Search Results - (( re evaluation model algorithm ) OR ( whale classification learning algorithm ))
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1
Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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Binary whale optimization algorithm with logarithmic decreasing time-varying modified sigmoid transfer function for descriptor selection problem
Published 2023“…The new Binary Whale Optimization Algorithm is integrated with wrapper feature selection and validated on descriptor selection problem to improve Amphetamine-type stimulants drug classification result. …”
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3
An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. …”
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An improve unsupervised discretization using optimization algorithms for classification problems
Published 2024“…Recognizing the critical role of discretization in enhancing classification performance, the study integrates equal width binning (EWB) with two optimization algorithms: the bat algorithm (BA), referred to as EB, and the whale optimization algorithm (WOA), denoted as EW. …”
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Unleashing the power of Manta Rays Foraging Optimizer: A novel approach for hyper-parameter optimization in skin cancer classification
Published 2025“…Optimizing hyperparameters is crucial for improving the performance of deep learning (DL) models, especially in complex applications like skin cancer classification from dermoscopic images. …”
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Hyperparameter tuned deep learning enabled intrusion detection on internet of everything environment
Published 2022“…Finally, MVO algorithm is exploited with Bidirectional Gated Recurrent Unit (BiGRU) model for classification. …”
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Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh
Published 2019“…The maximum RE obtained is 3.49%. The modelling results revealed that NARX algorithm is the best compared to the used algorithms in term of accuracy. …”
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8
State-Aware re-configuration model for multi-radio wireless Mesh Networks
Published 2017“…The proposed algorithm re-assigns channels to radios and re-configures flows’ routes with aim of achieving a tradeoff between maximizing the network throughput and minimizing the re-configuration overhead. …”
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Information fusion and data augmentation with deep features for a deep learning-based baby cry recognition / Zhang Ke
Published 2024“…Subsequently, a multilayer autoencoder is utilized for feature reduction, and a Support Vector Machine (SVM) is employed to select the transfer learning model with the highest classification accuracy. …”
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10
Optimization Of Fuzzy Logic Controllers With Genetic Algorithm For Two-Part-Type And Re-Entrant Production Systems
Published 2008“…GDF and GSF controllers are evaluated for two test cases namely “two-part-type production line” and “re-entrant production system”. …”
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11
Sustainable renewable energy resources utilization in rural areas
Published 2016“…Results obtained from the transportation model have been validated based on other RE studies in the area. …”
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Sustainable renewable energy resources utilization in rural areas
Published 2016“…Results obtained from the transportation model have been validated based on other RE studies in the area. …”
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Segmentation of MRI brain images using statistical approaches
Published 2011“…Moreover, three improvements of EM for brain MRI segmentation are proposed, which incorporate neighbourhood information in a new manner in the clustering process. In addition, two algorithms for the post-processing of clustering results using user-interaction and the re-evaluation of boundary data in each cluster are presented. …”
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14
A hybrid grey wolf assisted-sparrow search algorithm for frequency control of RE integrated system
Published 2023“…Moreover, the robustness of the proffered method is also evaluated under the random varying load, variation of HPS system parameter, and weather intermittency of RE resources in real-time conditions. …”
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15
ReSTiNet: An efficient deep learning approach to improve human detection accuracy
Published 2023“…The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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Weather prediction system using ANN algorithm / Nur Afiqah Ahmad Sukri
Published 2024“…The data is preprocessed, labeled, and split into training and testing sets which are 80% for training and 20% for testing. The ANN model consists of three layers with ReLU and softmax activations and is trained using the backpropagation algorithm. …”
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ReSTiNet: An Efficient Deep Learning Approach to Improve Human Detection Accuracy
Published 2023“…The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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Analysing the accuracy of machine learning techniques to develop an integrated influent time series model: case study of a sewage treatment plant, Malaysia
Published 2018“…The RE results also prove that the SVM model’s frequency of errors above 10% or below − 10% was greater than the NAR model’s. …”
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ReSTiNet : An efficient deep learning approach to improve human detection accuracy
Published 2023“…The developed ReSTiNet contains fire modules by evaluating their number and position in the network to minimize the model parameters and network size. …”
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An integrated reservoir modelling and evolutionary algorithm for optimizing field development in a mature fractured reservoir
Published 2016“…The second method is automatic optimization using Genetic Algorithm. That depends on the principle of natural selection as proposed by Darwin The genetic program was coupled with the reservoir flow model to re-evaluate the chosen wells at each iteration until obtaining the optimal choice. …”
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