Iterative Least Squares Functional Networks Classifier by Faisal, Kanaan A

“…The performance of this new intelligent systems scheme is demonstrated and examined using real-world applications. A comparative study with the most common classification algorithms in both machine learning and statistics communities is carried out. …”
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Stochastic evolution algorithm for technology mapping by Al-Mulhem, A.S.

“…SELF-Map is based on the Stochastic Evolution (SE) algorithm. The state space model of the problem is defined and suitable cost function which allows optimization for area, delay, or area-delay combinations is proposed. …”
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A new multimodulus blind equalization algorithm by Abrar, Shafayat

“…The proposed algorithm is obtained by removing the discontinuity found in the RCA cost function. …”
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A hybrid of clustering and meta-heuristic algorithms to solve a p-mobile hub location–allocation problem with the depreciation cost of hub facilities by Mahdi Mokhtarzadeh (11593310)

“…Three objective functions are considered to minimize costs, noise pollutions, and the harassment caused by the establishment of a hub for people, a new objective that locates hubs in less populated areas. …”

An efficient failure-resilient mutual exclusion algorithm for distributed systems leveraging a novel zero-message overlay structure by Mouna Rabhi (17086969)

“…The proposed algorithm overcomes these limitations by providing an effective solution to maintain a logarithmic cost in case of node failures. …”

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

“…A fitness function is constructed from the total operating cost of the generating units without penalty terms. …”
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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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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. The cross entropy function is proven to accelerate the backpropagation algorithm and to provide good overall network performance with relatively short stagnation periods. …”
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New fault models and efficient BIST algorithms for dual-portmemories by Amin, A.A.

“…The testability problem of dual-port memories is investigated. A functional model is defined, and architectural modifications to enhance the testability of such chips are described. …”
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Neural Networks as a Convex Problem by Khalil, Baha

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Application of Red Deer Algorithm in Optimizing Complex functions by Zitar, Raed

“…The Red Deer algorithm (RDA), a recently developed population-based meta-heuristic algorithm, is examined in this paper with the optimization task of complex functions. …”
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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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Evolutionary Algorithms for VLSIMultiobjective Netlist Partitioning by Sait, Sadiq M.

“…A series of experiments are performed to evaluate the efficiency of the algorithms. …”
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Evolutionary algorithms, simulated annealing and tabu search: a comparative study by Youssef, H.

“…The benchmark problem used is the floorplanning of very large scale integrated (VLSI) circuits. This is a hard multi-criteria optimization problem. Fuzzy logic is used to combine all objective criteria into a single fuzzy evaluation (cost) function, which is then used to rate competing solutions. # 2001 Elsevier Science Ltd. …”
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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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A deterministic heuristic algorithm for optimal multiprocessor scheduling. (c1995) by Moujabber, Bassam N.

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A hybridization of evolution strategies with iterated greedy algorithm for no-wait flow shop scheduling problems by Bilal Khurshid (16715865)

“…<p dir="ltr">This study investigates the no-wait flow shop scheduling problem and proposes a hybrid (HES-IG) algorithm that utilizes makespan as the objective function. …”

Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem by Mantawy, A.H.

“…This paper presents a new algorithm based on integrating genetic algorithms, tabu search and simulated annealing methods to solve the unit commitment problem. …”
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Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

“…The goal is to select a set of sensors based on norms of weighted distances cost function. …”
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Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images by Abu Zitar, Raed

“…The solutions are evaluated using Otsu's fitness function throughout the optimization process. The picture histogram is used to display the algorithm's potential solutions. …”
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