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Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment
Published 2023“…The artificial neural network demonstrates a higher prediction accuracy and is used as the system model in the proposed control framework. A robust model predictive control strategy, based on the minimax objective function and particle swarm optimisation algorithm, is developed to handle the uncertainties in the system. …”
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Bee Colony Algorithm for Proctors Assignment.
Published 2015“…The Bee Colony algorithm is a recent population-based search algorithm that mimics the natural behavior of swarms of honey bees during the process of collecting food. …”
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Process Mining over Unordered Event Streams
Published 2020“…This requires online algorithms that, instead of keeping the whole history of event data, work incrementally and update analysis results upon the arrival of new events. …”
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86
An Event-Triggered Robust Attitude Control of Flexible Spacecraft With Modified Rodrigues Parameters Under Limited Communication
Published 2019“…Aligned with these design objectives, a robust event-triggered attitude control algorithm is proposed to regulate the orientation of a flexible spacecraft subjected to parametric uncertainties, external disturbances, and vibrations due to flexible appendages. …”
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Mapping realistic data sets on parallel computers
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Sentiment visualization of correlation of loneliness mapped through social intelligence analysis
Published 2024“…Social media platforms have become a valuable source of data to study this phenomenon.</p><h3>Objectives</h3><p dir="ltr">This paper aims to visualize the frequency of loneliness-related themes and topics in Twitter data. …”
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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition
Published 2021“…Whilst different models are proposed for STLF, they are based on small historical datasets and are not scalable to process large amounts of big data as energy consumption data grow exponentially in large electric distribution networks. …”
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Machine Learning Model for a Sustainable Drilling Process
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95
Data redundancy management for leaf-edges in connected environments
Published 2022“…Major advances in the fields of Internet and Communication Technology (ICT), data modeling/processing, and sensing technology have rendered traditional environments (e.g., cities, buildings) more connected. …”
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96
Recent Advances of Chimp Optimization Algorithm: Variants and Applications
Published 2023“…Chimp Optimization Algorithm (ChOA) is one of the recent metaheuristics swarm intelligence methods. …”
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97
A hybrid graph representation for recursive backtracking algorithms
Published 2017“…The performance of these algorithms often suffers from the increasing number of graph modifications, such as deletions, that reduce the problem instance and have to be “taken back” frequently during the search process. …”
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The effects of data balancing approaches: A case study
Published 2023“…Our results showed that the replacement method was effective, and LogisticRegression combined with the oversampling algorithms SMOTE or ADASYN, GaussianProcessClassifier with the oversampling algorithm SMOTE, and LinearDiscriminantAnalysis were the best performing models after log transformation of the dataset was followed by Recursive Feature Elimination.…”
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Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information
Published 2019“…In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. …”
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100
A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition
Published 2025“…A range of machine learning (ML) methods can be used to recognize facial expressions based on data from small to large datasets. Random Forest (RF) is simpler and more efficient than other ML algorithms. …”