RESOURCE LEVELING USING IMPROVED GENETIC ALGORITHM by unknown

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

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

“…The proposed model was developed and implemented using MATLAB software. A Pareto front was derived from the MOGA by employing the T2FNN within the process, identifying fourteen optimal solutions.…”

Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms by 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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Parallel algorithm for hardware implementation of inverse halftoning by Siddiqi, U.F.

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An Evolutionary Algorithm for the Allocation Problem in High-Level Synthesis by Harmanani, Haidar

“…This paper presents an evolutionary algorithm to solve the datapath allocation problem in high-level synthesis. …”
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A Parallel Algorithm for Inverse Halftoning and its Hardware Implementation by Siddiqi, Umair F.

“…Keywords: (1) Inverse Halftoning (2) Hardware Implementation (3) Look-Up Table Inverse Halftoning (4) Complex Programmable Logic Devices (CPLD) (5) Image Processing…”
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Formal synthesis of VLSI layouts from algorithmic specifications by Sait, Sadiq M.

“…In this paper we present a formal approach for high level synthesis. This formal high level syntesis system uses recursive algorithms to model the behaviour to be synthesized. …”
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Spectrum Sensing Algorithms for Cooperative Cognitive Radio Networks by Hassan, Yasmin Adel

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Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation by 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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The Detection of Dysarthria Severity Levels Using AI Models: A Review by Afnan Al-Ali (16888695)

Optimization and control of solar-wind islanded hybrid microgrid by using heuristic and deterministic optimization algorithms and fuzzy logic controller by Sk. A., Shezan

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A PARALLEL AND DISTRIBUTED FRAMEWORK FOR IMPLEMENTING BACK PROPAGATION ALGORITHM IN BIG DATA by unknown

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Image-Based Air Quality Estimation Using Convolutional Neural Network Optimized by Genetic Algorithms: A Multi-Dataset Approach by Arshad Ali Khan (23152516)

“…This paper proposes a new approach using convolutional neural networks with genetic algorithms for estimating air quality directly from images. …”

New Fast Arctangent Approximation Algorithm for Generic Real-Time Embedded Applications by Mohieddine Benammar (18103039)

“…The eZDSP-F28335 platform has been used for practical implementation and results validation of the proposed technique. …”

Design of acoustic absorbing metasurfaces using a data-driven approach by Hamza Baali (14603380)

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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 picture histogram is used to display the algorithm's potential solutions. …”
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Optimized FPGA Implementation of PWAM-Based Control of Three—Phase Nine—Level Quasi Impedance Source Inverter by Syed Rahman (569240)

“…In this paper, closed loop control of nine - level three - phase qZSI system is implemented using single FPGA control board thereby eliminating above said problems. …”

Meta-Heuristic Procedures for the Multi-Resource Leveling Problem with Activity Splitting by AlSayegh, Hadeel Yacoub

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Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”