Search Results - ((((((linear algorithm) OR (new algorithm))) OR (based algorithm))) OR (means algorithm))
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Widely linear dynamic quaternion valued least mean square algorithm for linear filtering
Published 2017“…The performance of the proposed algorithms are compared with quaternion least mean square QLMS, zero-attract quaternion least mean square ZA-QLMS, and widely linear quaternion least mean square WL-QLMS algorithms. …”
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2
Dynamic determinant matrix-based block cipher algorithm
Published 2018“…The design of the s-box is the most crucial part while designing a new block cipher algorithm since it is the only non-linear element of the cipher. …”
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3
Real time nonlinear filtered-x lms algorithm for active noise control
Published 2012“…The performance of these algorithms is usually compared with the standard linear filtered-x least mean square (FXLMS) algorithm. …”
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4
Clustering Spatial Data Using a Kernel-Based Algorithm
Published 2005“…Therefore, this work comes up with new clustering algorithm using kernel-based methods for effective and efficient data analysis by exploring structures in the data.…”
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5
Nonlinear FXLMS algorithm for active noise control systems with saturation nonlinearity
Published 2012“…Simulation results show that the performance of the THF-based NLFXLMS algorithm is comparable with the SEF-based NLFXLMS.…”
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The new efficient and accurate attribute-oriented clustering algorithms for categorical data
Published 2012“…This work firstly reveals the significance of attributes in categorical data clustering, and then investigates the limitations of algorithms MMR and G-ANMI respectively, and correspondingly proposes a new attribute-oriented hierarchical divisive clustering algorithm termed Mean Gain Ratio (MGR) and an improved genetic clustering algorithm termed Improved G-ANMI (IG-ANMI) for categorical data. …”
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8
A NOVEL FORWARD BACKWARD LINEAR PREDICTION ALGORITHM FOR SHORT TERM POWER LOAD FORECAST
Published 2010“…The proposed AR-based algorithm divides long data record into short segments and searches for the AR coefficients that simultaneously model the data with the least means squared errors. …”
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9
Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman
Published 2013“…The idea was incorporated into a new algorithm called, k-Approximate Modal Haplotypes (&-AMH) algorithm. …”
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10
Computation of cryptosystem based on Lucas functions using addition chain
Published 2010“…The computation time for existing and new algorithms will be recorded. Smaller computation time means the algorithm is efficient than the other. …”
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11
Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…For fingerprint database optimisation, novel access point (AP) selection algorithms which are based on variant AP selection are investigated to improve computational accuracy compared to existing AP selection algorithms such as Max-Mean and InfoGain. …”
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12
A new multiperspective framework for standardization and benchmarking of image dehazing algorithms
Published 2021“…A standardization and benchmarking framework for image dehazing algorithms based on multiple perspectives is not yet available. …”
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13
Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane
Published 2021“…In the HMVOSCA algorithm, the new position updating mechanism of the traditional MVO method is modified based on the sine function and cosine function which is taken from the Sine Cosine Algorithm (SCA). …”
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14
Ant system-based feature set partitioning algorithm for classifier ensemble construction
Published 2016“…In this study, Ant system-based feature set partitioning algorithm for classifier ensemble construction is proposed.The Ant System Algorithm is used to form an optimal feature set partition of the original training set which represents the number of classifiers.Experiments were carried out to construct several homogeneous classifier ensembles using nearest mean classifier, naive Bayes classifier, k-nearest neighbor and linear discriminant analysis as base classifier and majority voting technique as combiner. …”
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Enhanced location and positioning in wimax networks with virtual mimo base station
Published 2015“…Furthermore, a new hybrid algorithm enhancement of mobile station (MS) location estimation by using a single MIMO base station (SMBS) with the virtual base station has been introduced. …”
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16
Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025Subjects:Article -
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Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia
Published 2024“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short-term daily electricity load in Peninsular Malaysia. …”
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Improved bacterial foraging optimization algorithm with machine learning driven short term electricity load forecasting: A case study in Peninsular Malaysia
Published 2024“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short‑term daily electricity load in Peninsular Malaysia. …”
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Relevance detection and summarizing strategies identification algorithm using linguistic measures / Seyed Asadollah Abdiesfandani
Published 2016“…The findings of the study show that, there is a strong relationship between the summary writing proficiency of students and the summarizing strategies that they used. We then develop a new algorithm to address the summarizing strategies identification problem. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…Three algorithms of Linear (PURELIN), hyperbolic tangent sigmoid (TANSIG) and logistic sigmoid (LOGSIG) activation functions were selected for output layer. …”
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