Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

“…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …”

Minimizing using BBO and DFO methods by El Zeghondy, Jean

“…In order to apply this algorithm to real life problems, two numerical methods need to be developed: A numerical method to solve nonlinear differential equations, and a numerical method to nd the minimum of an objective function (given only numerically) in fi nite dimensional spaces. …”
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Computational evluation of protein energy functions by Mansour, Nashat

“…However, the energy functions proposed so far by biophysicists and biochemists are still in the exploration phase and their usefulness has been demonstrated only individually. …”
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STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization by Muhammad Salman Khan (7202543)

Optimization and control of solar-wind islanded hybrid microgrid by using heuristic and deterministic optimization algorithms and fuzzy logic controller by Sk. A., Shezan

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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method by Amit Kumar Balyan (18288964)

“…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”

BUC algorithm for iceberg cubes by Nasr, George E.

“…In this paper, we implement the Bottom-Up Computation (BUC) algorithm for computing Iceberg cubes and conduct a sensitivity analysis of BUC with respect to the probability density function of the data. …”
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Iterative Least Squares Functional Networks Classifier by Faisal, Kanaan A

“…Both methodology and learning algorithm for this kind of computational intelligence classifier using the iterative least squares optimization criterion are derived. …”
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Evolution Of Activation Functions for Neural Architecture Search by Nader, Andrew

“…However, to the best of our knowledge, the design of new activation functions has mostly been done by hand. In this work, we propose the use of a self-adaptive evolutionary algorithm that searches for new activation functions using a genetic programming approach, and we compare the performance of the obtained activation functions to ReLU. …”
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Cross entropy error function in neural networks by Nasr, G.E.

“…The ANN is implemented using the cross entropy error function in the training stage. …”
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Improved scatter search algorithm for predicting all-atoms protein structures using charmm22 energy model. (c2010) by Ghalayini, Iman Adnan

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High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm by Badreddine Kanouni (23073244)

A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models by Osama Bassam J. Rabie (21323741)

“…<p dir="ltr">The Internet of Things (IoT) is extensively used in modern-day life, such as in smart homes, intelligent transportation, etc. …”

Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

“…Since we use Multi-objects to track, the Joint Probability Distribution Function (JPDA) estimates the best measurement values with a preset gating threshold. …”
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Tracking analysis of normalized adaptive algorithms by Moinuddin, M.

“…A unified approach is carried out using a mixed-norm-type error nonlinearity. Close agreement between analytical analysis and simulation results is obtained for the case of the NLMS algorithm. …”
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Evolutionary algorithm for protein structure prediction by Mansour, Nashat

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Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning by Sait, Sadiq M.

“…A series of experiments are performed to evaluate the efficiency of the algorithms. ISCAS-85/89 benchmark circuits are used and experimental results are reported and analyzed to compare the performance of GA, TS and SimE. …”
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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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Android Malware Detection Using Machine Learning by Al Ali, Shaikha

“…It was found that SVM using radial basis function (RBF) kernel achieved the highest performance with an accuracy of 99.5%. …”
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Accuracy of an internationally validated genetic-guided warfarin dosing algorithm compared to a clinical algorithm in an Arab population by Amr M. Fahmi (21632909)

“…After reaching warfarin maintenance dose, the dose was recalculated using the GWD and median absolute error (MAE) and the percentage of warfarin doses within 20% of the actual dose were calculated and compared for the two algorithms. …”