Search Results - (( loading classification learning algorithm ) OR ( basic optimisation based algorithm ))
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Assessment of cognitive load using multimedia learning and resting states with deep learning perspective
Published 2019“…It is a well-understood fact that the brain activity increases with the increased demand of cognition. The deep learning algorithm based on Pre-trained convolutional neural network (CNN) networks have been used as a transfer learning for the classification of rest and cognitive states and also assessed the cognitive load using brain waves particularly alpha wave. …”
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Detection and classification of conflict flows in SDN using machine learning algorithms
Published 2021“…Moreover, applying machine learning algorithms in the identification and classification of conflicting flows has limitations. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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Daily maximum load forecasting of consecutive national holidays using OSELM-based multi-agents system with weighted average strategy
Published 2023Subjects:Article -
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Fault classification in smart distribution network using support vector machine
Published 2023“…In this paper, a machine-learning algorithm known as Support Vector Machine (SVM) for fault type classification in distribution system has been developed. …”
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Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification
Published 2019“…Furthermore, the Support vector machine (SVM) and Linear discriminant analysis (LDA) machine learning for the hand posture classification based on the EMG signal pattern were investigated and compared in term of classification performance. …”
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Cyberbullying detection: a machine learning approach
Published 2022“…Those algorithms are used in the classification or regression model to predict an input. …”
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Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques
Published 2022“…However, a few overlapped NIRs’ spectral data between healthy and infected samples require for further validation which chemometric and machine learning (ML) classification technique are chosen. …”
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Gender Classification: A Convolutional Neural Network Approach
Published 2016“…Unlike in conventional CNNs, we replace the convolution operation with cross-correlation, hence reducing the computational load. The network is trained using a second-order backpropagation learning algorithm with annealed global learning rates. …”
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Driver behaviour classification: a research using OBD-II data and machine learning
Published 2024“…The relationship between all features and engine speed is analysed to select the optimal features, which include engine speed, vehicle speed, throttle position, and calculated engine load. Then, the proposed model makes use of the K-Means algorithm to create driving behaviour labels whether belong to safe or aggressive - validated by the safety score criteria. …”
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Development of vehicle detection and counting system for traffic analysis using computer vision
Published 2024“…Once the trained weights are ready a deep learning algorithm detection model is applied to detect and draw a bounding box on the vehicles. …”
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Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation
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Local search manoeuvres recruitment in the bees algorithm
Published 2011“…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. The Bees Algorithm (BA) was created specifically by mimicking the foraging behavior of foraging bees in searching for food sources.During the searching, the original BA ignores the possibilities of the recruits being lost during the flying.The BA algorithm can become closer to the nature foraging behavior of bees by taking account of this phenomenon.This paper proposes an enhanced BA which adds a neighbourhood search parameter which we called as the Local Search Manoeuvres (LSM) recruitment factor.The parameter controls the possibilities of a bee extends its neighbourhood searching area in certain direction.The aim of LSM recruitment is to decrease the number of searching iteration in solving optimization problems that have high dimensions.The experiment results on several benchmark functions show that the BA with LSM performs better compared to the one with basic recruitment.…”
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Unit commitment in power system using multi-agent evolutionary programming incorporating priority listing optimisation technique / Muhammad Nazree Che Othman
Published 2013“…The search process then being refined using heuristic EP-based algorithm with multi-agent approach to produce the final solution. …”
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Handover Parameter for Self-optimisation in 6g Mobile Networks: A Survey
Published 2024journal::journal article -
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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A systematic review on emperor penguin optimizer
Published 2021“…To-date, EPO has slowly gaining considerable momentum owing to its successful adoption in many broad range of optimization problems, that is, from medical data classification, economic load dispatch problem, engineering design problems, face recognition, multilevel thresholding for color image segmentation, high-dimensional biomedical data analysis for microarray cancer classification, automatic feature selection, event recognition and summarization, smart grid system, and traffic management system to name a few. …”
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Instance matching framework for heterogeneous semantic web content over linked data environment
Published 2021“…These discovered attributes serve as input to a modified training set generation component, where training sets are generated based on the potential attributes’ clusters. Property alignment check the irregular data associated to the generated sets to optimise the matching performance. …”
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