Nested ensemble selection: An effective hybrid feature selection method by Kamalov, Firuz

“…Numerical experiments on synthetic and real-life data demonstrate the effectiveness of the proposed method. The NES algorithm achieves perfect precision on the synthetic data and near optimal accuracy on the real-life data. …”
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Inferential sensing techniques in industrial applications by Shakil,, Muhammad

“…System delays are obtained by approximating the model by a linear model. Genetic algorithm, which is a heuristic optimization technique, is used to ¯nd the system delays of the linear model, which are used in dynamical neural network model. …”
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Performance driven standard-cell placement using the geneticalgorithm by Youssef, H.

“…In this paper we present a timing-driven placer for standard-cell IC design. The placement algorithm follows the genetic paradigm. Besides optimizing for area and wire length, the placer minimizes the propagation delays on a predicted set of critical paths. …”
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Vibration suppression in a cantilever beam using a string-type vibration absorber by Issa, Jimmy S.

“…In the first, the spring stiffness, the position of the second attachment point of the string and a preliminary damping constant are calculated using a genetic algorithm approach where the objective function is the maximum displacement on the beam. …”
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Virtual Inertia Support in Power Systems for High Penetration of Renewables—Overview of Categorization, Comparison, and Evaluation of Control Techniques by Naruttam Kumar Roy (16904544)

“…Integrating intelligent methods, such as fuzzy logic, genetic algorithm, non-convex optimization, and heuristic optimization, signify intelligent control methods. …”

A new variable structure DC motor controller using geneticalgorithms by Al-Hamouz, Z.M.

“…This paper presents a new application of the genetic algorithm for the selection of the variable structure controller (VSC) feedback gains and switching vector for a separately excited DC motor. …”
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A Novel Centrality-Based Approach for Link Prediction by El Khoury, Elissa Lichaa

“…Namely, we consider weighted betweenness, closeness and Katz centralities, in addition to the Resource Allocation and Adamic-Adar indices. We also use a genetic algorithm to optimize the weights of these metrics, reflecting their contributions to link prediction. …”
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Design of a vibration absorber for harmonically forced damped systems by Issa, Jimmy

“…Two different numerical approaches are used in solving the problem; the first is based on the genetic algorithm technique and the second on the downhill simplex method. …”
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A new fuzzy logic controller based IPM synchronous motor drive by Abido, M.A.

“…The FLC parameters are optimized by genetic algorithm. The complete vector control scheme incorporating the FLC is successfully implemented in real-time using a digital signal processor board DS 1102 for a laboratory 1 hp interior permanent magnet (IPM) motor. …”
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Investigating the Impact of Skylights and Atrium Configurations on Visual Comfort and Daylight Performance in Dubai Shopping Malls by SANAD, AYMAN ADEL AHMED

“…Annual simulations are used to assess seasonal variations, while sensitivity analysis identifies key parameters. A genetic algorithm and multi-objective optimisation (MOO) simulations are used to generate optimal configurations, summarised in the form of a Pareto front selection criteria guide the choice of the optimum solution, which is then applied and analysed in a case study. …”
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Improving passenger satisfaction at Kuwait International Airport by using multi-objective optimisation by Alsaber, Ahmad

“…The proposed methods employ optimisation techniques such as mixed integer goal programming (MIGP) and genetic algorithm (GA) to offer a comparative multi-solution outcome towards optimising the passenger quality of services at airport departure check-in. …”
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A Dual Vibration Absorber for Vibration Suppression of Harmonically Forced Systems by El Khoury, Elie

“…Then, a numerical technique based on both the genetic algorithm and the search simplex method is used to calculate the optimal system parameters. …”
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Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information by M. Ghoniem, Rania

“…For classifying unimodal data of either speech or EEG, a hybrid fuzzy c-means-genetic algorithm-neural network model is proposed, where its fitness function finds the optimal fuzzy cluster number reducing the classification error. …”
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Practical single node failure recovery using fractional repetition codes in data centers by Itani, May

“…Hence, a practical solution for node failures is presented by using a self-designed genetic algorithm that searches within the feasible solution space. …”
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An Evolutionary Meta-Heuristic for State Justification in Sequential Automatic Test Pattern Generation by El-Maleh, Aiman H.

“…Evolutionary algorithms have been effective in solving many search and optimization problems. …”
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Improving the Resilience of Smart Distribution Networks against Cyber Attacks by ElYamani, Mohamed ElHusseiny Mohamed

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Application of Metastructures for Targeted Low-Frequency Vibration Suppression in Plates by Ratiba F. Ghachi (14152455)

“…<h2>Purpose</h2> <p>We present an approach that combines finite element analysis and genetic algorithms to find the optimal configuration of local resonators created in the host structure to suppress their vibration in a target low-frequency range. …”

Dynamic single node failure recovery in distributed storage systems by Itani, M.

“…To minimize the system repair cost, we formulate our problem using incidence matrices and solve it heuristically using genetic algorithms for all possible cases of single node failures. …”
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Iterative heuristics for multiobjective VLSI standard cellplacement by Sait, Sadiq M.

“…We employ two iterative heuristics for the optimization of VLSI standard cell placement. These heuristics are based on genetic algorithms (GA) and tabu search (TS) respectively. …”
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EVOLUTIONARY HEURISTICS FOR MULTIOBJECTIVE VLSI NETLIST BI-PARTITIONING by Sait, Sadiq M.

“…These heuristics are based on Genetic Algorithms (GAs) and Tabu Search (TS) [sadiq et al., 1999] respectively. …”
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