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modeling algorithm » scheduling algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
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data modeling » data models (Expand Search), spatial modeling (Expand Search)
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Using Machine Learning Algorithms to Forecast Solar Energy Power Output
Published 2025“…The data forecasting horizon used was a 24-h window in steps of 30 min. …”
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83
Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms
Published 2023“…Eighteen classification models were built using different classification algorithms such as Gaussian Naive Bais, Logistic Regression, k-nearest neighbors, Random Forest, and Decision Tree. …”
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84
Design of A Theoretical Framework For A Real-Time Fire Evacuation Guidance System
Published 2020Get full text
doctoralThesis -
85
A method for test scheduling using an evolutionary approach. (c2000)
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masterThesis -
86
A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs†
Published 2010“…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and k colours. …”
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87
Auto-indexing Arabic texts based on association rule data mining. (c2015)
Published 2015“…In this work, we propose a new model to enhance auto-indexing Arabic texts. Our model denotes extracting new relevant words by relating those chosen by the previous classical methods, to new words using data mining rules. …”
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masterThesis -
88
Customs Trade Facilitation and Compliance for Ecommerce using Blockchain and Data Mining
Published 2021“…Additionally, the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology is employed for modelling the two proposed clustering algorithms to identify transactional risks. …”
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89
Predicting COVID-19 cases using bidirectional LSTM on multivariate time series
Published 2022“…Unlike other forecasting techniques, our proposed approach first groups the countries having similar demographic and socioeconomic aspects and health sector indicators using K-means clustering algorithm. The cumulative case data of the clustered countries enriched with data related to the lockdown measures are fed to the bidirectional LSTM to train the forecasting model. …”
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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark
Published 2021“…The paper proposes a concurrent job scheduling algorithm in a multi-energy data source environment using Apache Spark. …”
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93
Real-Time Path-Planning using Depth/INS Sensor Fusion for Localization
Published 2019Get full text
doctoralThesis -
94
Just-in-time defect prediction for mobile applications: using shallow or deep learning?
Published 2023“…In this research, we evaluate the performance of traditional machine learning algorithms and data sampling techniques for JITDP problems and compare the model performance with the performance of a DL-based prediction model. …”
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95
Forecasting the nearly unforecastable: why aren’t airline bookings adhering to the prediction algorithm?
Published 2021“…The resulting model achieves an 89% predictive accuracy using historical data. …”
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96
Wearable Real-Time Heart Attack Detection and Warning System to Reduce Road Accidents
Published 2019“…It was observed that the linear classification algorithm was not able to detect heart attack in noisy data, whereas the support vector machine (SVM) algorithm with polynomial kernel with extended time–frequency features using extended modified B-distribution (EMBD) showed highest accuracy and was able to detect 97.4% and 96.3% of ST-elevation myocardial infarction (STEMI) and non-ST-elevation MI (NSTEMI), respectively. …”
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97
Deploying model obfuscation: towards the privacy of decision-making models on shared platforms
Published 2024“…The implementation nuances involve data and model sharing among allies and partners working on the same domain. …”
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A hybrid distributed test generation method using deterministic and genetic algorithms
Published 2017“…The algorithm is parallelized based on a cluster of workstations using the message passing interface (MPI) library. …”
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100