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

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Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques by Fares, Samar

“…An objective function utilizing the covariance of the fused tracks is used by the first algorithm while a cost function based on the Kullback-Leibler (KL) divergence measure is used in the second case for training the LSTM. …”
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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System UsingA Time-Multiplied Cost Function by Boukas, EK

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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function by Boukas, EK

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Guaranteed Cost Control Of A Markov Jump Linear Uncertain System Using A Time-Multiplied Cost Function by Boukas, EK

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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems by Almajed, Rasha

“…In the event of a violation in internet security, an attacker was able to interfere with the system's functions, which might result in catastrophic consequences. …”
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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. …”
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From Collatz Conjecture to chaos and hash function by Masrat Rasool (17807813)

“…<p>The non-linear property of Chaos is a promising approach to information security, and many accomplishments have been made by combining Chaos with several sub-security domains, including chaos-based stream ciphers, block ciphers, image encryption, and hash functions. …”

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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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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Economic load dispatch using memetic sine cosine algorithm by Abu Zitar, Raed

“…SCA is a recent population based optimizer turned towards the optimal solution using a mathematical-based model based on sine and cosine trigonometric functions. As other optimization methods, SCA has main shortcoming in exploitation process when a non-linear constraints problem like ELD is tackled. …”
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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. …”

New Fast Arctangent Approximation Algorithm for Generic Real-Time Embedded Applications by Mohieddine Benammar (18103039)

“…This paper presents a novel technique that combines the advantages of both rational formulae and LUT approximation methods. The new algorithm exploits the pseudo-linear region around the tangent function zero point to estimate a reduced input arctangent through a modified rational approximation before referring this estimate to its original value using miniature LUTs. …”

Face Recognition in Uncontrolled Indoor Environment by Abuqaaud, Kamal Adel

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A systolic algorithm for VLSI design of a 1/N rate Viterbi decoder by Sait, Sadiq M.

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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)

“…<h3>Purpose</h3><p dir="ltr">To identify the impact of <i>CYP2C9*2, *3, VKORC1−1639 G>A </i>and <i>CYP4F2*3</i> on warfarin dose in an Arab population. …”

Shuffled Linear Regression with Erroneous Observations by Saab, Samer S.

“…We propose an optimal recursive algorithm that updates the estimate from the underdetermined function that is based on that permutation-invariant constraint. …”
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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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