Search Results - (( variable interactive learning algorithm ) OR ( parallel optimisation based algorithm ))
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Tool path generation of contour parallel based on ant colony optimisation
Published 2016“…The optimisation of tool path length based on ACO algorithm ascertained that the cutting tool remove the uncut line once and able to eliminate the uncut region in the shortest tool path length. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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A 'snowflake' geometrical representation for optimised degree six 3-modified chordal ring networks
Published 2016“…The results of this research are important in developing a routing algorithm for CHR6o3.…”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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Revolutionizing video analytics: a review of action recognition using 3D
Published 2024“…It also addresses the practicalities of implementing action recognition algorithms in real-world situations, which include tools like deep learning frameworks, pre-trained models, open-source libraries, cloud services, GPU acceleration, and evaluation metrics. …”
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A Simulated Annealing-Based Hyper-Heuristic For The Flexible Job Shop Scheduling Problem
Published 2023“…Flexible job shop scheduling problem (FJSP) is a common optimisation problem in the industry. The use of parallel machines allows an operation to be executed on a machine assigned from a set of alternative machines, raising a combination of machine assignment and job sequencing sub-problems. …”
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Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining
Published 2009“…One such method is machine learning, which involves using a computer algorithm to capture hidden knowledge from data. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through the use of Backtracking Search Algorithm (BSA) as an efficient optimization algorithm in learning process of ANFIS approach. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
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Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm
Published 2024“…The optimum parameters were determined according to the design flow, constraints value and mathematical algorithm. Based on MOGA-II analysis, every workflow generated 1600 feasible solutions for optimization that meet the design space requirement. …”
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Support vector machine in precision agriculture: a review
Published 2021“…The Support Vector Machine (SVM) is a Machine Learning (ML) algorithm which may be used for acquiring solutions towards better crop management. …”
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Predicting sea levels using ML algorithms in selected locations along coastal Malaysia
Published 2024“…In consideration of the distinct behavior of machine learning (ML) algorithms, six well-defined ML used were carried out in this study for predicting sea level on a day-to-day basis. …”
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Predicting sea levels using ML algorithms in selected locations along coastal Malaysia
Published 2025“…In consideration of the distinct behavior of machine learning (ML) algorithms, six well-defined ML used were carried out in this study for predicting sea level on a day-to-day basis. …”
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The Effects Of Segmenting And Computational Thinking In Digital Video Courseware On Knowledge Achievement, Self-Efficacy And Motivation Among Students With Different Thinking Style...
Published 2023“…The researcher found significant main and interaction effects of the learner-paced predefined segment on all dependent variables. …”
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Analysis of daytime and nighttime ground level ozone concentrations using boosted regression tree technique
Published 2017“…Sensitivity testing of the BRT model was conducted to determine the best parameters and good explanatory variables. Using the number of trees between 2,500-3,500, learning rate of 0.01, and interaction depth of 5 were found to be the best setting for developing the ozone boosting model. …”
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