Search Results - (( parameter implementation learning algorithm ) OR ( parameter evaluation method algorithm ))
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An improved back propagation leaning algorithm using second order methods with gain parameter
Published 2018“…Back Propagation (BP) algorithm is one of the oldest learning techniques used by Artificial Neural Networks (ANN). …”
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…The methodology used includes data collection, preprocessing, and algorithm implementation with evaluation using crossvalidation techniques. …”
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Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…Recently, deep learning methods have significantly sharpened the cutting edge of learning algorithms in a wide range of artificial intelligence tasks. …”
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis
Published 2022“…However, different clustering algorithms have different parameters that need to be specified. …”
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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7
Restoration of blurred images using geometric and chebichef moments / Ahlad Kumar
Published 2016“…Once the blur parameters are estimated, image restoration of the proposed method is carried out using split Bregman algorithm. …”
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8
Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…Three major problems are encountered when designing metaheuristics; the first problem is balancing exploration with exploitation capabilities (which leads to premature convergence or trapping in the local minima), while the second problem is the dependency of the algorithm on the controlling parameters, which are parameters with unknown optimal values. …”
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9
Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…For the proposed technique of the FID3-DBD algorithm, the continuous and discrete (integer) attributes would be defined in the linguistic values of the fuzzy sets, and the FUZZYDBD method is being used to set up the fuzzy sets’ parameters. …”
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10
Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…After evaluating the results of these algorithms, a hybrid Artificial Neural Network-based Imperial Competitive Algorithm (ANN-ICA) was presented in the deployment step of the proposed methodology to identify the structural damage of illustrative structures. …”
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Prediction Of Petroleum Reservoir Properties Using Nonlinear Feature Selection And Ensembles Of Computational Intelligence Techniques
Published 2015“…The algorithms were implemented with optimized tuning parameters and validated with real-life porosity and permeability datasets obtained from diverse and heterogeneous petroleum reservoirs after they have passed on testing them with a benchmark dataset from the UCI Machine Learning Repository. …”
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Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach
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Applications of contemporary artificial intelligence technology in forensic odontology as primary forensic identifier : A scoping review
Published 2022“…Conclusion: The reviewed articles demonstrate that machine learning techniques are reliable for studies involving continuous features such as morphometric parameters. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…The framework uses machine learning methods, including classification, clustering, feature selection, and parameter tuning, to improve accuracy and reliability. …”
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Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region
Published 2025“…This study employs various machine learning and deep learning algorithms, specifically Random Forest (RF), Artificial Neural Network (ANN), and Deep Learning Neural Network (DLNN), to estimate landslide susceptibility in Chamoli district, Uttarakhand, India?…”
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Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach
Published 2022“…Deep Neural Network (DNN) is a combination method between two different subfields of Machine Learning application, including the Artificial Neural Network (ANN) and Deep Learning (DL). …”
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Context enrichment framework for sentiment analysis in handling word ambiguity resolution
Published 2024“…Machine learning algorithms are deployed to perform sentiment classification. …”
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Model Prediction Of Pm2.5 And Pm10 Using Machine Learning Approach
Published 2021“…Based on the feature selection, model development was built with and without input selection using the Nonlinear Autoregressive with Exogeneous Input (NARX) neural network model which made use of 10 number of hidden neurons and 2 number of delays, implementing Levenberg-Marquardt as training algorithm. …”
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