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161
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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162
A hybrid graph representation for recursive backtracking algorithms
Published 2017“…The use of efficient data structures is necessary for fast graph modification modules as well as fast take-back procedures. …”
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conferenceObject -
163
Social spider optimization algorithm: survey and new applications
Published 2024“…This survey also studied the main applications of this algorithm in different fields, including medical, mathematical, artificial intelligence, engineering, and data engineering, and how this algorithm affected, impacted, and supported the different fields. …”
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164
(k, l)-Clustering for Transactional Data Streams Anonymization
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conferenceObject -
165
Application of Data Mining to Predict and Diagnose Diabetic Retinopathy
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doctoralThesis -
166
Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices
Published 2025“…Drawing on data from the Smart Cities Index (SCI) and other economic and sustainability competitiveness metrics, the study uses various <u>ML algorithms</u> to categorize cities into <u>performance classes</u>, ranging from high-achieving Class 1 to emerging Class 3 cities. …”
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167
IntruSafe: a FCNN-LSTM hybrid IoMT intrusion detection system for both string and 2D-spatial data using sandwich architecture
Published 2025“…The IoMT manufacturers need to offer their products at a competitive price, which forces them to use simplified architecture, leaving limited and, to some extent, no scope to employ sophisticated cybersecurity algorithms. …”
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168
A comparison of optimization heuristics for the data mapping problem
Published 1997“…In this paper we compare the performance of six heuristics with suboptimal solutions for the data mapping problem of two dimensional meshes that are used for the numerical solution of Partial Differential Equations(PDEs) on multicomputers. …”
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169
Data redundancy management for leaf-edges in connected environments
Published 2022“…Although the sensed data could be useful for various applications (e.g., event detection in cities, energy management in commercial buildings), it first requires pre-processing to clean various inconsistencies (e.g., anomalies, redundancies, missing values). …”
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170
Correlation Clustering via s-Club Cluster Edge Deletion
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masterThesis -
171
Exploring Semi-Supervised Learning Algorithms for Camera Trap Images
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doctoralThesis -
172
Time-varying volatility model equipped with regime switching factor: valuation of option price written on energy futures
Published 2025“…To determine the parameters of the regime switching model and identify when economic states change, we employ the EM algorithm, utilizing real gas futures price data. We validate our closed-form solution for the option pricing through simulations employing the generalized antithetic variates Monte-Carlo technique. …”
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173
A fast exact sequential algorithm for the partial digest problem
Published 2016“…Two types of simulated data, random and Zhang, are used to measure the efficiency of the algorithm. …”
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174
Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach
Published 2006“…The algorithm is tested using 200 randomly generated 2-variable 4-valued functions. …”
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175
Simulated annealing and genetic algorithms for exam scheduling. (c1997)
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masterThesis -
176
Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
Published 2024“…Among these, K-means is widely used for efficiently solving clustering problems. …”
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masterThesis -
177
Second-order conic programming for data envelopment analysis models
Published 2022“…Data envelopment analysis (DEA) is a widely used benchmarking technique. …”
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178
A Scatter search algorithm for exam scheduling. (c2006)
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masterThesis -
179
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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180
Data mining approach to predict student's selection of program majors
Published 2019“…The approach includes a methodology to manage data mining projects, sampling techniques to handle imbalanced data and multiclass data, a set of classification algorithms to predict and measures to evaluate performance of models. …”
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