Search Results - ((detection algorithm) OR (((function algorithm) OR (prediction algorithm))))
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1
A comparative analysis of machine learning algorithms for diabetes prediction
Published 2024“…The study contributes insights into the importance of pre-processing and feature selection in improving algorithm performance. The findings have implications for developing accurate predictive models and improving diabetes detection.…”
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2
Accuracy and performance analysis for classification algorithms based on biomedical datasets
Published 2021“…This paper presents and analyzes five different machine learning (ML) algorithms: Function-based Neural Network (MLP) algorithm. …”
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3
Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…In summary, this study advances the field by delivering an effective, optimized predictive algorithm for early heart disease detection, thereby offering valuable insights that could enhance healthcare outcomes, support proactive cardiovascular risk management, and pave the way for future innovations in personalized medicine…”
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4
Anomaly detection in ICS datasets with machine learning algorithms
Published 2021“…The machine learning algorithms have been performed with labeled output for prediction classification. …”
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Benchmarking in silico tools for the functional assessment of DNA variants using a set of strictly pharmacogenetic variants
Published 2019“…Predictive algorithms are important tools for translating genomic data into meaningful functional annotations. …”
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Snake detection system using convolutional neural network / Muhammad Danial Ahmad Tarmizi
Published 2020“…This project uses Convolutional Neural Network algorithms which is one the best algorithms for image processing. …”
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Early prediction of acute kidney injury using machine learning algorithms
Published 2018“…Thus, the main aim of this manuscript is to compare the performance of well-known machine learning (ML) algorithms to a problem in the domain of medical diagnosis and analyze their efficiency in predicting the results. …”
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Proceeding Paper -
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A study on component-based technology for development of complex bioinformatics software
Published 2004“…Othman develop a predictive algorithm named R-HCSVM to predict protein local structure that works with following steps. …”
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Monograph -
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…Different types of metaheuristic optimization tools have their unique features which vary from others and hence lead to different suitability in the particular application. Two metaheuristic algorithms i.e., Harmony Search (HS) and Gravitational Search Algorithm (GSA), are selected to integrate separately with a Radial Basis Function Network with Dynamic Decay Adjustment (RBFN-DDA) to perform condition monitoring in industrial processes. …”
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10
Analysis of banana plant health using machine learning techniques
Published 2024“…This manuscript examines the prediction and detection of diseases in banana leaves, exploring various diseases, machine learning algorithms, and methodologies. …”
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Smart fall detection by enhanced SVM with fuzzy logic membership function
Published 2023“…Because combining these two algorithms is not an easy task, we leverage SVM with a kernel comprised of a fuzzy membership function and thus build a new model known as FSVM. …”
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Fish Motion Trajectories Detection Algorithm Based on Spiking Neural Network (S/O: 12893)
Published 2017“…The spike encoding was used for feature extraction. The algorithm for this learning model adopted the reward-modulated STDP. …”
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Monograph -
13
Design and implementation of multimedia digital matrix system
Published 2005“…Due to the issues of signal integrity in high-speed digital design, a new adaptive channel synchronization algorithm has been developed. The algorithm, named as hybrid-reset algorithm utilizes the nature of asynchronous reset to compensate the drawback of synchronous counter for phase detection. …”
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14
Prostate cancer prediction using feedforward neural network trained with particle swarm optimizer
Published 2022“…The experimental results are evaluated using the mean, best, worst, and standard deviation (Std.) values of the fitness function and compared with other learning algorithms for FNNs, including the Salp Swarm Algorithm (SSA) and Sine Cosine Algorithm (SCA). …”
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15
Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…Classification and prediction are the functions provided by the data mining techniques that suit in EEG signal processing. …”
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16
Defect green coffee bean detection using image recognition and supervised learning
Published 2022“…Therefore, in this research project, the process will be conducted by using an image classifier with the model of a machine learning algorithm which the candidates comprise of Support Vector Machine, k-Nearest Neighbour and Decision Tree. k-nearest neighbour has the highest F1-score (0.51) than the other two algorithms (Support Vector Machine: 0.50, and Decision Tree: 0.48). …”
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Academic Exercise -
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Automatic spike detection and correction for outdoor machine vision: application to tomato
Published 2011“…Then by the use of mean shift color segmentation algorithm, the spiky pixels on the surface of tomato are spotted. …”
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Cardiac abnormality prediction using tansig based multilayer perceptron
Published 2021“…At the end of the study, it showed the MLP network which by BR training algorithm gave the highest accuracy prediction (94.04%), followed by LM (92.95%) and BP (88.77%). …”
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Terahertz sensing analysis for early detection of ganoderma boninense disease using near infrared (NIR) spectrometer
Published 2023“…Therefore, a DT-based predictive analytic on leaves NIR spectral reference data is developed for real-time detection of G. boninense infection. …”
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Thesis -
20
Adapting And Enhancing Hybrid Computational Methods For RNA Secondary Structure Prediction
Published 2011“…This thesis presents a hybrid method to predict the RNA pseudoknot secondary structures by combining detection methods with dynamic programming algorithms.…”
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