Search Results - (( wolf optimization learning algorithm ) OR ( java application scheduling algorithm ))

Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Aloufi, Khalid, Kamal Z., Zamli

“…Many variants have been developed to cope with this problem and improve algorithm performance. In this paper, a hybrid algorithm of HS with grey wolf optimizer (GWO) has been developed to solve the problem of HS parameter selection. …”
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Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost by Chen, Suihai, Bong, Chih How, Chiu, Po Chan

“…Under the background of big data, it is of practical significance to prevent loan risk by the machine learning algorithm. Aiming at the characteristics of unbalanced loan data and high noise, this paper proposes an improved Gray Wolf optimization strategy (PSOEBGWO). …”
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Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm by Jaber M.M., Yussof S., Elameer A.S., Weng L.Y., Abd S.K., Nayyar A.

“…Automation; Complex networks; Computational complexity; Deep learning; Image analysis; Medical imaging; Pattern matching; Pixels; Distribution pattern-matching rule; Distribution patterns; Gray wolf-optimized deep convolution network; Gray wolves; Learning patterns; Matching rules; Medical fields; Medical image analysis; Pattern matching algorithms; Pattern-matching; Convolution…”

An Improved Grey Wolf Optimization-based Learning of Artificial Neural Network for Medical Data Classification by Kumar, Narender, Kumar, Dharmender

“…Grey wolf optimization (GWO) is a recent and popular swarm-based metaheuristic approach. …”
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Long Term Load Forecasting using Grey Wolf Optimizer - Artificial Neural Network by Yasin Z.M., Salim N.A., Ab Aziz N.F.

An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…Grey Wolf Optimizer (GWO) is a recently developed meta-heuristic algorithm which is appealing to researcher owing to its demonstrated performance as cited in the scientific literature. …”
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One-Dimensional Convolutional Neural Network with Variable Weights Grey Wolf Optimizer for Modeling of Sand Retention Test by Abd Razak, Nurul Nadhirah

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Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

“…The CPU profiler of JavaTM VisualVM measures the number of invocations of scheduling event handlers (procedures) in each algorithm as well as the total time spent in all invocations of this handler. …”
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Prediction of solar irradiance using grey Wolf optimizer least square support vector machine by Yasin Z.M., Salim N.A., Aziz N.F.A., Mohamad H., Wahab N.A.

“…Least Squares Support Vector Machine (LSSVM) has strong ability to learn a complex nonlinear problems. In GWO-LSSVM, the parameters of LSSVM are optimized using Grey Wolf Optimizer (GWO). …”

Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm by Ullah, Wasif, Muhammad Ammar, Nik Mu’tasim, Mohd Fadzil Faisae, Ab Rashid

“…This paper investigates the optimization of a CHFS problem using the Teaching Learning-Based Optimization (TLBO) algorithm. …”
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A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

“…In this type of environment it is nearly impossible to prove the effectiveness of a scheduling algorithm. Hence the main objective of this study is to develop a desktop grid simulator toolkit for measuring and modeling scheduler algorithm performance. …”
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

“…This paper reports the power fill techniques using GA in scheduling. Class timetabling problem is one of the applications in scheduling. …”
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Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

“…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection by Norfadzlan, Yusup, Izzatul Nabila, Sarbini, Dayang Nurfatimah, Awang Iskandar, Azlan, Mohd Zain, Didik Dwi, Prasetya

“…In the experiment, we conducted an evaluation of the effectiveness and efficiency of four nature-inspired binary algorithms for optimization namely Binary Particle Swarm Optimization (BPSO), Binary Grey Wolf Optimization algorithm (BGWO), Binary Differential Evolution algorithm (BDE), and Binary Salp Swarm algorithm (BSS) - in the context of human activity recognition (HAR). …”
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Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

“…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization by Kamal Z., Zamli

“…Many meta-heuristic algorithms have been developed to date (e.g. Simulated Annealing (SA), Particle Swarm Optimization (PSO), Teaching Learning based Optimization (TLBO), Grey Wolf Optimizer(GWO) to name a few). …”
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Hybrid harmony search algorithm for continuous optimization problems by Ala’a Atallah, Hamad Alomoush

“…Taken together, the proposed hybrid algorithm, called IHS-GWO, aims to address continuous optimization problems. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Unleashing the power of Manta Rays Foraging Optimizer: A novel approach for hyper-parameter optimization in skin cancer classification by Adamu, Shamsuddeen, Alhussian, Hitham, Aziz, Norshakirah, Abdulkadir, Said Jadid, Alwadin, Ayed, Abdullahi, Mujaheed, Garba, Aliyu

“…Empirical evaluations on diverse datasets (ISIC, PH2, HAM10000) showcase the significant superiority of the MRFO-based model over conventional optimization algorithms. The model achieves impressive accuracy and loss metrics (ISIC: 99.43 , 0.0250; PH2: 99.96 , 0.0033; HAM10000: 97.70 , 0.0626), outperforming alternative optimization algorithms such as the Grey Wolf Optimizer (98.33 accuracy, 0.17 loss), Whale Optimization Algorithm (96 accuracy), Grasshopper Optimization Algorithm (97.2 accuracy), Densnet121-MRFO (99.26 accuracy), InceptionV3 with GA (99.9 accuracy), and African Vulture Optimization Algorithm (92.7 accuracy). …”
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