Search Results - (( wave optimization based algorithm ) OR ( parallel localization based algorithm ))

Enhanced Weight Optimized Recurrent Neural Networks Based On Sine Cosine Algorithm For Wave Height Prediction by Alqushaibi, Alawi Ali Manea

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Effective software fault localization based on complex network theory / Abubakar Zakari by Abubakar , Zakari

“…Furthermore, two novel fault localization techniques based on complex network theory, namely multiple fault localization based on complex network theory (FLCN-M) and single fault localization based on complex network theory (FLCN-S), are proposed to improve localization effectiveness, and to aid developers’ to localize multiple faults simultaneously in a single diagnosis rank list. …”
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Optimizing the efficiency of Oscillating Water Column (OWC) wave energy converter using genetic algorithm by Nallagownden, P., Alhaj, H.M.M., Sarwar, M.B.

“…This paper, describes a method to maximize the pneumatic system efficiency using optimization technique based on Genetic algorithm. This method involves an extraction of maximum incident wave energy corresponding to the wave height, determining of the best deep water length and maximizing the applied damping ratio which can lead to an increase in the pneumatic system efficiency. …”
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Healthcare Data Analysis Using Water Wave Optimization-Based Diagnostic Model by Kaur, Arvinder, Kumar, Yugal

“…In the proposed diagnostic model, a water wave optimization (WWO) algorithm was implemented for improving the diagnosis accuracy. …”
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Pipeline scour rates prediction-based model utilizing a multilayer perceptron-colliding body algorithm by Ehteram M., Ahmed A.N., Ling L., Fai C.M., Latif S.D., Afan H.A., Banadkooki F.B., El-Shafie A.

ENHANCED WEIGHT OPTIMIZED RECURRENT NEURAL NETWORKS BASED ON SINE COSINE ALGORITHM FOR WAVE HEIGHT PREDICTION by ALQUSHAIBI, ALAWI ALI ALI MANEA

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A Community-Based Fault Isolation Approach for Effective Simultaneous Localization of Faults by Zakari, Abubakar, Lee, Sai Peck, Targio Hashem, Ibrahim Abaker

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Low computational complexity for optimizing energy efficiency in mm-wave hybrid precoding system for 5G by Salh, Adeb, Audah, Lukman, Abdullah, Qazwan, Aydoğdu, Ömer, A. Alhartomi, Mohammed, Alsamhi, Saeed Hamood, A. Almalki, Faris, M. Shah, Nor Shahida

“…We propose effective alternating minimization algorithms based on the zero gradient method to establish fully-connected structures (FCSs) and partially-connected structures (PCSs). …”
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Low computational complexity for optimizing energy efficiency in mm-wave hybrid precoding system for 5G by Salh, Adeb, Audah, Lukman, Abdullah, Qazwan, Aydoğdu, Ömer, A. Alhartomi, Mohammed, Alsamhi, Saeed Hamood, A. Almalki, Faris, M. Shah, Nor Shahida

“…We propose effective alternating minimization algorithms based on the zero gradient method to establish fully-connected structures (FCSs) and partially-connected structures (PCSs). …”
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Enhanced weight-optimized recurrent neural networks based on sine cosine algorithm for wave height prediction by Alqushaibi, A., Abdulkadir, S.J., Rais, H.M., Al-Tashi, Q., Ragab, M.G., Alhussian, H.

“…Therefore, the wind plays an essential role in the oceanic atmosphere and contributes to the formation of waves. This paper proposes an enhanced weight-optimized neural network based on Sine Cosine Algorithm (SCA) to accurately predict the wave height. …”
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Optimized controllers for stabilizing the frequency changes in hybrid wind-photovoltaic-wave energy-based maritime microgrid systems by Peddakapu, K., Mohd Rusllim, Mohamed, Srinivasarao, P., Licari, J.

“…Furthermore, an Archimedes optimization algorithm (AOA) is used to optimize the 2DOF-TIDN controller. …”
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

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Hybridizing guided genetic algorithm and single-based metaheuristics to solve unrelated parallel machine scheduling problem with scarce resources by Abed, Munther H., Mohd Nizam, Mohmad Kahar

“…The single-based metaheuristics replaces the mutation in the genetic algorithm. …”
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Heuristic optimization-based wave kernel descriptor for deformable 3D shape matching and retrieval by Naffouti, S.E., Fougerolle, Y., Aouissaoui, I., Sakly, A., Mériaudeau, F.

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Heuristic optimization-based wave kernel descriptor for deformable 3D shape matching and retrieval by Naffouti, S.E., Fougerolle, Y., Aouissaoui, I., Sakly, A., Mériaudeau, F.

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Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad by Saima Gulzar, Ahmad

“…Similarly, when data parallelism is introduced in the algorithm the performance of the algorithm improved further by 12% in latency and 17% in throughput when compared to PDWA algorithm. …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

“…In some complex problems, the convergence rate can still be poor owing to becoming trapped in local optima. Opposition-based learning (OBL) has shown promising results to address the aforementioned issue. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

PMT: opposition-based learning technique for enhancing meta-heuristic performance by Alamri, Hammoudeh S., Kamal Z., Zamli

“…In some complex problems, the convergence rate can still be poor owing to becoming trapped in local optima. Addressing these issues, this research proposes a new general opposition-based learning (OBL) technique inspired by a natural phenomenon of parallel mirrors systems called the parallel mirrors technique (PMT). …”
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Design and analysis of management platform based on financial big data by Chen, Yuhua, Mustafa, Hasri, Zhang, Xuandong, Liu, Jing

“…In addition, a financial data management platform based on distributed Hadoop architecture is designed, which combines MapReduce framework with the fuzzy clustering algorithm and the local outlier factor (LOF) algorithm, and uses MapReduce to operate in parallel with the two algorithms, thus improving the performance of the algorithm and the accuracy of the algorithm, and helping to improve the operational efficiency of enterprise financial data processing. …”
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