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modeling algorithm » scheduling algorithm (Expand Search)
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data modeling » data models (Expand Search), spatial modeling (Expand Search)
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Wavelet Analysis- Singular Value Decomposition Based Method for Precise Fault Localization in Power Distribution Networks Using k-NN Classifier
Published 2025“…<p dir="ltr">This article presents a wavelet analysis-singular value decomposition (WA-SVD) based method for precise fault localization in recent power distribution networks using k-NN Classifier. …”
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163
A heuristics for HTTP traffic identification in measuring user dissimilarity
Published 2020“…The study utilizes HTTP request method of GET filtering, to develop a heuristic algorithm to identify user-initiated requests. …”
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164
Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu
Published 2024Subjects: -
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Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Alg...
Published 2023“…In this paper, the scheduling and management framework of an energy hub (EH) is presented with the aim of energy profit maximization in partnership with electricity, natural gas, and district heating networks (EGHNs) considering the coordinated multi-energy management based on the day-ahead market. The optimum capacity of EH equipment, including photovoltaic and wind renewable energy sources, a combined heat and power system (CHP), a boiler, energy storage, and electric vehicles is determined in the day-ahead market using the improved Fick’s law algorithm (IFLA), considering the energy profit maximization and also satisfying the linear network and hub constraints. …”
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Fast Methods Fbr Split Codebooks
Published 2020“…The method is based on a family of fractals called Space-Filling Curves (SFC). …”
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168
Stability improvement of the PSS-connected power system network with ensemble machine learning tool
Published 2022“…The backtracking search algorithm (BSA) based proposed ensemble model is formed by combining three machine learning (ML) techniques, namely the extreme learning machine (ELM), neurogenetic (NG) system, and multi-gene genetic programming (MGGP). …”
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169
Nested ensemble selection: An effective hybrid feature selection method
Published 2023“…The proposed feature selection algorithm differs from the existing filter-wrapper hybrid methods in its simplicity and efficiency as well as precision. …”
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170
Predict Student Success and Performance factors by analyzing educational data using data mining techniques
Published 2022“…The model is then applied to data collected from a reputable university that included 126,698 records with twenty-six (26) initial data attributes. …”
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Tensile Test Optimization Using the Design of Experiment and Soft Computing
Published 2023“…This study employs a hybrid soft computing approach, integrating an adaptive network-based fuzzy inference system (ANFIS), genetic algorithm (GA) optimization, and design of experiments (DOE). …”
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173
Privacy-Preserving Fog Aggregation of Smart Grid Data Using Dynamic Differentially-Private Data Perturbation
Published 2022“…We describe our differentially-private model with flexible constraints and a dynamic window algorithm to maintain the privacy-budget loss in infinitely generated time-series data. …”
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174
Approximation algorithms inspired by kernelization nethods
Published 2017“…Kernelization algorithms in the context of Parameterized Complexity are often based on a combination of reduction rules and combinatorial insights. …”
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Bee Colony Algorithm for Proctors Assignment.
Published 2015“…The results also show that the Bee Colony algorithm outperforms other methods on most subject problems.…”
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177
Scalable Parallel Algorithms for FPT Problems
Published 2006“…Algorithmic methods based on the theory of fixed-parameter tractability are combined with powerful computational platforms to launch systematic attacks on combinatorial problems of significance. …”
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178
Improvement Algorithm for Limited Space Scheduling
Published 2001“…The model characterizes resource space requirements over time and establishes a time-space relationship for each activity in the schedule, based on alternative resource levels. An example illustrates the presented algorithm that generates a feasible space schedule.…”
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179
Oversampling techniques for imbalanced data in regression
Published 2024“…For tabular data we conducted a comprehensive experiment using various models trained on both augmented and non-augmented datasets, followed by performance comparisons on test data. …”
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180
Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE
Published 2018“…We examined different feature selection methods and classification algorithms to find the best prediction model with the highest accuracy. …”
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