Search Results - (( data distribution means algorithm ) OR ( data distribution factor algorithm ))
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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Development of an effective clustering algorithm for older fallers
Published 2022“…The proposed algorithm was developed through the stages of: data pre-processing, feature identification and extraction with either t-Distributed Stochastic Neighbour Embedding (t-SNE) or principal component analysis (PCA)), clustering (K-means clustering, Hierarchical clustering, and Fuzzy C-means clustering) and characteristics interpretation with statistical analysis. …”
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023Conference Paper -
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Development Of Fall Risk Clustering Algorithm In Older People
Published 2020“…The proposed algorithm consists of several stages, includes data pre-processing, feature selection, feature extraction, clustering and characteristic interpretation. …”
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Final Year Project / Dissertation / Thesis -
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Estimation of transformers health index based on condition parameter factor and hidden Markov model
Published 2018“…In this paper, HI was represented as hidden state and the condition parameter factors in the HI algorithm namely Dissolved Gas Analysis Factor (DGAF), Oil Quality Analysis Factor (OQAF) and Furfural Analysis Factor (FAF) were represented as the observable states. …”
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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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Strut-and-tie model for externally bonded CFRP-strengthened reinforced concrete deep beams based on particle swarm optimization algorithm: CFRP debonding and rupture
Published 2017“…It utilized a particle swarm optimization algorithm (PSO), in which the optimal STM of an CFRP-strengthened RC beam was determined by searching for the optimum unknown coefficients (stress distribution and concrete tensile stress reduction factors). …”
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Resource-Efficient Coverage Path Planning for UAV-Based Aerial IoT Gateway
Published 2023“…As a result, the Energy Efficient Coverage Path Planning (EECPP) algorithm has been proposed. The EECPP is composed of two algorithms: the Stop Point Prediction Algorithm using K-Means, and Path Planning Algorithm using Particle Swarm Optimization. …”
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Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization
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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An optimal under frequency load shedding scheme for islanded distribution network / Amalina Izzati Md Isa
Published 2018“…However, the implementation of this technique is feasible for a smart grid distribution system possessing effective communication means, comprehensive monitoring tools and advanced sensors for transferring measurement data and executes load shedding.…”
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Thesis -
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Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation
Published 2024“…The K-means++ clustering algorithm generates candidate bounding boxes, adapting to defects of different sizes and selecting finer features earlier. …”
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Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks
Published 2022“…The previous works assumed that the network environment is evenly and uniformly distributed, ignored anisotropic factors in a real setting. …”
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Thesis -
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Geographic Distribution and Potential Conservation Strategies for the Genus Japonia in Sarawak, Malaysia
Published 2024“…The study aimed to identify these diversity and distribution patterns and to predict habitat suitability for selected Japonia species using the Maximum Entropy algorithm based on bioclimatic data. …”
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Thesis -
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The use of radar-rainfall inputs for quantitative precipitation estimation (QPE) in Klang River Basin / Suzana Ramli
Published 2015“…Thus, the deployment of radar helps to retrieve better rainfall data due to spatial and temporal factors. Radar has the advantages of detecting rainfall amount with higher resolution and covers larger areas. …”
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A new scheduling technique to improve data management in cloud computing
Published 2013“…Data Management is the key factor of Cloud Computing, which is „the right data in the right place at the right time’. …”
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Termite mounds morphometry in predicting groundwater potentiality using geospatial technology
Published 2020“…For termite mounds site suitability, the result revealed that moderate to low elevation, rock cover types that are more susceptible to weathering, cultivated areas and shallow water table are factor classes that influence the distribution of termite mounds. …”
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Prediction of rice biomass using machine learning algorithms
Published 2022“…The TESI retained the features’ original probability distribution in the four datasets. The C-TESI achieved the lowest mean squared error mean percentage (MAEP) on the oil palm (0.60–2.85%), rice (0.77–1.72%), and fertiliser datasets (2.04–2.21%). …”
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Development of mapping methods for seagrass meadows in Malaysia by using landsat images
Published 2015“…Mapping capabilities of Landsat were not tested in different tidal regimes, characterizing seagrass habitats in relation to water turbidity and depth regimes, and understand spatiotemporal dynamics from multi-date images due to lack of appropriate methods and data, including unresolved Scan Line Corrector (SLC)-off data gaps in Landsat 7 Enhanced Thematic Mapper (ETM)+ images. …”
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