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101
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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102
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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103
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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conferenceObject -
104
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105
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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106
Big Data Energy Management, Analytics and Visualization for Residential Areas
Published 2020“…A high-speed distributed computing cluster based on commodity hardware with efficient big data mathematical algorithm is employed in this work. …”
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107
Exploring Semi-Supervised Learning Algorithms for Camera Trap Images
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doctoralThesis -
108
An efficient approach for textual data classification using deep learning
Published 2022“…Textual data contains much useless information that must be pre-processed. …”
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109
Bee colony algorithm for assigning proctors to exams. (c2013)
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masterThesis -
110
Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
Published 2024“…The proposed method, named Eye-means, emulates the natural ocular process of estimating initial centroids. To achieve this goal, supervised machine learning was employed to train models on graphs with labeled data points, where each graph contains a set of points and a label indicating the centroid determined by K-means. …”
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masterThesis -
111
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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112
An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study
Published 2024“…For cases in which Ornge air services and land ambulance medical transport were both involved in a patient transport process, data were merged and time intervals of the transport journey were determined. …”
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113
Convergence and steady-state analysis of the normalized least mean fourth algorithm
Published 2007article -
114
Convergence and steady-state analysis of the normalized least mean fourth algorithm
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115
The buffered work-pool approach for search-tree based optimization algorithms
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conferenceObject -
116
Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data
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doctoralThesis -
117
Customs Trade Facilitation and Compliance for Ecommerce using Blockchain and Data Mining
Published 2021“…An integrated web application is developed to mock up the end-to-end process in ecommerce. 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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118
Machine Learning Techniques for Pharmaceutical Bioinformatics
Published 2018“…A predictive model is developed to predict drug indication as well as to predict new DDIs using multiple machine learning algorithms. This dissertation presents a case study of predicted anti-cancer activity for 38 drugs. …”
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The role of Reinforcement Learning in software testing
Published 2023“…However, for some complex software testing scenarios, neither supervised nor unsupervised machine learning techniques were adequate. As such, researchers applied Reinforcement Learning (RL) techniques in some cases. …”