Search Results - (( normal distribution new 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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Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop
Published 2016“…Log likelihood estimation technique is used to fit the best 2-parameter CDF compared to Weibull, Normal and Rician distribution model. The percentage level 5% under original bandwidth used is developed on policing and shaping algorithms to control bandwidth used. …”
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A new efficient checkpointing algorithm for distributed mobile computing
Published 2015“…Considering this issue, the contribution in this paper is a proposal of a new checkpointing algorithm suitable for mobile computing systems. …”
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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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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution: article / Nor Azura Ayop
Published 2016“…Log likelihood estimation technique is used to fitted the best 2-parameter CDF compared to WeibuII, Normal and Rician distribution model. The percentage level 5% under original bandwidth used is developed on policing and shaping algorithms to control bandwidth used. …”
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Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan
Published 2015“…Directional statistics is a branch of statistics which deal with the data in angle form in which the method of analysis is different from linear data. For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Anderson-Darling (AD) and Goodness of Fit test is used to identify the best fitted distribution model to the real data. Four traffic distribution which are normal, lognormal, Weibull and exponential distribution are fitted and derived. …”
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JPEG Image Encryption Using Combined Reversed And Normal Direction-Distorted Dc Permutation With Key Scheduling Algorithm-Based Permutation
Published 2008“…This thesis work studied on digital image encryption algorithms performed towards JPEG images. With image encryption algorithms, JPEG images can be securely scrambled or encrypted prior to distribution. …”
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Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Anderson-Darling (AD) and Goodness of Fit test is used to identify the best fitted distribution model to the real data. Four traffic distribution which are normal, lognormal, Weibull and exponential distribution are fitted and derived. …”
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Entropy in portfolio optimization / Yasaman Izadparast Shirazi
Published 2017“…More specifically, we use multi-objective models that are the mean-entropy-entropy (MEE). The purpose of this new model is to overcome the limitations as observed in a traditional model; that is, having performance close to Markowitz’s mean-variance (MV) model when data comes from a normal distribution, but exhibit better performance when data comes from a non-normal distribution. …”
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Improving resource management with multi-instance broker scheduling algorithm in hierarchical grid computing
Published 2016“…Multi-Instance Broker Scheduling Algorithm (MiBSA) has been proposed as a new scheduling algorithm to get rid of the drawback from the iHLBA algorithm. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…The obtained results were compared with the BH and previous optimization algorithms for both test functions as well as data clustering in terms of normal and high dimensional datasets. …”
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Single-solution Simulated Kalman Filter algorithm for global optimisation problems
Published 2018“…In the proposed ssSKF algorithm, the initialisation parameters are not constants, but they are produced by random numbers taken from a normal distribution in the range of 0, 1, thus excluding them from tuning requirement. …”
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Single-solution Simulated Kalman Filter algorithm for global optimisation problems
Published 2018“…In the proposed ssSKF algorithm, the initialisation parameters are not constants, but they are produced by random numbers taken from a normal distribution in the range of 0, 1, thus excluding them from tuning requirement. …”
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Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian
Published 2013“…In addition to the normal metrics, the computational time for executing each algorithm was also measured and compared. …”
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Robust Kernel Density Function Estimation
Published 2010“…To do this evaluation, the mixtures of bivariate normal distribution with different percentage of contribution are simulated. …”
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