Predicting Android Malware Using Evolution Networks by Chahine, Joy

“…This issue requires the development of efficient solutions in order to keep up with the continuous evolution of malware. With this aim, we introduce evolutionary networks, and particularly the Susceptible-Infectious-Susceptible (SIS) model, as a way to address the limitations of previous studies which are typically based on traditional machine learning models. …”
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Evolution Of Activation Functions for Neural Architecture Search by Nader, Andrew

“…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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Optimal design of power system stabilizers using evolutionary programming by Abido, M.A.

“…Incorporation of EP algorithm in the design of PSSs significantly reduces the computational burden. …”
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Logarithmic spiral search based arithmetic optimization algorithm with selective mechanism and its application to functional electrical stimulation system control by Abu Zitar, Raed

“…A biomedical application of a novel metaheuristic optimizer is proposed in this paper by constructing an enhanced arithmetic optimization algorithm (AOA). The latter algorithm was constructed using the logarithmic spiral (Ls) search mechanism from the whale optimization algorithm and the greedy selection scheme from the differential evolution algorithm. …”

Hybrid Cooperative Co-evolution for Large Scale Optimization by El-Abd, Mohammed

“…In this paper, we propose the idea of hybrid cooperative co-evolution (hCC). In CC, multiple instances of the same evolutionary algorithm work in parallel, each optimizes a different subset of the problem in hand. …”
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Particle Swarm Optimization with Adaptive Bounds. IEEE Congress on Evolutionary Computation by El-Abd, Mohammed

“…Estimation of distributions algorithms (EDAs) are a class of evolutionary algorithms that build and maintain a probabilistic model capturing the search space characteristics and continuously use this model to generate new individuals. …”
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Hybrid Cooperative Co-evolution for the CEC15 Benchmarks by El-Abd, Mohammed

“…In its second stage, the method adopts different algorithms within the cooperative co-evolution (CC) framework to simultaneously optimize the generated groups. …”
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Reinforced steering Evolutionary Markov Chain for high-dimensional feature selection by Atiq ur Rehman (3044409)

“…(ii) To support the global convergence of the algorithm and manage its computational complexity, a restricted group of the most effective agents is maintained within the evolutionary population. …”

Digital circuit design through simulated evolution (SimE) by Sait, Sadiq M.

“…In this paper, the use of simulated evolution (SimE) algorithm in the design of digital logic circuits is proposed. …”
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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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An evolutionary meta-heuristic for state justification insequential automatic test pattern generation by El-Maleh, A.H.

“…Evolutionary algorithms have been effective in solving many search and optimization problems. …”
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Evaluating Parallel Simulated Evolution Strategies for VLSI Cell Placement by Sait, Sadiq M.

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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy by Haitao Xu (435549)

“…The complex gas hydrate prevention unit is simulated using the MLPNN model trained by 20 different optimization algorithms. This study investigates the gradient-based, evolutionary, and Bayesian-based optimization algorithms. …”

Cooperative Co-evolution using LSHADE with Restarts For The CEC15 Benchmarks by El-Abd, Mohammed

“…In this paper, we test the performance of an LSHADE Cooperative Co-evolutionary (CC) algorithm using the CEC15 benchmarks. …”
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Simulated evolution for timing and low power VLSI standard cell placement by Sait, Sadiq M.

“…Abstract This paper presents a Fuzzy Simulated Evolution algorithm for VLSI standard cell placement with the objective of minimizing power, delay and area. …”
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Fuzzy simulated evolution for power and performance optimization ofVLSI placement by Sait, Sadiq M.

“…In this paper, an algorithm for VLSI standard cell placement for low power and high performance design is presented. …”
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A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments by Barada, Hassan

“…The performance of SE is compared with a genetic algorithm approach for the same problem with respect to the quality of solutions generated, and timing requirements of the algorithms. r 2003 Elsevier Science Ltd. …”
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Fast force-directed/simulated evolution hybrid for multiobjective VLSI cell placement by Sait, Sadiq M.

“…In this work, a fast hybrid algorithm is designed to address this problem. The algorithm employs simulated evolution (SE), an iterative search heuristic that comprises three steps: evaluation, selection and allocation. …”
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Assigning proctors to exams using scatter search. (c2006) by Zeidan, Moujab Moustapha

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Differential Evolution and Its Applications in Image Processing Problems: A Comprehensive Review by Chakraborty, Sanjoy

“…Differential evolution (DE) is one of the highly acknowledged population-based optimization algorithms due to its simplicity, user-friendliness, resilience, and capacity to solve problems. …”
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