Bee Colony Algorithm for Proctors Assignment. by Mansour, Nashat

“…The Bee Colony algorithm is a recent population-based search algorithm that mimics the natural behavior of swarms of honey bees during the process of collecting food. …”
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Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units by Shanableh, Tamer

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Public health utility of cause of death data: applying empirical algorithms to improve data quality by Sarah Charlotte Johnson (9715415)

Bee colony algorithm for assigning proctors to exams. (c2013) by Taha, Mohamad Kassem

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A modified ant colony algorithm for evolutionary design of digital circuits by Sait, Sadiq M.

“…In this paper, a multiobjective optimization of logic circuits based on a modified ant colony (ACO) algorithm is presented. …”
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Fuzzified ant colony optimization algorithm for efficient combinational circuits synthesis by Sarif, B.A.B.

“…Multiobjective optimization of logic circuits based on a fuzzified ant colony (ACO) algorithm is presented. …”
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POWER SYSTEM STABILIZER FOR MULTI-MACHINE POWER SYSTEMS BASED ON FUZZY LOGIC CONTROL AND ARTIFICIAL BEE COLONY ALGORITHM by unknown

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A combined ant colony optimization and simulated annealing algorithm to assess Stability and fault-proneness of classes based on internal software quality attributes by Azar, Danielle

“…., & Daoud, C. (2016). A Combined Ant Colony Optimization and Simulated Annealing Algorithm to Assess Stability and Fault-Proneness of Classes Based on Internal Software Quality Attributes. …”
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Development of an Optimization Algorithm for Internet Data Traffic by Misbahuddin, Syed

“…The algorithm monitors data repetitions in IP datagram and prepares a compression code in response of this repetition. …”
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Arabic Text Classification Using Modified Artificial Bee Colony Algorithm for Sentiment Analysis: The Case of Jordanian Dialect by Habeeb, Abdallah

“…The second phase, modified the Artificial Bee Colony (ABC) Algorithm, with Upper Confidence Bound (UCB) Algorithm, to promote the exploitation ability for the minimum dimension, to get the minimum number of the optimal feature, then using forward feature selection strategy by four classifiers of machine learning algorithms: (K-Nearest Neighbors (KNN), Support vector machines (SVM), Naïve-Bayes (NB), and Polynomial Neural Networks (PNN). …”
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A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network by Xiaofang Pan (1895950)

Practical single node failure recovery using fractional repetition codes in data centers by Itani, May

“…FR codes consist of a concatenation of an outer maximum distance separable (MDS) code and an inner fractional repetition code that splits the data into several blocks and stores multiple replicas of each on different nodes in the system. …”
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Large language models for code completion: A systematic literature review by Rasha Ahmad Husein (19744756)

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

“…UniBFS exploits the inherent characteristic of binary algorithms-binary coding-to search the entire problem space for identifying relevant features while avoiding irrelevant ones. …”

FarmTech: Regulating the use of digital technologies in the agricultural sector by Imad Antoine Ibrahim (14158998)

A Quasi-Oppositional Method for Output Tracking Control by Swarm-Based MPID Controller on AC/HVDC Interconnected Systems With Virtual Inertia Emulation by Iman M. Hosseini Naveh (16891482)

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Using artificial bee colony to optimize software quality estimation models. (c2015) by Abou Assi, Tatiana Antoine

“…In this thesis, we propose a novel heuristic based on Artificial Bee Colony (ABC) to optimize rule-based software quality prediction models. …”
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Optimization of Piezoelectric Sensor-Actuator for Plate Vibration Control Using Evolutionary Computation: Modeling, Simulation and Experimentation by Asan G. A. Muthalif (16888818)

“…The analytical model is derived based on the Euler-Bernoulli model. The Optimal location of the collocated sensor-actuator, as well as PID controller gains, are determined using Ant Colony Optimization (ACO) technique, then compared with the Genetic Algorithm (GA) and enumerative method (EM). …”

Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

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ANT-colony optimization-direct torque control for a doubly fed induction motor : An experimental validation by Said Mahfoud (17150968)

“…For that reason, this work is focused on the theoretical studies and experimental validation on dSPACE Board DS1104 of the new proposed approach based on PID speed regulation, optimized by the Ant Colony Optimization algorithm (ACO) for DTC, applied to both sides of the Doubly Fed Induction Motor (DFIM), to overcome the previous drawbacks cited at the beginning. …”