Search Results - ((machine algorithm) OR (new algorithm))
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Propose a New Machine Learning Algorithm based on Cancer Diagnosis
Published 2018“…In this review, we focus on the current status of machine learning applications in cancer research, also propose a new algorithm Fast Learning Network to work based on cancer research.…”
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E4ML: Educational Tool for Machine Learning
Published 2003“…There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.…”
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Using the bees algorithm to optimise a support vector machine for wood defect classification
Published 2007“…This paper describes a new application of the Bees Algorithm to the optimization of a Support Vector Machine (SVM) for the problem of classifying defects in plywood. …”
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Development of Simulated Annealing Based Scheduling Algorithm for Two Machines Flow Shop Problem
Published 2015“…Viewing as optimization problem and focusing on two machines, this research aims to develop a new Simulated Annealing based scheduling algorithm, called SA2M, for flow shop problem. …”
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Machining optimization using Firefly Algorithm / Farhan Md Jasni
Published 2020“…Based on the previous research on the success of Firefly Algorithm, this approach will be able to optimize the machining parameter of milling operation. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…Therefore, in this study a new optimized variant of machine learning algorithms is presented. …”
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Development of New Genetic Algorithm Software for Blow Mould Process
Published 2008“…This software directly reduces in term of machining cost. …”
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A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification
Published 2023“…Algorithms; Benchmarking; E-learning; Knowledge acquisition; Learning systems; Pattern recognition; Bench-mark problems; Efficient learning; Extreme learning machine; Fuzzy ARTMAP; Generalization performance; Online learning; Online learning algorithms; Online sequential extreme learning machine; Learning algorithms…”
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The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement
Published 2025Subjects:Article -
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter
Published 2017“…This paper presents a hybrid classification algorithm, ACOMV-SVM which is based on ant colony and support vector machine.A new direction for ant colony optimisation is to optimise mixed (discrete and continuous) variables.The optimised variables are then feed into selecting feature subset and tuning its parameters are two main problems of SVM.Most approaches related to tuning support vector machine parameters will discretise the continuous value of the parameters which will give a negative effect on the performance. …”
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Improved rsync algorithm to minimize communication cost using multi-agent systems for synchronization in multi-learning management systems
Published 2017“…Remote file synchronization (RFS) is based on updating the outdated version of a file that resides on one machine to be similar to the new version of the updated file in another machine at a minimum computation time (cost). …”
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An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective
Published 2023“…However, there needs to be more research examining the role of interactive methods in multiobjective optimisation problems. To integrate machine learning and human interactions, this paper develops a new three-stage interactive algorithm in business analytics, called the interactive Nautilus-based algorithm, to address complex problems. …”
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New bio-inspired barnacle optimizers based least-square support vector machine for time-series prediction of pandemic outbreaks
Published 2024“…These findings underscore the efficacy of GBO and its competitive edge in achieving accurate time-series predictions when compared to a diverse set of algorithms. The groundbreaking outcome of this research lies in the transformative impact of enhanced BMO variants, along with the innovative new bio-inspired GBO algorithm and GBO-LSSVM models. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023Subjects:Conference paper -
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Adaptive intelligence job online scheduling within dynamic grid environment based on gridsim
Published 2008“…The idea behind the adaptive job scheduling algorithm is the hybrid algorithms that consist of Ant Colony Optimization (ACO) and Tabu algorithms. …”
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Detection and classification of conflict flows in SDN using machine learning algorithms
Published 2021“…As a result, this paper presents several machine learning algorithms that include Decision Tree (DT), Support Vector Machine (SVM), Extremely Fast Decision Tree (EFDT) and Hybrid (DT-SVM) for detecting and classifying conflicting flows in SDNs. …”
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…The average size of feature subset is eight for the ACOR-SVM and IACOR-SVM algorithms and four for the ACOMV-R and IACOMV-R algorithms. …”
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An automated strabismus classification using machine learning algorithm for binocular vision management system
Published 2023“…To overcome these limitations, a machine learning algorithm, which is a case-based reasoning, is developed to automate the strabismus classification. …”
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Proceeding Paper
