بدائل البحث:
algorithm within » algorithm its (توسيع البحث)
using function » using fusion (توسيع البحث)
algorithm fa » algorithm _ (توسيع البحث), algorithms a (توسيع البحث), algorithms _ (توسيع البحث)
algorithm within » algorithm its (توسيع البحث)
using function » using fusion (توسيع البحث)
algorithm fa » algorithm _ (توسيع البحث), algorithms a (توسيع البحث), algorithms _ (توسيع البحث)
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41
Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation
منشور في 2023"…This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding, called RSA-SSA. …"
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46
Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering
منشور في 2022"…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …"
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47
Minimizing using BBO and DFO methods
منشور في 2022"…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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masterThesis -
48
Computational evluation of protein energy functions
منشور في 2014"…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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conferenceObject -
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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
منشور في 2022"…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. …"
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51
BUC algorithm for iceberg cubes
منشور في 2003"…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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conferenceObject -
52
Iterative Least Squares Functional Networks Classifier
منشور في 2007"…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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53
Evolution Of Activation Functions for Neural Architecture Search
منشور في 2020"…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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masterThesis -
54
Cross entropy error function in neural networks
منشور في 2002"…The ANN is implemented using the cross entropy error function in the training stage. …"
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conferenceObject -
55
From Collatz Conjecture to chaos and hash function
منشور في 2023"…These sequences are then utilized within the diffusion and confusion structures of the hashing function. …"
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A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models
منشور في 2024"…<p dir="ltr">The Internet of Things (IoT) is extensively used in modern-day life, such as in smart homes, intelligent transportation, etc. …"
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59
On the Optimization of Band Gaps in Periodic Waveguides
منشور في 2025"…For the first optimization scenario, distribution-free analysis showed that at intermediate function evaluation budgets, detectable differences emerge among algorithms, whereas in the second scenario, these differences diminish at higher evaluation budgets (with no significant pairwise contrasts), indicating convergence. …"
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60
Tracking analysis of normalized adaptive algorithms
منشور في 2003"…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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article