Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization by Abu Zitar, Raed

“…The gazelle optimization algorithm (GOA) is a global stochastic optimizer that is straightforward to comprehend and has powerful search capabilities. …”
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Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach by Nargess Sadeghzadeh-Nokhodberiz (16904952)

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Salp swarm algorithm: survey, analysis, and new applications by Abualigah, Laith

“…The behavior of the species when traveling and foraging in the waters is the main source of SSA and MSSA. These two algorithms are put to test on a variety of mathematical optimization functions to see how they behave when it comes to finding the best solutions to optimization problems. …”
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Application of Red Deer Algorithm in Optimizing Complex functions by Zitar, Raed

Subjects: “…RD algorithm…”
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Optimization of Support Structures for Offshore Wind Turbines using Genetic Algorithm with Domain-Trimming (GADT) by AlHamaydeh, Mohammad

“…The two versions of the optimization problem are nonlinearly constrained where the objective function is the material weight of the supporting truss. …”
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Evolutionary algorithm for protein structure prediction by Mansour, Nashat

“…A protein is characterized by its 3D structure, which defines its biological function. The protein structure prediction problem has real-world significance where several diseases are associated with the wrong folding of proteins. …”
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Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994) by Kawash, Jalal Y.

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New enumeration algorithm for regular boolean functions by Nasrallah, Walid F.

“…This paper introduces a new algorithm for enumerating regular Boolean functions. …”
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An improved kernelization algorithm for r-Set Packing by Abu-Khzam, Faisal N.

“…We present a reduction procedure that takes an arbitrary instance of the r -Set Packing problem and produces an equivalent instance whose number of elements is in O(kr−1), where k is the input parameter. Such parameterized reductions are known as kernelization algorithms, and a reduced instance is called a problem kernel. …”
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Learning continuous functions using decision tree learning algorithms by Ibrahim, Ahmed Esmat Mahmoud

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A New Penalty Function Algorithm For Convex Quadratic Programming by Bendaya, M.

“…In this paper, we develop an exterior point algorithm for convex quadratic programming using a penalty function approach. …”
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Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach by Sarif, Bambang

“…None of these algorithms provides absolute optimum results for synthesis of these functions. …”
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Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

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A comparative study of RSA based digital signature algorithms by Haraty, Ramzi A.

“…We implement the classical and modified RSA cryptosystem to compare and to test their functionality, reliability and security. To test the security of the algorithms we implement attack algorithms to solve the factorization problem in Z, Z[<i>i</i>] and F[<i>x</i>]. …”
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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)

“…The role of the proposed quasi oppositional based SMPID controller is to modify the tracking strategy on AC/HVDC interconnected systems while reducing the related cost function. The proposed analysis is established considering the most highly cited, well-known tested and newly expanded swarm-based optimization algorithms (SBOAs), such as Grasshopper Optimization Algorithm (GOA), Grey Wolf Optimization (GWO), Artificial Fish Swarm Algorithm (AFSA), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). …”

Evolutionary algorithms, simulated annealing and tabu search: a comparative study by Youssef, H.

“…Abstract Evolutionary algorithms, simulated annealing (SA), and tabu search (TS) are general iterative algorithms for combinatorial optimization. …”
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Convergence analysis of the variable weight mixed-norm LMS-LMFadaptive algorithm by Zerguine, A.

“…In this work, the convergence analysis of the variable weight mixed-norm LMS-LMF (least mean squares-least mean fourth) adaptive algorithm is derived. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time varying and adapts itself so as to allow the algorithm to keep track of the variations in the environment. …”
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Improved Transportation Model with Internet of Things Using Artificial Intelligence Algorithm by Ayman Khallel Al-Ani (17541447)

“…The proposed method is designed in such a way as to detect the number of loads that are present in a vehicle where functionality tasks are computed in the system. …”

Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems by Abualigah, Laith

Subjects: “…Prairie dog optimization algorithm…”
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Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm by Saima Hassan (14918003)

“…The antecedent part parameters (Gaussian membership function parameters) are encoded as a population of artificial swarm of grasshoppers and optimized using its algorithm. …”