Search Results - (( variable missing learning algorithm ) OR ( leave application optimization algorithm ))
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Tangible interaction learning model to enhance learning activity processes among children with dyslexia
Published 2024“…To find optimum variables, Machine Learning approach needs to be utilized. …”
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Intelligent imputation method for mix data-type missing values to improve data quality
Published 2024“…To find optimum variables, Machine Learning approach needs to be utilized. …”
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High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor
Published 2024“…The Principal Component Analysis (PCA) technique was employed to choose relevant environmental variables as input for the machine learning model, and various imputation methods were utilized to manage missing data, such as mean imputation and the KNN algorithm. …”
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Predicting the optimum compositions of a transdermal nanoemulsion system containing an extract of Clinacanthus nutans leaves (L.) for skin antiaging by artificial neural network mo...
Published 2017“…Hence, ANN was found to be an effective tool for optimizing the nanoemulsion containing C. nutans leaves extract with efficacy to protect collagen from breakdown.…”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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Automated recognition of Ficus deltoidea using ant colony optimization technique
Published 2013“…At first, through image processing specified features are extracted from the Ficus deltoidea leaves such as vein, morphology and texture features and they construct a search space to be chosen for the optimal subset features that is selected by ACO algorithm as support vector machine (SVM) classify them. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Most of the existing plant identification methods are based on both the global shape features and the intact plant leaves. However, for the non-intact leaves such as the deformed, partial and overlapped leaves that largely exist in practice, the global shape features are not efficient and these methods are not applicable.The dried leave parts and noise can degrade identification results and affect the quality of the extracted features which lead to poor classification results. …”
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Expansion power system transmission using ant colony optimization: article / Izzataswad Ibrahim
Published 2015“…This paper presents an application of ant colony optimization (ACO) to optimization the expansion transmission in power system. …”
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Recent advances in meta-heuristic algorithms for training multilayer perceptron neural networks
Published 2025“…The study also highlights bibliometric trends, identifies underexplored areas such as adaptive and hybrid algorithms, and emphasizes the practical application of MHAs in optimizing ANN performance. …”
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Predicting wheat yield from 2001 to 2020 in Hebei Province at county and pixel levels based on synthesized time series images of Landsat and MODIS
Published 2024“…In our study, the synthesized images of Landsat and MODIS were used to provide remote sensing (RS) variables, which can fill the missing values of Landsat images well and cover the study area completely. …”
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State of charge estimation for lithium-ion battery based on random forests technique with gravitational search algorithm
Published 2023Conference Paper -
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Dynamic area coverage algorithms for static and mobile wireless sensor network environments using voronoi techniques
Published 2011“…This thesis focuses on developing Voronoi Tessellation-based Coverage Optimization Algorithms for Static and Mobile Wireless Sensor Networks, where a large number of static nodes are supported by few mobile nodes in carrying out the sensing task. …”
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Modeling forest fires risk using spatial decision tree
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