Search Results - (( java adaptation optimization algorithm ) OR ( based learning force algorithm ))
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Active force control with iterative learning control algorithm for a vehicle suspension
Published 2013“…The new control scheme named active force control with iterative learning control algorithm (AFCIL) is complemented by the classic proportionalintegral-derivative (PID) control incorporated and designed as the outermost control loop. …”
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Algorithm animation for cryptanalysis of caesar and hill ciphers / Sapiee Haji Jamel and Giuseppina Sherry Sayan
Published 2009“…Cryptographic algorithms are usually kept secret and the complexity of each algorithm is based on mathematical or statistical analysis. …”
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CAGDEEP : Mobile malware analysis using force atlas 2 with strong gravity call graph and deep learning
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A wheelchair sitting posture detection system using pressure sensors
Published 2024“…Three classification algorithms based on the supervised learning of machine learning, such as support vector machine (SVM), random forest (RF),and decision tree (DT) were used to classify the postures which produced an accuracy of 95.44%, 98.72%,and 98.80%, respectively. …”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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Handgrip strength evaluation using neuro fuzzy approach
Published 2010“…Multilevel Perception neural network utilizes the back-propagation learning algorithm is suitable to discover relationships and patterns in the dataset. …”
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ICS cyber attack detection with ensemble machine learning and DPI using cyber-Kit datasets
Published 2021“…The processed metadata is normalized for the easiness of algorithm analysis and modelled with machine learning-based latest deep learning ensemble LSTM algorithms for anomaly detection. …”
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A review of classification techniques for electromyography signals
Published 2023“…All of the ML classifiers have their own algorithm, special specification, pros and cons based on the available input. …”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han
Published 2018“…The third part of the thesis proposes a novel framework of plant structural learning based on Recurrent Neural Networks (RNN), namely the Plant-StructNet. …”
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End-to-end DVB-S2X system design with deep learning-based channel estimation over satellite fading channels
Published 2021“…In the fourth part a deep learning (DL) algorithm of channel estimation for two fad�ing channel models, Tropical and Temperate in the satellite communication system is presented. …”
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Machine learning application in predicting anterior cruciate ligament injury among basketball players
Published 2025“…Preventing ACL injury is challenging due to their multifactorial nature. Machine learning-based data mining techniques have shown significant potential in identifying risk factors associated with ACL injury. …”
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Developing framework for natphoric computer-aided web-based kansei engineering / Mohammad Bakri Che Haron
Published 2013“…The Natphoric algorithm learns the process done by training with sets of training data from previous KE research works. …”
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Enhanced faster region-based convolutional neural network for oil palm tree detection
Published 2021“…Hence, this research aims to close the research gaps by exploring the deep learning-based object detection algorithm and the classical convolutional neural network (CNN) to build an automatic deep learning-based oil palm tree detection and counting framework. …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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