Search Results - (( java implication based algorithm ) OR ( using meta study algorithm ))

Studying the effect of training Levenberg Marquardt neural network by using hybrid meta-heuristic algorithms by Abubakar, Adamu, Khan, Abdullah, Nawi, Nazri Mohd, Rehman, M. Z., Teh , Ying Wah, Chiroma , Haruna, Herawan, Tutut

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Comparative study of meta-heuristics optimization algorithm using benchmark function by Ismail, I., Halim, A.H.

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Symbiotic organisms search optimization algorithm in cloud computing: a nature-inspired meta-heuristic by Sa'ad, Suleiman, Abdullah, Muhammed, Abdullah, Azizol, Ayob, Fahrul Hakim

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Comparative Study between Flower Pollination Algorithm and Cuckoo Search Algorithm for t-way Test Data Generation by Abdullah, Nasser, Kamal Z., Zamli

“…As a consequence, several meta-heuristic algorithms have been used as the basis of t-way strategies. …”
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Performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment by Mohammed, Faten Ameen Saif

“…Thus, this study focuses on optimizing the hybrid meta-heuristic (genetic algorithm along with DE algorithm that minimizes the completion time and enhances the performance of the task scheduling. …”
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Studying the Effect of Training Levenberg Marquardt Neural Network by Using Hybrid Meta-Heuristic Algorithms by Abubakar, A., Khan, A., Nawi, N.M., Rehman, M.Z., Teh, Y.W., Chiroma, H., Herawan, T.

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Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions by Mazlina, Abdul Majid, Alsariera, Yazan A., Alamri, Hammoudeh S., Nasser, Abdullah M., Kamal Z., Zamli

“…In order to help engineers make a sound decision on the selection amongst the best meta-heuristic algorithms for the problem at hand, there is a need to assess the performance of each algorithm against common case studies. …”
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Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences by Adnan Ashraf, Sobia Pervaiz, Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Ag. Ibrahim, Joel J. P. C. Rodrigues, Danda B. Rawat

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Meta-heuristic structure for multiobjective optimization case study: Green sand mould system by Ganesan, T., Elamvazuthi, I., KuShaari, K.Z., Vasant, P.

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Locust- inspired meta-heuristic algorithm for optimising cloud computing performance by Fadhil, Mohammed Alaa

“…The first contribution entails a study on server consolidation, which employs the Locust Scheduling Meta-Heuristic Algorithm (LACE). …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification by Mohd. Nawi, Nazri, M. Z., Rehman, Hafifi, Nurfarian, Khan, Abdullah, Siming, Insaf Ali

“…This study intends to show the superiority (time performance and quality of solution) of the proposed meta-heuristic Bat-BP algorithm over other more standard neural network training algorithms. …”
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A new meta heuristic evolutionary programming (NMEP) in optimizing economic energy dispatch by Mohamad Ridzuan, Mohamad Radzi, Hassan, Elia Erwani, Abdullah, Abdul Rahim, Bahaman, Nazrulazhar, Abdul Kadir, Aida Fazliana

“…The proposed optimization algorithm, namely New Meta-Heuristic Evolutionary Programming (NMEP) algorithm is followed to Meta-Heuristic Evolutionary Programming (Meta-EP) approach with some modification where the cloning process embedded as a significant progress during the implementation. …”
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An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation by Kamal Z., Zamli, Fakhrud, Din, Kendall, Graham, Ahmed, Bestoun S.

“…Although useful, meta-heuristic algorithms that make up these strategies often require specific domain knowledge in order to allow effective tuning before good quality solutions can be obtained. …”
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An optimal LFC in two-area power systems using a meta-heuristic optimization algorithm by Najeeb M., Mansor M., Feyad H., Taha E., Abdullah G.

“…In this study, an optimal meta-heuristic optimization algorithm for load frequency control (LFC) is utilized in two-area power systems. …”

HEURISTIC OPTIMIZATION OF BAT ALGORITHM FOR HETEROGENEOUS SWARMS USING PERCEPTION by Kappagantula, S., Vojjala, S., Iyer, A.A., Velidi, G., Emani, S., Vandrangi, S.K.

“…In this paper, we study the advantages of fusing the Meta-Heuristic Bat Algorithm with Heuristic Optimization. …”
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Recent advances in meta-heuristic algorithms for training multilayer perceptron neural networks by Al-Asaady, Maher Talal, Mohd Aris, Teh Noranis, Mohd Sharef, Nurfadhlina, Hamdan, Hazlina

“…Despite the growing use of MHAs, existing studies often focus on specific subsets of algorithms or narrow application domains, leaving a gap in understanding their comprehensive potential and comparative performance across diverse classification tasks. …”
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Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

“…The machine learning techniques are used to predict lung cancer in this study. First, the Computed Tomography (CT) images obtained from the Cancer Imaging Archive (CIA) dataset processed with the help of a weighted mean histogram equalization approach that used to eliminate the noise information from CT image. …”
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Elitist hybrid migrating birds optimization and genetic algorithm based strategy for T-way test suite generation by Hasneeza Liza, Zakaria

“…Although useful, much existing meta-heuristic based strategies have not sufficiently explored the adoption of more than one meta-heuristic to perform the search (termed hybridization). …”
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Embedded Meta evolutionary-firefly algorithm-ANN for multi dg planning in distribution system / Siti Rafidah Abdul Rahim by Abdul Rahim, Siti Rafidah

“…In this study, Meta Evolutionary–Firefly Algorithm (EMEFA) was initially developed to expedite the computational time in multi-DG installation with improved accuracy. …”
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Component-wise analysis of metaheuristic algorithms for novel fuzzy-meta classifier by Talfur, Khasif Hussain

“…To address the significant gap between theory and practice in metaheuristic research, this study proposed in-depth analysis approach using component-view of metaheuristic algorithms and diversity measurement for determining exploration and exploitation abilities. …”
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