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141
NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM
Published 2020“…Two new algorithms for fuzzy clustering are presented. Convergence of the proposed algorithms is proved. …”
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142
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143
Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems
Published 2022“…Data-driven algorithms with capabilities to predict the system’s dynamic behavior still need to be developed. …”
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144
Machine Learning Model for a Sustainable Drilling Process
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145
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146
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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147
Evolutionary algorithm for predicting all-atom protein structure
Published 2011“…We present an improved version of a scatter search (SS) algorithm for predicting all-atoms protein structures using a recent energy model. …”
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conferenceObject -
148
Capturing outline of fonts using genetic algorithm and splines
Published 2001“…Hence, it is very difficult to obtain a global optima. We present a method to convert the original problem into a discrete combinatorial optimization problem and solve it by a genetic algorithm. …”
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149
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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150
An improved quorum selection algorithm (IQSA). (c2007)
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masterThesis -
151
Convergence behavior of the normalized least mean fourth algorithm
Published 2000“…The normalized least mean fourth (NLMF) algorithm is presented in this work and shown to have potentially faster convergence. …”
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152
A FAMILY OF NORMALIZED LEAST MEAN FOURTH ALGORITHMS
Published 2020“…In this work, a family of normalized least mean fourth algorithms is presented. Unlike the LMF algorithm, the convergence behavior of these algorithms is independent of the input data correlation statistics. …”
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153
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 -
154
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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155
Indexing Arabic texts using association rule data mining
Published 2019“…The model denotes extracting new relevant words by relating those chosen by previous classical methods to new words using data mining rules. Design/methodology/approach The proposed model uses an association rule algorithm for extracting frequent sets containing related items – to extract relationships between words in the texts to be indexed with words from texts that belong to the same category. …”
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156
A method for data path synthesis using neural networks
Published 2017“…Presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …”
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conferenceObject -
157
Exploring Semi-Supervised Learning Algorithms for Camera Trap Images
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158
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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159
Bee colony algorithm for assigning proctors to exams. (c2013)
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masterThesis -
160
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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