Rigorous Phase Equilibrium Calculation Methods for Strong Electrolyte Solutions: The Isothermal Flash by Ilias K. Nikolaidis (9217172)

“…In this way, an augmented function (Lagrange function) is formulated which serves as the basis for the equations that govern phase equilibrium. …”

Application of Red Deer Algorithm in Optimizing Complex functions by Zitar, Raed

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A genetic-based algorithm for fuzzy unit commitment model by Mantawy, A.H.

“…In the implementation for the GA, coding of the UCP solutions is based on mixing binary and decimal representations. …”
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Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids by Khayata, Mohammad Tarek

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A New Genetic-Based Tabu Search Algorithm For Unit Commitment Problem by Mantawy, A. H.

“…This paper presents a new algorithm based on integrating the use of genetic algorithms and tabu search methods to solve the unit commitment problem. …”
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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm by De Rochechouart, Maxence

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Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks by Haris M. Khalid (17017743)

“…To address this issue, a median regression function (MRF)-based state estimation is presented in this paper. …”

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. …”
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Logarithmic spiral search based arithmetic optimization algorithm with selective mechanism and its application to functional electrical stimulation system control by Abu Zitar, Raed

A new genetic algorithm approach for unit commitment by Mantawy, A.H.

“…In the proposed algorithm, coding the solution of the unit commitment problem is based on mixing binary and decimal representations. …”
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Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Mujahid, S.N.

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Process Targeting Of Multi-Characteristic Product Using Fuzzy Logic And Genetic Algorithm With An Interval Based Taguchi Cost Function by Duffuaa, S. O.

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Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach by Sarif, Bambang

“…The search space is too large to be explored by deterministic algorithms. In this paper, a Genetic Algorithm based algorithm for synthesis of MVL functions is proposed. …”
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Consensus-Based Distributed Formation Control of Multi-Quadcopter Systems: Barrier Lyapunov Function Approach by Nargess Sadeghzadeh-Nokhodberiz (16904952)

Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem by Mantawy, A.H.

“…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems by Abualigah, Laith

“…In this paper, a novel hybrid optimization algorithm is proposed to solve various benchmark functions, which is called IPDOA. …”
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Attacking ElGamal based cryptographic algorithms using Pollard's rho algorithm by El-Kassar, A. N.

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Integrating Genetic Algorithms, Tabu Search, And Simulated Annealing For The Unit Commitment Problem by Montawy, A.H.

“…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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Metaheuristic Algorithm for State-Based Software Testing by Haraty, Ramzi A.

“…SA evolves a solution by minimizing an energy function that is based on testing objectives such as coverage, diversity, and continuity of events. …”
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Belief selection in point-based planning algorithms for POMDPs by Azar, Danielle

“…Current point-based planning algorithms for solving partially observable Markov decision processes (POMDPs) have demonstrated that a good approximation of the value function can be derived by interpolation from the values of a specially selected set of points. …”
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