Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network حسب Mohammad Reza Chalak Qazani (13893261)

"…Its purpose was to estimate shear and residual stress levels. Additionally, the multi-objective genetic algorithm (MOGA) was utilised to extract the most optimal parameters for the injection moulding process, aiming to minimise shear and residual stress and thereby increase the resistance of the final product. …"

RESOURCE LEVELING USING IMPROVED GENETIC ALGORITHM حسب unknown

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Scheduling and allocation in high-level synthesis using genetic algorithm حسب Ali, Shahid

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Nonlinear analysis of shell structures using image processing and machine learning حسب M.S. Nashed (16392961)

"…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …"

Socially Motivated Approach to Simulate Negotiation Process حسب Hammadih, Mohammed Zaher

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Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars حسب Abathar Al-Hamrani (16494884)

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Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation حسب Abualigah, Laith

"…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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An Evolutionary Algorithm for the Allocation Problem in High-Level Synthesis حسب Harmanani, Haidar

"…This paper presents an evolutionary algorithm to solve the datapath allocation problem in high-level synthesis. …"
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An improved kernelization algorithm for r-Set Packing حسب Abu-Khzam, Faisal N.

"…We present a reduction procedure that takes an arbitrary instance of the r -Set Packing problem and produces an equivalent instance whose number of elements is in O(kr−1), where k is the input parameter. …"
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A kernelization algorithm for d-Hitting Set حسب Abu-Khzam, Faisal N.

"…For a given parameterized problem, π, a kernelization algorithm is a polynomial-time pre-processing procedure that transforms an arbitrary instance of π into an equivalent one whose size depends only on the input parameter(s). …"
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Intelligent Rapidly-Exploring Random Tree Star Algorithm حسب Ahmed, Khidir Galal Eldin Khidir

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The Detection of Dysarthria Severity Levels Using AI Models: A Review حسب Afnan Al-Ali (16888695)

A Parallel Neural Networks Algorithm for the Clique Partitioning Problem حسب Harmanani, Haidar M.

"…Our model uses a large number of simple processing elements or neurons, based on the McCulloch-Pitts binary neuron. …"
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Adapted arithmetic optimization algorithm for multi-level thresholding image segmentation: a case study of chest x-ray images حسب Abu Zitar, Raed

"…The picture histogram is used to display the algorithm's potential solutions. …"
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Meta-Heuristic Procedures for the Multi-Resource Leveling Problem with Activity Splitting حسب AlSayegh, Hadeel Yacoub

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Brain Source Localization in the Presence of Leadfield Perturbations حسب Momin, Rabiya Nakhat

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A combined algorithm based on finite elements and a modified methodof characteristics for the analysis of the corona in wire-ductelectrostatic precipitators حسب Al-Hamouz, Z.M.

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Scheduling and allocation in high-level synthesis using stochastic techniques حسب Sait, Sadiq M.

"…In this work, a unique approach to scheduling and allocation problem using the genetic algorithm (GA) is described. This approach is different from a previous attempt using GA (Wehn et al., IFIP Working Conference on Logic and Architecture Synthesis, Paris, 1990, pp. 47–56) in many respects. …"
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A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011) حسب Kozhaya, David Elias

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Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms حسب Harmanani, H. M.

"…The method is based on a genetic algorithm that efficiently explores the testable design space and finds a sub-optimal test registers assignment for each k-test session. …"
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