Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

“…BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”

An algorithm for solving bond pricing problem by Dibeh, Ghassan

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Multiclass feature selection with metaheuristic optimization algorithms: a review by Abu Zitar, Raed

“…Datasets can be classified using various methods. Nevertheless, metaheuristic algorithms attract substantial attention to solving different problems in optimization. …”
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Design of acoustic absorbing metasurfaces using a data-driven approach by Hamza Baali (14603380)

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Genetic Algorithm Analysis using the Graph Coloring Method for Solving the University Timetable Problem by Haraty, Ramzi A.

“…Genetic algorithms were successfully useful to solve many optimization problems including the university Timetable Problem. …”
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An evolutionary algorithm for solving the geometrically constrained site layout problem by Zouein, P.

“…This paper presents an investigation of applying an evolutionary approach to optimally solve the aforementioned layout problem. The proposed algorithm is two-phases: an initialization phase that generates an initial population of layouts through a sequence of mutation operations, and a reproduction phase that evolve the layouts generated in phase one through a sequence of genetic operations aiming at finding an optimal layout. …”
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Efficient convex-elastic net algorithm to solve the Euclideantraveling salesman problem by Al-Mulhem, M.

“…This paper describes a hybrid algorithm that combines an adaptive-type neural network algorithm and a nondeterministic iterative algorithm to solve the Euclidean traveling salesman problem (E-TSP). …”
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Modified clarke wright algorithms for solving the realistic vehicle routing problem by Shour, Amina

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A discrete-time learning control algorithm by Saab, Samer S.

“…A discretized version of the D-type learning control algorithm is presented for a MIMO linear discrete-time system. …”
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Genetic Algorithm for Solving Site Layout Problem with Unequal-Size and Constrained Facilities by Zouein, P. P.

“…This paper presents an investigation of the applicability of a genetic approach for solving the construction site layout problem. This problem involves coordinating the use of limited site space to accommodate temporary facilities so that transportation cost of materials is minimized. …”
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Artificial neural network algorithms. (c1999) by Ramadan, Samer N.

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Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

“…The network can then predict the solution of the problem for a varying range of parameters. The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. …”

Metaheuristic Optimization Algorithms for Training Artificial Neural Networks by Mansour, Nashat

“…The Cuckoo Search (CS) algorithm is a recently developed meta-heuristic optimization algorithm which is suitable for solving optimization problems. …”
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A stochastic iterative learning control algorithm with application to an induction motor by Saab, Samer S.

“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the learning gain matrix of a P-type ILC for linear discrete-time varying systems with arbitrary relative degree. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm by Nasr, Joshua

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Discrete-time learning control algorithm for a class of nonlinear systems by Saab, Samer S.

“…Applies a discrete-time learning algorithm to a class of discrete-time varying nonlinear system. …”
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Teaching–learning-based optimization algorithm: analysis study and its application by Abualigah, Laith

“…The teaching–learning-based optimization (TLBO) algorithm is a novel nature-based optimization approach that has attracted a lot of interest from researchers because of its great capacity to handle optimization problems. …”
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Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm by Nasser, Youssef

“…Unsupervised machine learning is a powerful technique for performing clustering, which involves identifying patterns or similarities within a dataset and grouping them into distinct clusters or subgroups. …”
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Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm by Noor Habib Khan (22224775)

“…<p dir="ltr">The present study introduces a nature inspired improved liver cancer algorithm (ILCA) for solving the non‐convex engineering optimization issues. …”

A discrete-time stochastic iterative learning control algorithm for a class of nonlinear systems by Saab, S. S.

“…This article presents a stochastic algorithm that computes the learning gain matrix of a “D-type iterative learning control (ILC) algorithm for a class of discrete-time varying nonlinear systems with linear input/output actions having relative degree one. …”
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