Search Results - time estimation ((methods algorithm) OR (((bat algorithm) OR (means algorithm))))
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…To summarise, metaheuristic algorithms can give a superior optimization approach than the traditional artificial neural network method, providing the computing time is within an acceptable range. …”
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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“…Block Matching Algorithm (BMA) is a technique used to minimize the computational complexity of motion estimation in video coding application. …”
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Severity Estimation of Plant Leaf Diseases Using Segmentation Method
Published 2020“…The best severity estimation algorithm and color space used to estimate the diseases severity of plant leaf is the combination of Fuzzy C-Means and YCbCr color space. …”
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Segmentation of MRI brain images using statistical approaches
Published 2011“…The non-Local means (NL-means) algorithm is a state-of-the art neighbourhood-based noisereduction method which is time-consuming and its accuracy can be improved. …”
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On time-domain OFDM channel estimation: Use of pilots correlation for digital video broadcasting (DVB) cable receiver
Published 2015“…In this paper, an improved OFDM time domain channel estimation algorithm is proposed for (DVB) Cable receivers. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. All of the algorithms are later combined to provide device location estimation for multi-floor environment. …”
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A Computationally Efficient Least Square Channel Estimation Method for MIMO-OFDM Systems
Published 2021“…Some of the most popular methods used in cellular communication for channel estimation are the Least Squares (LS) algorithm and the Minimum Mean Square Error (MMSE) algorithm. …”
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Reduced-rank technique for joint channel estimation in TD-SCDMA systems.
Published 2013“…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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Indoor positioning using weighted magnetic field signal distance similarity measure and fuzzy based algorithms
Published 2021“…Therefore, for the second objective, another algorithm named the fuzzy algorithm is designed which combines the clustering algorithm, matching algorithm, triangle area algorithm and average Euclidean algorithm used to estimate location. …”
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Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA)
Published 2018“…Generation gap used was 0.5 has shorten the algorithm convergence time without affecting the model accuracy.…”
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Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems
Published 2013“…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems
Published 2012“…The adopted reduced rank technique is based on singular value decomposition algorithm. Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity
Published 2014“…The proposed THF-NLFXLMS algorithm models the Wiener secondary path and applies the estimated degree of nonlinearity of the nonlinear secondary path in the control algorithm design. …”
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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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Performance of DOA estimation algorithms for acoustic localization of indoor flying drones using artificial sound source
Published 2024“…Similarly, it is observed that the chirping sound with wider band also produced better results in three of the algorithms, which is reflected in their absolute mean error. …”
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