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

“…The results obtained show that the introduced algorithm outperforms the deterministic technique based on the direct cover approach [3] in terms of the average number of product terms required to realize a given MVL function.…”
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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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Iterative Least Squares Functional Networks Classifier by Faisal, Kanaan A

“…The study was achieved with only sets of second-order linearly independent polynomial functions to approximate the neuron functions. The results show that this new framework classifier is reliable, flexible, stable, and achieves a high-quality performance. …”
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Optimization of Support Structures for Offshore Wind Turbines using Genetic Algorithm with Domain-Trimming (GADT) by AlHamaydeh, Mohammad

“…The powerful genetic algorithm optimization technique is augmented with an innovative “domain-trimming” modification. …”
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Stochastic evolution algorithm for technology mapping by Al-Mulhem, A.S.

“…Experimental results show that SELF-Map has an overall better performance compared to other algorithms reported in the literature…”
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Tracking analysis of normalized adaptive algorithms by Moinuddin, M.

“…Close agreement between analytical analysis and simulation results is obtained for the case of the NLMS algorithm. The results show that, unlike the stationary case, the steady-state excess-mean-square error is not a monotonically increasing function of the step-size, while the ability of the adaptive algorithm to track the variations in the environment degrades by increasing the frequency offset.…”
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A new reactive power optimization algorithm by Mantawy, A.H.

“…A new implementation for the particle swarm algorithm has been applied. The objective function of the proposed algorithm is to minimize the system active power loss. …”
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LINE SEARCH TECHNIQUES FOR THE LOGARITHMIC BARRIER FUNCTION IN QUADRATIC-PROGRAMMING by Bendaya, M.

“…In this paper, we propose a line-search procedure for the logarithmic barrier function in the context of an interior point algorithm for convex quadratic programming. …”
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A fuzzy basis function network for generator excitation control by Abido, M.A.

“…A fuzzy basis function network (FBFN) based power system stabilizer (PSS) is presented in this paper. …”
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Evolutionary algorithm for predicting all-atom protein structure by Mansour, Nashat

“…This algorithm produces a 3D structure of the whole protein, including back-bone and side-chain atoms, by minimizing the energy function associated with the structure. …”
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Ensemble Deep Random Vector Functional Link Neural Network for Regression by Minghui Hu (2457952)

“…Subsequently, we propose a novel regularization method [boosted factor (BF)], two dRVFLs variants [edRVFL with skip connection (edRVFL-SC) and edRVFL with random skip connections (edRVFL-RSC)] and one strategy [ensemble skip connection edRVFL (esc-edRVFL)] which show significant improvement over the original dRVFL. …”

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

“…This paper presents a new genetic algorithm approach to solve the unit commitment problem in electric power systems. …”
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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.

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Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

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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. A fitness function is constructed from the total operating cost of the generating units plus a penalty term determined due to the fuzzy load and spinning reserve membership functions. …”
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Economic load dispatch using memetic sine cosine algorithm by Abu Zitar, Raed

“…The proposed hybrid algorithm is abbreviated as SCA-βHC which is evaluated using two sets of real-world generation cases: (i) 3-units, two versions of 13-units, and 40-units, with neglected Ramp Rate Limits and Prohibited Operating Zones constraints. …”
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Metaheuristic algorithm for testing web 2.0 applications. (c2012) by Zeitunlian, Hratch Michel

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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

“…For the purpose of predicting ground loss as a function of fruit zone, plant height, fruit production, slope, leaf loss, and blower damage, three ML models i.e., support vector regression (SVR), linear regression (LR), and random forest (RF)—were used. …”

Tracking analysis of the NLMS algorithm in the presence of both random and cyclic nonstationarities by Moinuddin, M.

“…Tracking analysis of the normalized least mean square (NLMS) algorithm is carried out in the presence of two sources of nonstationarities: 1) carrier frequency offset between transmitter and receiver; 2) random variations in the environment. …”
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