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testing algorithm » cosine algorithm (Expand Search)
coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
element » elements (Expand Search)
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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem
Published 2002“…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and c cliques. …”
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A FUZZY EVOLUTIONARY ALGORITHM FOR TOPOLOGY DESIGN OF CAMPUS NETWORKS
Published 2020“…In this paper, we present a Simulated Evolution algorithm for the design of campus network topology. …”
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Intelligent Rapidly-Exploring Random Tree Star Algorithm
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4
Fuzzy simulated evolution algorithm for topology design of campusnetworks
Published 2000“…We present an approach based on the simulated evolution algorithm for the design of campus network topology. …”
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Evolutionary algorithms for state justification in sequential automatic test pattern generation
Published 2005“…Sequential circuit test generation using deterministic, fault-oriented algorithms is highly complex and time consuming. …”
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Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification
Published 2025“…In this study, we introduce an innovative method for the multi-classification of breast cancer histopathological images utilizing Bidirectional Recurrent Neural Networks (BRNN). The BRNN structure consists of four unique elements: the backbone branch for transfer learning, the Gated Recurrent Unit (GRU), the residual collaborative branch, and the feature fusion module. …”
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…The problem consists of deciding the number, types, and locations of the network active elements (hubs, switches, and routers), as well as the links and their capacities. …”
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…The problem consists of deciding the number, types, and locations of the network active elements (hubs, switches, and routers), as well as the links and their capacities. …”
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Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network
Published 2024“…Computational techniques, like the finite element method, are used to analyse behaviours based on varied input parameters. …”
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Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques
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13
Design of adaptive arrays based on element position perturbations
Published 1993“…The proposed adaptive system is used to form automatically the required nulls in the direction of arrival of the interference. The design has been tested on arrays of three, five and eight elements. …”
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On the Optimization of Band Gaps in Periodic Waveguides
Published 2025“…<h3 dir="ltr">Purpose</h3><p dir="ltr">This work applies a computational framework for vibration attenuation in periodic structures by combining the established wave and finite element (WFE) method with nature-inspired optimization algorithms. …”
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Test bus assignment, sizing, and partitioning for system-on-chip
Published 2007“…The test access mechanism (TAM) is an important element of test architectures for embedded cores and is responsible for on-chip test pattern transport from the source to the core under test to the sink. …”
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Large language models for code completion: A systematic literature review
Published 2024“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”
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Nonlinear analysis of shell structures using image processing and machine learning
Published 2023“…We show that the results of the trained network agree well with the results of the nonlinear finite element analysis. …”
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Adaptive bias simulated evolution algorithm for placement
Published 2001“…A new solution is evolved from current solution by relocating some of the solution elements. Elements with lower goodnesses have higher probabilities of getting selected for perturbation. …”
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