Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm by De Rochechouart, Maxence

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

“…The performance of three machine learning (ML) algorithms was assessed to predict the wild blueberry harvest losses on the ground. …”

A New Penalty Function Algorithm For Convex Quadratic Programming by Bendaya, M.

“…In this paper, we develop an exterior point algorithm for convex quadratic programming using a penalty function approach. …”
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Adaptive step-size sign least mean squares by Aldajani, M.A.

“…A powerful adaptation scheme is used to adapt the step-size of the sign function inside the recursion of the sign algorithm. …”
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Don't understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures by Iryna Haponchyk (19691701)

“…In this paper, we trade off exact computation for enabling the use and study of more complex loss functions for coreference resolution. Most interestingly, we show that such functions can be (i) automatically learned also from controversial but commonly accepted coreference measures, e.g., MELA, and (ii) successfully used in learning algorithms. …”

Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm by Noor Habib Khan (22224775)

“…To avoid such issues and provide the optimal solution, there are some modifications are implemented into the internal structure of t‐LCA based on Weibull flight operator, mutation‐based approach, quasi‐opposite‐based learning and gorilla troops exploitation‐based mechanisms to enhance the overall strength of the algorithm to obtain the global solution. For validation of ILCA, the non‐parametric and the statistical analysis are performed using benchmark standard functions. …”

Design of acoustic absorbing metasurfaces using a data-driven approach by Hamza Baali (14603380)

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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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A Comparative Study of Elgamal Based Cryptographic Algorithms by Haraty, Ramzi A.

“…In this work we implement the classical and modified ElGamal cryptosystem to compare and to test their functionality, reliability and security. To test the security of the algorithms we use a famous attack algorithm called Baby-Step-Giant algorithm which works in the domain of natural integers. …”
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Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

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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. The proposed algorithm minimizes an objective function defined as a weighted sum of the LMS and LMF cost functions where the weighting factor is time varying and adapts itself so as to allow the algorithm to keep track of the variations in the environment. …”
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Tracking analysis of the NLMS algorithm in the presence of both random and cyclic nonstationarities by Moinuddin, M.

“…The results show that, unlike in the stationary case, the steady-state excess MSE is not a monotonically increasing function of the step size. Moreover, the ability of the adaptive algorithm to track the variations in the environment is shown to degrade with increasing frequency offset.…”
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A comparative study of ElGamal based digital signature algorithms by Haraty, Ramzi A.

“…We implement the classical and modified ElGamal digital signature scheme to compare and to test their functionality, reliability and security. To test the security of the algorithms we use a famous attack algorithm called Baby-Step-Giant algorithm which works in the domain of natural integers. …”
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An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection by Abu Zitar, Raed

“…The binary enhanced RSO is built based on three successive modifications: i) an S-shape transfer function is used to develop binary RSO algorithms; ii) the local search paradigm of particle swarm optimization is used with the iterative loop of RSO to boost its local exploitation; iii) three crossover mechanisms are used and controlled by a switch probability to improve the diversity. …”

A new tabu search algorithm for the long-term hydro scheduling problem by Mantawy, A.H.

“…The proposed implementation contributes to the enhancement of speed and convergence of the original tabu search algorithm (TSA). A significant reduction in the objective function over previous classical optimization methods and a simulated annealing algorithm has been achieved. …”
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GATS: A Novel Hybrid Algorithm for Multiobjective Cell Placement in VLSI Circuit Design by Sait, Sadiq M.

“…This paper addresses the optimization of cell placement step in VLSI circuit design [1]. A novel hybrid algorithm is proposed for performance and low power driven VLSI standard cell placement. …”
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Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

“…This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …”
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A novel AI approach for optimal deployment of EV fast charging station and reliability analysis with solar based DGs in distribution network by Fareed Ahmad (134672)

A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

“…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”