Search Results - (( evolution optimization learning algorithm ) OR ( data replication system algorithm ))
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network
Published 2006“…Hybrid genetic algorithms are the combination of learning algorithms(Back propagation), usually working as evaluation functions, and genetic algorithms. …”
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Differential evolution for neural networks learning enhancement
Published 2008“…To overcome this problem, Differential Evolution (DE) has been used to determine optimal value for ANN parameters such as learning rate and momentum rate and also for weight optimization. …”
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Relationship based replication algorithm for data grid
Published 2014“…Data Grid is an infrastructure that manages huge amount of data files and provides intensive computational resources across geographically distributed systems.To increase resource availability and to ease resource sharing in such environment, there is a need for replication services.This research proposes a replication algorithm, termed as Relationship based Replication (RBR) that integrates users, grid and system perspective.In particular, the RBR includes information of three different relationships in identifying file(s) that requires replication; file-to-user, file-to-file and file-to-grid. …”
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Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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Dynamic replication algorithm in data grid: Survey
Published 2008“…For improving the performance of file accesses and to ease the sharing amongst distributed collaboration, such a system needs replication services. Data replication is a common method used to improve the performance of data access in distributed systems. …”
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Dual optimization approach in discrete Hopfield neural network
Published 2024“…Therefore, this research contributes to the improvement of the learning and retrieval phases by integrating the Hybrid Differential Evolution Algorithm and Swarm Mutation respectively. …”
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Navigating challenges and opportunities of machine learning in hydrogen catalysis and production processes: Beyond algorithm development
Published 2025“…This review uniquely focuses on harnessing the synergy between ML and computational modeling (CM) or optimization tools, as well as integrating multiple ML techniques with CM, for the synthesis of diverse hydrogen evolution reaction (HER) catalysts and various hydrogen production processes (HPPs). …”
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Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle
Published 2023“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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Binary Vote Assignment on Cloud Quorum Algorithm for Fragmented MyGRANTS Database Replication
Published 2015“…Data replication is one of the mechanisms to manage data since it improves data accessibility and reliability. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
Published 2011“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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Managing Fragmented Database Using BVAGQ-AR Replication Model
Published 2017“…The result shows that managing fragmented database replication through proposed BVAGQ-AR algorithm able to preserve data consistency. …”
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A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection
Published 2019“…Hence, a new co-evolution binary particle swarm optimization with a multiple inertia weight strategy (CBPSO-MIWS) is proposed in this work. …”
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…Nowadays, in the grid community, distributed and clustering system, a lot of work has been focused on providing efficient and safe replication management services through designing of algorithms and systems. …”
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Performances Of Metaheuristic Algorithms In Optimizing Tool Capacity Allocations
Published 2014“…In this research, the algorithms studied includes Genetic Algorithm, Particle Swarm Optimization Algorithm, Differential Evolution Algorithm, Harmony Search Algorithm, Teaching-LearningBased Optimization Algorithm and Black Hole Algorithm. …”
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Managing MyGRANTS Fragmented Database Using Binary Vote Assignment Grid Quorum with Association Rule (BVAGQ-AR) Replication Model
Published 2015“…Replication is one of the mechanisms managing data since it improves data access and reliability. …”
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A novel binary vote assignment grid quorum algorithm for distributed database fragmentation
Published 2011“…Data replication is one of the mechanisms in data grid architecture since it improves data access and reliability. …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…To evaluate the PMT’s performance and adaptability, the PMT was applied to four contemporary metaheuristic algorithms, Differential Evolution, Particle Swarm Optimization, Simulated Annealing, and Whale Optimization Algorithm, to solve 15 well-known benchmark functions as well as 2 real world problems based on the welded beam design and pressure vessel design. …”
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Development of read-one-write-all synchronization transaction daemon (row A-STD) in distributed system
Published 2010“…In distributed system environment, replicated data is the current trend to keep data updated in multiple sites. …”
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