Design of adaptive arrays based on element position perturbations حسب Dawoud, M.M.

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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT حسب Dhananjay Bisen (19482454)

Variable Selection in Data Analysis: A Synthetic Data Toolkit حسب Mitra, Rohan

"…Variable (feature) selection plays an important role in data analysis and mathematical modeling. This paper aims to address the significant lack of formal evaluation benchmarks for feature selection algorithms (FSAs). …"
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Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm حسب Nasser, Youssef

"…Among these, K-means is widely used for efficiently solving clustering problems. …"
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem حسب Harmanani, Haidar M.

"…In this paper we present a parallel algorithm to solve the above problem for arbitrary graphs using a Hopfield Neural Network model of computation. …"
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Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm حسب Ayman Khallel Al-Ani (17541447)

"…Furthermore, a route management technique is combined with Artificial Intelligence (AI) algorithm to transmit the data to appropriate central servers. …"

Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing حسب Al Sadawi, Alia

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Parallel physical optimization algorithms for allocating data to multicomputer nodes حسب Mansour, Nashat

"…Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. …"
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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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On the periodic hierarchical Chinese postman problem حسب Muhammed Emre Keskin (19457413)

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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Evolutionary algorithms for state justification in sequential automatic test pattern generation حسب El-Maleh, Aiman H.

"…A common search operation in sequential Automatic Test Pattern Generation is to justify a desired state assignment on the sequential elements. State justification using deterministic algorithms is a difficult problem and is prone to many backtracks, which can lead to high execution times. …"
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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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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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Cluster-based anonymity model and algorithm for 1:1 dataset with a single sensitive attribute using machine learning technique حسب J. Jayapradha (21323774)

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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Using Fractional Bernoulli Wavelets for Solving Fractional Diffusion Wave Equations with Initial and Boundary Conditions حسب Sahlan, Monireh Nosrati

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