.8 software. …”
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A simulation study of a parametric mixture model of three different distributions to analyze heterogeneous survival data
Published 2013“…In this paper a simulation study of a parametric mixture model of three different distributions is considered to model heterogeneous survival data.Some properties of the proposed parametric mixture of Exponential, Gamma and Weibull are investigated.The Expectation Maximization Algorithm (EM) is implemented to estimate the maximum likelihood estimators of three different postulated parametric mixture model parameters.The simulations are performed by simulating data sampled from a population of three component parametric mixture of three different distributions, and the simulations are repeated 10, 30, 50, 100 and 500 times to investigate the consistency and stability of the EM scheme.The EM Algorithm scheme developed is able to estimate the parameters of the mixture which are very close to the parameters of the postulated model.The repetitions of the simulation give parameters closer and closer to the postulated models, as the number of repetitions increases, with relatively small standard errors.…”
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Cost-effective scheduling analysis through discrete event simulation for distributed systems
Published 2015“…Users of the systems normally aim to maximize their own interest when consuming the shared resources. Apart from that, the pro- cessing requirements that submitted by the systems’ users are diverse in their properties (e.g., size, priority). …”
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Evoluation strategy for collaborative beamforming in wireless sensor networks
Published 2013“…This group of distributed wireless sensor nodes intrinsically act as a set of virtual antenna array and inherit the natural highly directional transmission properties from conventional antenna array. …”
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Evolution strategy for collaborative beamforming in wireless sensor networks
Published 2013“…This group of distributed wireless sensor nodes intrinsically act as a set of virtual antenna array and inherit the natural highly directional transmission properties from conventional antenna array. …”
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CFD modeling on coal properties towards the burnout efficiency
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Development of a new algorithm for segmentation of flotation froth images
Published 2014“…In spite of this fact, the algorithm suffers from oversegmentation in cases when the flotation froth includes large bubbles along with small ones. …”
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A Novel Approach Of Groebner Bases Computation For Safety Analysis Of Distributed Discrete Controllers
Published 2019“…One of the favorite topic is the formal verification via model checking, which is to verify whether a mathematical model of a system meets the formal specification that describes the property to be checked. In this research, our main objective is to generate a new model checking computation method based on Groebner bases algorithm for safety property analysis of distributed discrete controllers. …”
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