Physical optimization algorithms for mapping data to distributed-memory multiprocessors حسب Mansour, Nashat

"…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …"
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Using genetic algorithms to optimize software quality estimation models حسب Azar, Danielle

"…In the first approach, we assume the existence of several models, and we use a genetic algorithm to combine them, and adapt them to a given data set. …"
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Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994) حسب Kawash, Jalal Y.

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Second-order conic programming for data envelopment analysis models حسب Mourad, Nahia

"…This paper constructs a second-order conic optimization problem unifying several DEA models. Moreover, it presents an algorithm that solves the former problem, and provides a MATLAB function associated with it. …"
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Efficient Dynamic Cost Scheduling Algorithm for Financial Data Supply Chain حسب Al Sadawi, Alia

"…An iterative dynamic scheduling algorithm (DCSDBP) was developed to address the data batching process. …"
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data حسب Assaf, Ali

"…In this work, we present DG-means, which is a greedy algorithm that performs on distributed sets of data. …"
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices حسب Khawam, Yahya Bader

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Cluster-based anonymity model and algorithm for 1:1 dataset with a single sensitive attribute using machine learning technique حسب J. Jayapradha (21323774)

Information reconciliation through agent controlled graph model. (c2018) حسب Saba, Rita

"…Even though prevention techniques exist, they’re not enough to fully secure the data from malicious activities. Thus, the need for a detection and recovery algorithm to assess the damage and bring the database back to its consistent state in case of an attack. …"
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An ant colony optimization algorithm to improve software quality prediction models حسب Azar, D.

"…For this purpose, software quality prediction models have been extensively used. However, building accurate prediction models is hard due to the lack of data in the domain of software engineering. …"
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A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models حسب Azar, Danielle

"…In this paper, we present a genetic algorithm that adapts such models to new data. We give empirical evidence illustrating that our approach out-beats the machine learning algorithm C4.5 and random guess.…"
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Correlation Clustering with Overlaps حسب Fakhereldine, Amin

"…In other words, data elements (or vertices) will be allowed to be members in more than one cluster instead of limiting them to only one single cluster, as in classical clustering methods. …"
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A combined algorithm based on finite elements and a modified methodof characteristics for the analysis of the corona in wire-ductelectrostatic precipitators حسب Al-Hamouz, Z.M.

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Minimizing Deadline Misses of Mobile IoT Requests in a Hybrid Fog- Cloud Computing Environment حسب Omer, Dalia Fatahelrahman

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Impact of AI and Dynamic Ensemble Techniques in Enhancing Healthcare Services: Opportunities and Ethical Challenges حسب Haseeb Javed (18576340)

الموضوعات:

Graph Computing Systems and Partitioning Techniques: A Survey حسب Tewodros Alemu Ayall (19273717)

الموضوعات:

A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008) حسب Korkmaz, Rita

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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting حسب Mohamed Massaoudi (16888710)

الموضوعات:

The automation of the development of classification models and improvement of model quality using feature engineering techniques حسب Sjoerd Boeschoten (17347045)

"…In this article, we propose a framework that combines feature engineering techniques such as data imputation, transformation, and class balancing to compare the performance of different prediction models and select the best final model based on predefined parameters. …"

UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data حسب Behrouz Ahadzadeh (19757022)

"…<p>Feature selection (FS) is a crucial technique in machine learning and data mining, serving a variety of purposes such as simplifying model construction, facilitating knowledge discovery, improving computational efficiency, and reducing memory consumption. …"