Search Results - (( based optimization modified algorithm ) OR ( pattern optimization techniques algorithm ))
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Recently, various techniques based on different algorithms have been developed. …”
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Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making
Published 2024“…Moreover, the introduction of the novel modified stacked ensemble statistical learning-based algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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Dynamic reconfiguration of large-scale PV plant using based on specified switching matrix and genetic algorithm to mitigate partial shading
Published 2023“…A comparative study on performance analysis such as mismatch losses, fill factor, power loss and percentage power enhancement, for TCT configuration, SuDoKu, Competence Square, Two Phase, Particle Swarm Optimization, Genetic Algorithm, Modified Harris Hawks Optimizer and the proposed technique was carried out for each shading case. …”
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Facial image retrieval on semantic features using adaptive mean genetic algorithm
Published 2019“…The performance matrix of the AMGA was compared to those of particle swarm optimization algorithm (PSO) and genetic algorithm (GA) and found to perform better; thus, proving its efficiency.…”
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Analyzing enrolment patterns: Modified stacked ensemble statistical learning-based approach to educational decision-making
Published 2024“…Moreover, the introduction of the novel modified stacked ensemble statistical learning-based algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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Image watermarking optimization algorithms in transform domains and feature regions
Published 2012“…The achieved tradeoffs from these techniques between imperceptibility and robustness are controversial.To solve this problem,this study proposes the application of artificial intelligent techniques into digital watermarking by using discrete wavelet transform (DWT) and singular value decomposition (SVD).To protect the copyright information of digital images,the original image is decomposed according to two-dimensional discrete wavelet transform.Subsequently the preprocessed watermark with an affined scrambling transform is embedded into the vertical subband (HLm) coefficients in wavelet domain without compromising the quality of the image.The scaling factors are trained with the assistance of Particle Swarm Optimization (PSO).A new algorithmic framework is used to forecast feasibility of hypothesized watermarked images.In addition,the novelty is to associate the Hybrid Particle Swarm Optimization (HPSO),instead of a single optimization,as a model with SVD.To embed and extract the watermark,the singular values of the blocked host image are modified according to the watermark and scaling factors. …”
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Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment
Published 2017“…During the course of the present work, two fuzzy methods (modified Zimmermanns approach and modified angelovs approach ) and fourmeta-heuristics and hybrid meta heuristics including; simulated annealing (SA), modified simulated annealing (MSA), hybrid modified simulated annealing and simplex downhill (MSASD), hybrid modified simulated annealing and modified particle swarm optimization (MSAPSO) were proposed. …”
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Classification of herbs plant diseases via hierarchical dynamic artificial neural network
Published 2010“…This paper is to propose an unsupervised diseases pattern recognition and classification algorithm that is based on a modified Hierarchical Dynamic Artificial Neural Network which provides an adjustable sensitivity-specificity herbs diseases detection and classification from the analysis of noise-free colored herbs images. …”
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Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making
Published 2023“…Moreover, the introduction of the novel stacked ensemble machine learning algorithm had improved predictive accuracy compared to traditional dichotomous logistic regression algorithms on average, particularly at optimal training-to-test ratios of 70:30, 80:20, and 90:10. …”
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Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network
Published 2019“…In the proposed work, the focused problem is how to reduce the communication energy consumption and to avoid the routing hole problem by optimized routing algorithms. First, a routing hole detection algorithm is proposed prior to designing the routing protocol which decreases about 30 percent energy consumption rate, detection time and detection overhead. …”
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A NOVEL CONSTRUCTION OF VECTOR COMBINATORIAL (VC) CODE FAMILIES AND DETECTION SCHEME FOR SAC OCDMA SYSTEMS
Published 2010“…Secondly, a new detection technique based on exclusive-OR (XOR) logic is developed and compared to the reported detection techniques. …”
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Robust techniques for linear regression with multicollinearity and outliers
Published 2016“…The proposed method is formulated by incorporating robust MM-estimator and the modified generalized M-estimator (MGM) in the LRR algorithm. …”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…Due to the center biased nature of the videos, the HPSO algorithm uses an initial pattern (hexagon-shaped) to speed up the convergence of the algorithm. …”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…In addition, two novel Jaya-based methods namely, the modified Jaya (MJaya) algorithm and quasi-oppositional modified Jaya (QOMJaya) algorithm are proposed to solve different MOOPF problems. …”
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Hybrid of firefly algorithm and pattern search for solving optimization problems
Published 2018“…The pattern search is an optimization algorithm that further optimizes the values obtained in the maximum iterations of standard FA. …”
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Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…This modified algorithm called Modified Multi-Objective Particle Swarm Optimization (M-MOPSO) employs a fixed-sized external archive along with a dynamic boundary-based search mechanism to evolve the population. …”
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