Search Results - (( using simulation study algorithm ) OR ( based classification learning algorithm ))
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification
Published 2016“…Thus, this study investigates the use of Bat algorithm along with back-propagation neural network (BPNN) algorithm in-order to gain optimal weights to solve the local minima problem and also to enhance the convergence rate. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…At first, a peak classification algorithm is developed based on the general following processes including peak candidate identification, feature extraction, and classification. …”
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A comparative study and simulation of object tracking algorithms
Published 2020“…This article introduces the popular object tracking algorithms, from common problems in object tracking to the classification of algorithms: Early classic trackingalgorithms, tracking algorithms based on kernel correlation filtering, and tracking algorithms based on deep learning. …”
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Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction
Published 2024“…Overall, the proposed fuzzy rule-based diabetes diagnosis and level of care fuzzy model works well with most of the machine learning algorithms tested. …”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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The impact of fuzzy discretization�s output on classification accuracy of random forest classifier
Published 2020“…Random Forest is known as among the widely used classification algorithms by researchers and machine learning enthusiast in solving classification problems. …”
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Optimal Weighted Learning of PCA and PLS for Multicollinearity Discriminators and Imbalanced Groups in Big Data (S/O: 13224)
“…The designed algorithm was structured in k-fold cross-validation in attempt to minimise the biasness of the classification performance, measured using error rate. …”
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Review of Wheat Disease Classification and Severity Detection Models
Published 2023“…This paper mainly aims to explain deep learning-based wheat diseases identification algorithm, and to discuss the benefits and drawbacks of present wheat disease detection approaches. …”
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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets
Published 2021“…Consequently, the induced decision trees are dominated by the majority class which lack in predictive ability on the rare class. This study proposed an enhanced algorithm called hellingerant-tree-miner (HATM) which is inspired by ant colony optimization (ACO) metaheuristic for imbalanced learning using decision tree classification algorithm. …”
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The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…Hitherto, limited studies have investigated the classification of wink-based EEG signals through TL accompanied by classical Machine Learning (ML) pipelines. …”
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BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK
Published 2011“…The design features of the proposed system are inspired by the human immune system, integrated with pattern recognition nonlinear classification algorithm and machine learning. Firstly, the current intrusions preventions systems, biological innate and adaptive immune systems, autonomic computing and self-healing mechanisms are studied and analyzed. …”
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…The second test evaluates IFS in a controlled study using simulated datasets. Moreover, the third test used ten natural domain datasets obtained from UCI Repository, in about fifteen different experiments, using three to four different Machine Learning Algorithms for performance evaluation. …”
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Simultaneous fault diagnosis based on multiple kernel support vector machine in nonlinear dynamic distillation column
Published 2022“…In the developed MK-SVM algorithm, multilabel approach based on various kernel functions has been utilized for the classification of simultaneous faults. …”
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Fatigue State Detection Through Multiple Machine Learning Classifiers Using EEG Signal
Published 2023“…A preprocessing stage extracts relevant information before applying machine learning algorithms to the signal. Three analytical methods were employed in this study, specifically the Decision Tree, the K-Nearest Neighbors and the Random Forest. …”
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Enhancing land cover classification in remote sensing imagery using an optimal deep learning model
Published 2023“…The current study presents an Improved Sand Cat Swarm Optimization with Deep Learning-based Land Cover Classification (ISCSODL-LCC) approach on the RSIs. …”
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Prognostic Health Management of Pumps Using Artificial Intelligence in the Oil and Gas Sector: A Review
Published 2022“…To further understand its potential, various algorithms and related theories are examined. Based on the examined studies, machine learning shows potential for prognostics and defect diagnosis. …”
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On some methods of feature engineering useful for craniodental morphometrics of rats, shrews and kangaroos / Aneesha Pillay Balachandran Pillay
Published 2024“…RFE was applied to the craniodental measurements of Rattus rattus (R.rattus) data to select the best feature subset for both male and female rats. A comparative study based on machine learning algorithms was also conducted by using all features and the RFE-selected features to classify the R. rattus sample based on the age groups. …”
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Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques
Published 2011“…To validate the research, the researcher presents case study using GLOMOSIM simulation platform with AODV ad hoc routing protocols. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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