Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks حسب Najam Us Sahar Riyaz (22927843)

"…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R² = 0.05 to 0.99 in a representative thiophene set. …"

A comparative study of five regression testing algorithms حسب Mansour, N.

"…We compare five regression testing algorithms that include: slicing, incremental, firewall, genetic and simulated annealing algorithms. …"
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Simulated Annealing and Genetic Algorithms for Optimal Regression Testing حسب Mansour, Nashat

"…The algorithms are based on an integer programming problem formulation and the program’s control flow graph. …"
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GenDE: A CRF-Based Data Extractor حسب Kayed, Mohammed

"…The experiments show an encouraging result as it outperforms the CSP-based extractor algorithm (95% and 96% of recall and precision, respectively). …"
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Development of an Optimization Algorithm for Internet Data Traffic حسب Misbahuddin, Syed

"…In this paper, an optimization algorithm is proposed to reduce net data traffic, which works at Internet layer in the TCP/IP reference model. …"
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Efficient Approximate Conformance Checking Using Trie Data Structures حسب Awad, Ahmed

الموضوعات: "…Estimation error,Runtime,Computational modeling,Data structures,Approximation algorithms,Encoding,Computational efficiency…"
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An incremental approach for test scheduling and synthesis using genetic algorithms حسب Harmanani, H.

"…The method is based on a genetic algorithm that efficiently explores the testable design space. …"
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Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms حسب Harmanani, H. M.

"…The method is based on a genetic algorithm that efficiently explores the testable design space and finds a sub-optimal test registers assignment for each k-test session. …"
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Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm حسب Odat, Alhaj-Saleh A.

"…This article outlines the input data and partial shading conditions employed in the replication model of Sequential Monte Carlo (SMC)-based tracking techniques for photovoltaic (PV) systems. …"
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A genetic algorithm for corrective retesting. (c1995) حسب Fakih, Khaled A.

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Parametric Estimation From Empirical Data Using Particle Swarm Optimization Method for Different Magnetorheological Damper Models حسب Asan G. A. Muthalif (16888818)

A Tabu Search algorithm for mapping data to multicomputers. (c1997) حسب Diab, Kamal M.

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Intelligent Rapidly-Exploring Random Tree Star Algorithm حسب Ahmed, Khidir Galal Eldin Khidir

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Allocating data to distributed-memory multiprocessors by genetic algorithms حسب Mansour, Nashat

"…We present three genetic algorithms (GAs) for allocating irregular data sets to multiprocessors. …"
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A neural networks algorithm for data path synthesis حسب Harmanani, Haidar M.

"…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …"
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Metaheuristic algorithm for testing web 2.0 applications. (c2012) حسب Zeitunlian, Hratch Michel

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

"…The main advantage of using this technique over the other commonly used methods is that the amplitudes and phases of the array elements can be used mainly to steer the main beam towards the desired signal. …"
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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method حسب Amit Kumar Balyan (18288964)

"…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …"

Trial-based dominance for comparing both the speed and accuracy of stochastic optimizers with standard non-parametric tests حسب Kenneth V. Price (17877002)

"…<p>Non-parametric tests can determine the better of two stochastic optimization algorithms when benchmarking results are ordinal—like the final fitness values of multiple trials—but for many benchmarks, a trial can also terminate once it reaches a prespecified target value. …"

Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System حسب Abu Zitar, Raed

"…It will be used to determine courses learning results based on the empirical knowledge presented. We research and test the design of the right neural networks that achieves our goal. …"
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