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101
Machine Learning Model for a Sustainable Drilling Process
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doctoralThesis -
102
A novel linear time corner detection algorithm
Published 2005“…We have presented a novel scheme for detecting corners of a planner object SRM05. The core of the algorithm is based upon slope analysis. The complexity of our algorithm is linear. …”
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103
A hybrid graph representation for exact graph algorithms
Published 2014“…We investigate practical implementation-based aspects of exact graph algorithms by providing a simple hybrid graph representation that trades space for time to address the said take-back challenge. …”
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conferenceObject -
104
Evolutionary algorithms for VLSI multi-objective netlist partitioning
Published 2006“…For SimE, fuzzy goodness functions are designed for delay and power, and proved efficient. A series of experiments are performed to evaluate the efficiency of the algorithms. …”
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105
A new approach to record clustering for large databases. (c1997)
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masterThesis -
106
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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107
Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts
Published 2022“…So far none addresses the use of Threat Intelligence (IT) data in Ensemble Learning algorithms to improve the detection process, nor does it work as a function of time, that is, taking into account what happens on the network in a limited time interval. …”
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108
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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109
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 -
110
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111
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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112
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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113
A Cyber-Physical System and Graph-Based Approach for Transportation Management in Smart Cities
Published 2021“…To efficiently process the incoming big data streams, the proposed architecture uses the Apache GraphX tool with several parallel processing nodes, along with Spark and Hadoop that ultimately provide better performance against various state-of-the-art solutions. …”
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114
Fuzzy simulated evolution algorithm for multi-objectiveoptimization of VLSI placement
Published 1999“…A fuzzy simulated evolution algorithm is presented for multi-objective minimization of VLSI cell placement problem. …”
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115
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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116
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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117
Bee colony algorithm for assigning proctors to exams. (c2013)
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masterThesis -
118
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 -
119
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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120
Performance Analysis of Artificial Neural Networks in Forecasting Financial Time Series
Published 2013Get full text
doctoralThesis