Search Results - (( data organization learning algorithm ) OR ( parallel optimization path algorithm ))
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Tool path generation of contour parallel based on ant colony optimisation
Published 2016“…An Ant Colony Optimisation (ACO) method is used to optimize the tool path length because of its capability to find the shortest tool path length. …”
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Minimizing machining airtime motion with an ant colony algorithm
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Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib
Published 2019“…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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A novel large-bit-size architecture and microarchitecture for the implementation of Superscalar Pipeline VLIW microprocessors
Published 2008“…Different adder architectures are investigated for suitability on synthesis implementation of large data bus size adder for efficient usage within the ALU. An adder algorithm using repetitive constructs in a parallel algorithm that allows for efficient and optimal synthesis for large data bus size is proposed as a suitable implementation for the adder within the ALU. …”
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An improved self organizing map using jaccard new measure for textual bugs data clustering
Published 2018“…Considering the unsupervised learning algorithms, Self-Organizing Map (SOM) considers the equally compatible algorithm for clustering, as both algorithms are closely related but different in way they were used in data mining. …”
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An improved self organizing map using jaccard new measure for textual bugs data clustering
Published 2018“…Considering the unsupervised learning algorithms, SelfOrganizing Map (SOM) considers the equally compatible algorithm for clustering, as both algorithms are closely related but different in way they were used in data mining. …”
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Machine learning classifications of multiple organ failures in a malaysian intensive care unit
Published 2024“…This study aims to perform the classification of multiple organ failures using machine learning algorithms based on SOFA score. …”
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Octane number prediction for gasoline blends using convolution neural network / Zhu Yue
Published 2021“…At present, there are many prediction algorithms based on machine learning. According to the "80/20 rule" for building machine learning model, 80% of the time is spent of finding, cleaning, and organizing data, while the remaining 20% for training of the machine learning model. …”
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Underwater Image Recognition using Machine Learning
Published 2024“…It encompasses the procedure for feeding algorithms information to create the algorithms realize patterns in the data and then increase the performance of the algorithms. …”
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Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit
Published 2025“…This study aims to perform the classification of multiple organ failures using machine learning algorithms based on SOFA score. …”
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Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning
Published 2019“…Other types of the ART-based topological clustering algorithms have been developed, however, these algorithms have various drawbacks such as a large number of parameters, sensitivity to noisy data. …”
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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif
Published 2014“…Data mining is a widely used approach for knowledge discovery in machine learning. …”
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Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization / Mohd Norhisham Razali ... [et al.]
Published 2023“…Future research can explore more advanced machine learning algorithms, incorporate time-series analysis for temporal dependencies, and expand data collection from diverse organizational settings to improve the generalizability of predictive models.…”
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Preserving the topology of self-organizing maps for data analysis: A review
Published 2020“…This paper presents detail explanation on SOM learning algorithm and its applications. Some issues related to SOM's architecture are also discussed, namely the formulation of training data from input samples, and the Best Matching Unit (BMU) identification for better visualization of large datasets, and improvement made to the SOM algorithm.…”
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An artificial immune system model as talent performance predictor / Siti ‘Aisyah Sa’dan, Hamidah Jantan and Mohd Hanapi Abdul Latif
Published 2016“…To achieve this objective, the research was divided into three phases, which consist of talent data identification and data preparation phase, algorithm development for prototype phase and testing and evaluation phase to identify the most suitable prediction model for talent prediction. …”
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Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm
Published 2015“…The self organizing map (SOM) combined with the K-means algorithm arranged the data based on the relationships of 25 variables. …”
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A 'snowflake' geometrical representation for optimised degree six 3-modified chordal ring networks
Published 2016“…A tree visualisation was constructed based on its connectivity to enable the generation of formulae for optimal diameter and average optimal path lengths. …”
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