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

“…The clique partitioning problem has important applications in many areas including VLSI design automation, scheduling, and resources allocation. In this paper we present a parallel algorithm to solve the above problem for arbitrary graphs using a Hopfield Neural Network model of computation. …”
Get full text
Get full text

A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs† by Harmanani, Haidar

“…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and k colours. …”
Get full text
Get full text
Get full text

Deep Reinforcement Learning for Resource Constrained HLS Scheduling by Makhoul, Rim

“…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
Get full text
Get full text
Get full text

Hardening the ElGamal cryptosystem in the setting of the second group of units. (c2011) by Fanous, Suzan Mohamad

Get full text
Get full text

Using genetic algorithms to optimize software quality estimation models by Azar, Danielle

“…The second approach optimizes…”
Get full text
Get full text
Get full text

Genetic and heuristic algorithms for regrouping service sites. (c2000) by Tabbara, Hiba

Get full text
Get full text

A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008) by Korkmaz, Rita

Get full text
Get full text

An image processing and genetic algorithm-based approach for the detection of melanoma in patients by Tokajian, Sima

“…The first phase consists of an image processing-based method that extracts the Asymmetry, Border Irregularity, Color Variation and Diameter of a given mole. The second phase classifies lesions using a Genetic Algorithm. …”
Get full text
Get full text
Get full text
Get full text

Prediction of EV Charging Behavior Using Machine Learning by Shahriar, Sakib

“…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
Get full text

Portfolio Selection Problem Using CVaR Risk Measures Equipped with DEA, PSO, and ICA Algorithms by Abdelouahed Hamdi (14158899)

“…There are different metrics for the calculation of the risk factor, among which the most important one is the Conditional Value at Risk (CVaR). …”

Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain by Jun Zhu (84054)

“…In contrast, VIIRS_ML AOD at 550 nm has overall higher positive MB of 0.13–0.14 and a higher correlation (0.93–0.94) with CE318 AOD. Secondly, we evaluate the aerosol model types assumed by each algorithm, as well as the aerosol optical properties used in the AOD retrievals. …”

A Framework for Predictive Modeling in Sustainable Projects by Labban, Tarek

Get full text

Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization by Abu Zitar, Raed

“…This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …”
Get full text

Improved Dwarf Mongoose Optimization for Constrained Engineering Design Problems by Agushaka, Jeffrey O.

“…The performance of the IDMO, using different performance metrics and statistical analysis, is compared with the DMO and eight other existing algorithms. In most cases, the results show that solutions achieved by the IDMO are better than those obtained by the existing algorithms.…”
Get full text

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

Get full text

Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

“…The research work carried out, in relation to attack detection ensemble learning, mainly aims to increase the performance of machine learning algorithms by combining their results. Most of the studies propose the use of some technique, existing ensemble learning or created by the authors, to detect some type of attack in particular and not attacks in general. …”
Get full text

Optimal Sizing and Techno-Economic Analysis of Hybrid Renewable Energy Systems—A Case Study of a Photovoltaic/Wind/Battery/Diesel System in Fanisau, Northern Nigeria by Nasser Yimen (16697129)

“…In the first step, the MATLAB environment was used to run simulations and optimize the system via the genetic algorithm. Then, techno-economic and emissions analysis was carried out in the second step to compare the proposed system to the existing traditional modes of rural electrification in sub-Saharan Africa, namely, the grid-extension and diesel generator. …”

Adaptive temperature control of a reverse flow process by using reinforcement learning approach by A. Binid (22046054)

“…Additionally, a second algorithm is presented to enhance the implementability of the reinforcement learning algorithm from a practical perspective. …”

Machine Learning-Based Approach for EV Charging Behavior by Shahriar, Sakib

Get full text

A Modified Oppositional Chaotic Local Search Strategy Based Aquila Optimizer to Design an Effective Controller for Vehicle Cruise Control System by Ekinci, Serdar

“…Lastly, we also demonstrate the good performing capability of the CmOBL-AO algorithm for real traffic cases. We show the CmOBL-AO-based real PIDD2 controller as the most efficient method to control a vehicle cruise control system.…”
Get full text